Running Gedmatch calculators on the command line with stevenliuyi/admix [Archive] - The Apricity Forum: A European Cultural Community

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Komintasavalta

10-24-2021, 08:01 PM

AFAIK, DIYDodecad (https://dodecad.blogspot.com/2011/08/how-to-make-your-own-calculator-for.html) only has Linux and Windows binaries, and I didn't want to install a VM, so I wasn't able to use it before. But I now found this Python-based alternative to it: https://github.com/stevenliuyi/admix.

$ wget https://reichdata.hms.harvard.edu/pub/datasets/amh_repo/curated_releases/V50/V50.0/SHARE/public.dir/v50.0_HO_public.{anno,ind,snp,geno}
$ f=v50.0_HO_public;convertf -p <(printf %s\\n genotypename:\ $f.geno snpname:\ $f.snp indivname:\ $f.ind outputformat:\ PACKEDPED genotypeoutname:\ $f.bed snpoutname:\ $f.bim indivoutname:\ $f.fam)
$ pip3 install git+https://github.com/stevenliuyi/admix
$ plink --bfile v50.0_HO_public --keep <(grep Chuvash33 v50.0_HO_public.fam) --recode 23
$ admix -f plink.txt -v 23andme -m K12b

Admixture calculation models: K12b

Calcuation is started...

K12b
Gedrosia: 2.06%
Siberian: 20.86%
Northwest African: 1.28%
Southeast Asian: 0.00%
Atlantic Med: 4.46%
North European: 53.12%
South Asian: 0.70%
East African: 0.00%
Southwest Asian: 1.85%
East Asian: 2.89%
Caucasus: 12.78%
Sub Saharan: 0.00%

It comes with files for these calculators: https://github.com/stevenliuyi/admix/tree/master/admix/data. It doesn't have files for K13, but where can I download them?

I used it to make K12b averages of Siberian samples from the Reich dataset:

,Gedrosia,Siberian,Northwest_African,Southeast_Asi an,Atlantic_Med,North_European,South_Asian,East_Af rican,Southwest_Asian,East_Asian,Caucasus,Sub_Saha ran
Chukchi,2.02,57.32,0,1.37,0,7.42,1.85,0.01,0,30.00 ,0,0.02
Dolgan,0.30,70.24,0,0.16,1.86,4.90,1.00,0.02,0.45, 20.23,0.62,0.23
Enets,3.16,66.82,0,0,0.95,17.61,0.15,0,0,11.30,0,0 .02
Even,0.92,49.56,0.12,0.31,5.90,19.70,0.63,0.08,1.0 2,18.40,3.35,0
Itelmen,2.57,55.38,0,1.45,0,6.50,1.22,0,0,32.82,0, 0.05
Ket,7.09,56.91,0.01,0.40,0.07,23.48,1.33,0.04,0,10 .60,0,0.07
Koryak,1.87,56.27,0,2.48,0,6.19,1.13,0,0,32.03,0,0 .04
Mansi,5.75,42.24,0,0.76,2.52,38.74,1.29,0.01,0,7.7 4,0.96,0
Nganasan,0.13,90.28,0.06,0.40,0.02,1.09,0.15,0.08, 0.02,7.63,0,0.13
Selkup,5.90,58.22,0.16,1.30,0.41,26.25,1.02,0,0.01 ,6.63,0.01,0.08
Todzin,2.53,61.11,0,0.92,0.46,6.92,1.72,0,0.32,26. 01,0,0
Tofalar,2.61,61.25,0.04,0.48,0.97,8.12,0.91,0.14,0 .56,24.37,0.55,0
Ulchi,0.05,43.23,0.03,1.24,0.02,0.13,0.43,0.06,0,5 4.67,0.04,0.09

I didn't try to eliminate any outliers or samples that looked mixed, but here's individual samples:

,Gedrosia,Siberian,Northwest_African,Southeast_Asi an,Atlantic_Med,North_European,South_Asian,East_Af rican,Southwest_Asian,East_Asian,Caucasus,Sub_Saha ran
Chukchi:ADR00057,0.88,53.31,0,0.13,0,9.44,3.47,0,0 ,32.78,0,0
Chukchi:ADR00059,2.17,54.93,0,0,0,8.11,1.66,0,0,33 .13,0,0
Chukchi:ADR00060,2.46,60.32,0,0.79,0,5.00,0,0,0,31 .42,0,0
Chukchi:ADR00061,0.99,59.88,0,2.31,0,7.16,2.77,0,0 ,26.89,0,0
Chukchi:ADR00064,1.34,55.80,0,1.77,0,8.67,1.60,0,0 ,30.82,0,0
Chukchi:ADR00065,2.97,57.07,0,1.94,0,5.59,1.93,0,0 ,30.51,0,0
Chukchi:ADR00066,0.81,57.01,0,0,0,7.01,3.03,0,0,31 .81,0,0.34
Chukchi:ADR00068,3.21,56.99,0,0.51,0,7.43,0.87,0,0 ,30.98,0,0
Chukchi:ADR00074,2.82,58.01,0,1.14,0,5.94,1.11,0,0 ,30.98,0,0
Chukchi:ADR00079,2.59,56.18,0,4.38,0,7.42,2.18,0,0 ,27.25,0,0
Chukchi:MC_06,1.97,55.80,0,0,0,8.35,1.06,0,0,32.82 ,0,0
Chukchi:MC_08,0.76,56.93,0,3.49,0,8.82,1.89,0.19,0 ,27.92,0,0
Chukchi:MC_14,3.44,56.91,0,3.32,0,8.94,1.24,0,0,26 .16,0,0
Chukchi:MC_15,1.47,59.29,0,0,0,5.93,3.18,0,0,30.13 ,0,0
Chukchi:MC_16,1.14,57.12,0,0.71,0,6.77,3.22,0,0,31 .04,0,0
Chukchi:MC_17,2.58,58.81,0,1.63,0,5.99,2.51,0,0,28 .49,0,0
Chukchi:MC_18,0.40,61.63,0,0.31,0,9.53,0.31,0,0,27 .82,0,0
Chukchi:MC_25,3.13,58.27,0,1.64,0,6.16,1.25,0,0,29 .54,0,0
Chukchi:MC_38,1.90,56.27,0,1.08,0,8.95,1.27,0,0,30 .53,0,0
Chukchi:MC_40,3.29,55.79,0,2.23,0,7.14,2.48,0,0,29 .08,0,0
Dolgan:Dolgan1708,0.01,70.78,0,0.19,0,2.20,1.11,0. 07,0,25.63,0,0
Dolgan:Dolgan3185,1.17,63.44,0,0,0.30,3.77,0,0,0.4 8,30.74,0,0.10
Dolgan:Dolgan3857,0,70.50,0,0.43,4.55,7.69,1.75,0, 0,12.38,2.50,0.19
Dolgan:Dolgan3875,0,76.26,0,0,2.59,5.92,1.12,0,1.3 2,12.16,0,0.63
Enets:Tuebingen02,3.77,69.76,0,0,0,13.71,0,0,0,12. 69,0,0.07
Enets:Tuebingen35,4.45,60.42,0,0,1.90,22.28,0,0,0, 10.94,0,0
Enets:Tuebingen44,1.25,70.28,0,0,0.94,16.83,0.45,0 ,0,10.26,0,0
Even:Nlk10,0.24,36.72,0,0,10.77,25.21,0.90,0,1.46, 14.22,10.47,0
Even:Nlk14,1.16,41.16,0,0.69,12.27,26.85,0,0,0,13. 29,4.58,0
Even:Nlk16,0.38,42.16,0,0.30,6.46,27.39,0.21,0,2.0 1,15.46,5.63,0
Even:Nlk18,0.23,74.01,0,0,0,0.16,0,0,0.31,24.58,0. 71,0
Even:Nlk19,3.73,20.49,0,0.37,13.15,43.42,3.18,0,1. 43,11.54,2.68,0
Even:Nlk3,0,72.04,0,0,0.49,0,0.23,0.32,0.33,25.77, 0.83,0
Even:Nlk5,1.65,46.38,0.95,0.91,4.09,23.51,0,0.36,1 .26,20.58,0.32,0
Even:Nlk6,0,63.48,0,0.19,0,11.09,0.52,0,1.39,21.79 ,1.55,0
Itelmen:Kor57,2.07,56.04,0,1.59,0,7.54,1.25,0,0,31 .50,0,0
Itelmen:Kor60,0.33,56.28,0,4.16,0,7.94,1.48,0,0,29 .81,0,0
Itelmen:Kor62,3.28,53.46,0,0.97,0,5.77,2.20,0,0,34 .21,0,0.11
Itelmen:Kor72,1.50,55.74,0,0.73,0,7.32,0.15,0,0,34 .34,0,0.21
Itelmen:Kor76,3.66,56.18,0,1.02,0,5.48,1.31,0,0,32 .35,0,0
Itelmen:Kor78,4.59,54.60,0,0.21,0,4.98,0.90,0,0,34 .72,0,0
Ket:Tuebingen101,5.18,60.24,0,0,0,22.73,2.17,0.24, 0,9.36,0,0.09
Ket:Tuebingen103,6.11,57.77,0,0.64,0,26.29,0,0,0,9 .19,0,0
Ket:Tuebingen104,8.01,54.84,0,0,0,23.12,1.42,0,0,1 2.60,0,0
Ket:Tuebingen76,6.88,57.50,0,3.24,0,22.97,0,0,0,9. 41,0,0
Ket:Tuebingen80,7.87,54.85,0,0,0,23.31,1.85,0,0,12 .12,0,0
Ket:Tuebingen81,7.27,56.69,0,0,0,22.56,1.31,0,0,12 .16,0,0
Ket:Tuebingen82,6.95,57.37,0,0,0,22.80,0.39,0,0,12 .49,0,0
Ket:Tuebingen83,7.12,57.74,0,0,0,20.51,1.47,0,0,13 .17,0,0
Ket:Tuebingen87,8.58,60.63,0,1.98,0,20.27,0.84,0,0 ,7.69,0,0
Ket:Tuebingen90,7.84,55.59,0,0.02,0,21.96,2.59,0,0 ,12.00,0,0
Ket:Tuebingen94,6.11,56.42,0,0,0,24.92,0,0,0,12.55 ,0,0
Ket:Tuebingen95,5.30,57.45,0,0,1.39,23.82,1.04,0,0 ,10.31,0,0.69
Ket:Tuebingen97,8.81,57.53,0,0,0,20.51,2.01,0,0,11 .13,0,0
Ket:TuebingenK15,5.85,53.42,0,0,0,28.47,1.63,0.30, 0,10.33,0,0
Ket:TuebingenK16,6.15,57.17,0,0,0,22.24,3.66,0.10, 0,10.55,0,0.13
Ket:TuebingenK17,9.10,55.32,0,1.80,0,24.76,0.38,0, 0,8.37,0,0.27
Ket:TuebingenK22,7.01,53.56,0.21,0,0.02,28.77,2.99 ,0.03,0,7.25,0,0.15
Ket:TuebingenK29,6.99,57.05,0,0,0,21.45,1.59,0,0,1 2.93,0,0
Ket:TuebingenK7,7.57,60.09,0,0,0,24.59,0,0,0,7.75, 0,0
Koryak:Kor2,1.98,57.07,0,4.71,0,5.20,2.03,0,0,28.6 5,0,0.35
Koryak:Kor22,2.96,56.18,0,3.85,0,6.26,0.17,0,0,30. 58,0,0
Koryak:Kor30,0.97,57.06,0,0.63,0,5.19,2.39,0,0,33. 76,0,0
Koryak:Kor35,1.89,56.22,0,3.48,0,5.26,0.88,0,0,32. 27,0,0
Koryak:Kor40,4.33,56.45,0,4.13,0,4.21,1.52,0,0,29. 36,0,0
Koryak:Kor49,1.22,54.91,0,1.57,0,7.39,1.40,0,0,33. 51,0,0
Koryak:Kor54,1.25,54.38,0,1.26,0,8.75,1.16,0,0,33. 21,0,0
Koryak:Kor61,1.97,56.49,0,0,0,7.77,0,0,0,33.76,0,0
Koryak:Kor66,0.24,57.64,0,2.67,0,5.65,0.59,0,0,33. 20,0,0
Mansi:Mansi43,5.49,35.11,0,0.37,7.92,35.94,0.90,0, 0,9.40,4.87,0
Mansi:Mansi48,7.42,39.45,0,0.62,7.35,33.06,2.57,0, 0,9.52,0,0
Mansi:Mansi56,7.72,39.63,0,0,2.52,37.88,2.27,0.05, 0,8.35,1.58,0
Mansi:Mansi76,9.66,44.98,0,0,0,30.22,3.94,0,0,11.2 0,0,0
Mansi:Mansi79,0,39.17,0,0,0,60.81,0.03,0,0,0,0,0
Mansi:Mansi84,0.62,47.22,0,1.51,0,39.22,0,0,0,10.1 6,1.26,0
Mansi:Mansi91,7.83,45.79,0,0,1.31,36.29,0,0,0,8.78 ,0,0
Mansi:Mansi94,7.24,46.54,0,3.60,1.02,36.46,0.59,0, 0,4.55,0,0
Nganasan:ADR00504,0,99.76,0,0.01,0,0,0,0,0,0.01,0, 0.24
Nganasan:ADR00507,0.27,88.51,0,0,0,0.57,0,0,0,10.1 4,0,0.51
Nganasan:ADR00508,0,88.31,0,0.78,0,1.72,0,0.16,0,9 .03,0,0
Nganasan:ADR00509,0.34,87.39,0,0,0,2.17,0,0,0,10.1 1,0,0
Nganasan:ADR00510,0,87.43,0,0,0,0.74,0,0,0,11.29,0 ,0.54
Nganasan:ADR00511,0,88.67,0.40,0,0.34,0.78,0,0,0,9 .81,0,0
Nganasan:ADR00512,0,87.02,0,0,0,0.32,0.33,0.39,0,1 1.94,0,0
Nganasan:ADR00513,0.87,90.33,0,0,0,0.04,0,0.07,0,8 .63,0,0.07
Nganasan:ADR00514,0,85.37,0,0,0,2.40,0,0,0,11.97,0 ,0.26
Nganasan:ADR00515,1.01,90.72,0,2.01,0,1.12,0,0,0,4 .99,0,0.16
Nganasan:Nov_005,0,90.25,0,1.65,0,0,0,0.12,0,7.98, 0,0
Nganasan:Tuebingen06,0,90.82,0.70,0,0,1.32,0,0,0.2 9,6.68,0,0.17
Nganasan:Tuebingen07,0,86.74,0.05,2.84,0,1.24,0,0, 0,8.84,0,0.29
Nganasan:Tuebingen106,0,89.52,0,0.72,0,1.99,0.51,0 .01,0,7.26,0,0
Nganasan:Tuebingen111,0,87.66,0,0,0,0.93,0,0,0,11. 23,0,0.18
Nganasan:Tuebingen112,0.09,93.44,0,0,0,1.09,0.48,0 ,0,4.90,0,0
Nganasan:Tuebingen114,0,87.01,0,0.68,0,4.63,0.41,0 ,0,7.28,0,0
Nganasan:Tuebingen116,0,88.29,0.63,0,0,0.78,0.26,0 .10,0,9.94,0,0
Nganasan:Tuebingen119,0,88.41,0,0,0,0.74,0,0.38,0, 10.45,0,0.02
Nganasan:Tuebingen12,0,92.80,0,0.12,0,0.81,0.17,0, 0.45,5.65,0,0
Nganasan:Tuebingen121,0,89.22,0,1.86,0,1.18,0,0,0, 7.75,0,0
Nganasan:Tuebingen123,0,89.01,0,0,0,1.45,0.24,0.13 ,0,8.84,0,0.34
Nganasan:Tuebingen124,0,99.66,0,0.01,0,0.27,0,0.01 ,0,0.01,0,0.08
Nganasan:Tuebingen126,1.62,89.23,0,1.07,0,0.82,0.0 5,0,0,7.21,0,0
Nganasan:Tuebingen127,0.03,89.20,0,0,0,1.20,0.99,0 ,0,8.17,0,0.41
Nganasan:Tuebingen14,0,99.93,0,0,0,0,0,0,0,0,0,0.0 7
Nganasan:Tuebingen17,0,89.81,0,0.17,0,2.40,0.70,0, 0,6.92,0,0
Nganasan:Tuebingen19,0.16,89.21,0,0,0,0.57,0.15,0. 23,0,9.68,0,0
Nganasan:Tuebingen21,0,88.64,0,0,0,1.92,0,0,0,9.43 ,0,0
Nganasan:Tuebingen23,0,87.02,0,1.06,0,2.10,0,0.67, 0,8.81,0,0.33
Nganasan:Tuebingen25,0,92.23,0,0,0.31,0.54,0.75,0. 21,0,5.78,0.13,0.04
Nganasan:Tuebingen27,0,97.36,0,0,0,0,0.04,0.08,0,2 .04,0,0.47
Nganasan:Tuebingen28,0,90.12,0.14,0.16,0,0.24,0,0, 0,9.08,0,0.27
Selkup:Selkup105,4.40,35.44,0.89,2.32,9.90,45.74,1 .20,0,0.11,0,0,0
Selkup:Selkup121,6.91,57.74,0,3.83,0,21.71,3.34,0, 0,6.47,0,0
Selkup:Selkup21,8.01,58.59,0,2.71,0,30.69,0,0,0,0, 0,0
Selkup:Selkup220,7.18,53.36,0.55,1.86,0,34.07,0.40 ,0,0,2.56,0,0
Selkup:Selkup38,4.43,67.41,0,2.61,0,25.22,0.33,0,0 ,0,0,0
Selkup:Selkup4,7.20,61.96,0,1.44,0,27.08,0,0,0,2.3 2,0,0
Selkup:Selkup4a,2.85,72.87,0,2.47,0,18.03,0,0,0,3. 78,0,0
Selkup:Selkup82,4.43,59.37,0,0,0,26.20,0.89,0,0,9. 11,0,0
Selkup:Selkup83,0.75,68.80,0,0.48,0,16.13,0,0,0,13 .70,0,0.14
Selkup:Selkup87,1.33,71.21,0,0,0,8.78,2.21,0,0,16. 47,0,0
Selkup:Tuebingen50,5.00,59.90,1.08,1.19,0,22.64,1. 35,0.07,0,8.77,0,0
Selkup:Tuebingen51,6.91,59.41,0,0.76,0,26.50,0,0,0 ,6.42,0,0
Selkup:Tuebingen52,0.99,58.23,0,6.39,0,31.91,0,0,0 ,2.48,0,0
Selkup:Tuebingen53,7.94,54.61,0,0,0,26.44,1.17,0,0 ,9.84,0,0
Selkup:Tuebingen54,7.32,54.78,0,0.41,0,26.96,1.81, 0,0,8.71,0,0
Selkup:Tuebingen58,6.91,58.89,0,0.93,0,24.90,0.87, 0,0,7.50,0,0
Selkup:Tuebingen59,6.19,57.77,0,1.10,0,27.27,0.91, 0,0,6.76,0,0
Selkup:Tuebingen60,6.22,57.34,0,2.63,0,25.15,1.59, 0,0,6.95,0,0.12
Selkup:Tuebingen62,7.11,57.97,0,0,0,26.66,0,0,0,7. 96,0,0.31
Selkup:Tuebingen64,8.60,52.84,0,0,0,25.62,1.61,0,0 ,10.71,0,0.63
Selkup:Tuebingen72,7.85,54.02,0,0.05,0,26.62,3.02, 0,0,8.42,0,0
Selkup:Tuebingen74,6.99,51.39,1.36,0,0,32.40,0.49, 0,0.22,6.85,0.31,0
Selkup:Tuebingen77,9.34,54.58,0,0,0,27.74,2.00,0,0 ,5.87,0,0.47
Selkup:Tuebingen79,6.65,58.86,0,0,0,25.43,1.24,0,0 ,7.48,0,0.34
Todzin:TUV-121,4.10,58.39,0,0.52,0.04,7.21,2.83,0,0,26.91,0,0
Todzin:TUV-195,2.52,65.01,0,2.25,1.33,5.60,1.93,0,0,21.34,0,0
Todzin:TUV-199,0.97,59.93,0,0,0,7.96,0.39,0,0.97,29.78,0,0
Tofalar:Vgut1,5.34,65.16,0,0,0,2.10,1.03,0,1.45,24 .93,0,0
Tofalar:Vgut11,0,64.21,0,0.70,0,7.20,0,0.71,0.08,2 7.10,0,0
Tofalar:Vgut12,1.87,63.29,0,1.91,0,9.22,0,0,0,23.7 1,0,0
Tofalar:Vgut13,2.81,63.61,0,0,0,7.19,0,0.24,0.12,2 6.04,0,0
Tofalar:Vgut14,3.99,26.79,0.56,0,11.81,37.91,1.88, 0.24,0,10.62,6.19,0
Tofalar:Vgut15,2.78,65.77,0,0,0,4.55,0,0.07,0.15,2 6.68,0,0
Tofalar:Vgut18,2.45,64.59,0,0.47,0,4.51,2.14,0,0,2 5.85,0,0
Tofalar:Vgut19,3.07,61.62,0,0.05,0,3.87,2.93,0,1.3 7,27.09,0,0
Tofalar:Vgut2,2.51,63.70,0,0,0,4.17,1.51,0.55,0.98 ,26.59,0,0
Tofalar:Vgut4,2.60,64.52,0,0,0,6.36,0,0,0,26.52,0, 0
Tofalar:Vgut6,3.69,64.59,0,0.43,0,4.67,1.18,0,0.08 ,25.36,0,0
Tofalar:Vgut7,1.26,68.68,0,0,0,1.99,1.21,0,3.07,23 .78,0,0
Tofalar:Vgut8,1.59,59.68,0,2.66,0.82,11.78,0,0,0,2 2.56,0.91,0
Ulchi:Ul1,0,33.06,0,1.61,0,0.56,0.81,0.26,0,63.63, 0,0.07
Ulchi:Ul10,0,37.22,0,0,0,0,0,0,0,62.78,0,0
Ulchi:Ul16,0,39.95,0,0,0,0.02,0,0,0,59.90,0,0.13
Ulchi:Ul19,0,29.16,0,4.15,0,0,1.82,0,0,64.88,0,0
Ulchi:Ul24,0.12,55.89,0,2.33,0.25,0,0,0,0,41.22,0. 12,0.07
Ulchi:Ul25,0,40.19,0.17,1.13,0,0.18,0,0,0,58.33,0, 0
Ulchi:Ul31,0,47.48,0,0,0,0,1.04,0,0,51.48,0,0
Ulchi:Ul33,0,48.09,0,1.03,0,0,0,0,0,50.61,0.27,0
Ulchi:Ul36,0,56.02,0,0,0,1.04,0,0,0.02,42.78,0.14, 0
Ulchi:Ul39,0,41.97,0,2.40,0,0,0,0,0,55.62,0,0
Ulchi:Ul43,0,48.12,0,3.21,0,0,0,0,0,48.67,0,0
Ulchi:Ul44,0.35,40.82,0,0,0,0,0,0,0,58.60,0.23,0
Ulchi:Ul5,0.72,44.87,0,0.45,0,0,0.83,0,0,53.14,0,0
Ulchi:Ul51,0,40.84,0,0,0,0,2.13,0,0,57.03,0,0
Ulchi:Ul52,0,42.08,0,4.92,0,0.05,0,0,0,52.51,0,0.4 4
Ulchi:Ul55,0,48.01,0.14,0.63,0,0.41,0,0,0,50.40,0, 0.41
Ulchi:Ul56,0,41.96,0,5.50,0,1.03,0,0,0,50.78,0,0.7 3
Ulchi:Ul59,0,43.57,0,0.21,0,0.06,1.08,0.21,0,54.87 ,0,0
Ulchi:Ul6,0,33.94,0,0,0,0,2.86,0,0,63.20,0,0
Ulchi:Ul65,0,50.85,0,0,0.28,0,0,0,0,48.86,0,0
Ulchi:Ul69,0,44.28,0.48,2.15,0,0,0,0,0,53.09,0,0
Ulchi:Ul70,0,44.59,0,0,0,0,0.01,0,0,55.00,0,0.39
Ulchi:Ul71,0,42.63,0,0,0,0,0.28,0.11,0,56.98,0,0
Ulchi:Ul72,0.07,43.66,0,0.71,0,0,0,0.90,0,54.53,0. 13,0
Ulchi:Ul74,0,41.40,0,0.56,0,0,0,0,0,57.96,0.08,0

PCA and heatmap of the new samples:

https://i.ibb.co/pzXXhkJ/p.pnghttps://i.ibb.co/P6VRtP4/h.png

I probably did something wrong, so I'm waiting for feedback from Lucas before I post more averages. Does this produce the same results as DIYDodecad, GEDmatch, or Admixture Studio?

Script for making population averages:

mkdir 23 admix
printf %s\\n Chukchi Dolgan Enets|awk 'NR==FNR{a[$0];next}$3 in a{print$1}' - v50.0_HO_public.ind|while read x;do plink --bfile v50.0_HO_public --allow-no-sex --keep <(awk '$2==x' "x=$x" v50.0_HO_public.fam) --recode 23 --out 23/$x;done
printf %s\\n 23/*.txt|while read l;do b=${l%.txt};admix -f $l -m K12b|grep %>admix/${b##*/};done
# printf %s\\n 23/*.txt|parallel -j10 'admix -f {} -m K12b|grep %>admix/{/.}' # run 10 parallel jobs
for x in admix/*;do sed 's/.* //' $x|tr -d %|paste -sd\ -|sed s/^/${x##*/}\ /;done|awk 'NR==FNR{a[$1]=$3;next}{print a[$1]":"$0}' v50.0_HO_public.ind -|tr \ ,>admix.csv
awk -F, '{n[$1]++;for(i=2;i<=NF;i++){a[$1,i]+=$i}}END{for(i in n){o=i;for(j=2;j<=NF;j++)o=o FS sprintf("%.2f",a[i,j]/n[i]);print o}}' admix.csv>admix.ave

Lucas

10-24-2021, 09:16 PM

Lucas

10-24-2021, 09:35 PM

It doesn't have files for K13, but where can I download them?

In AdmixtureStudio in app folder is created subfolder Calculators. Here are calc files for every of them, so K13, k15 too.

Komintasavalta

10-24-2021, 10:03 PM

In AdmixtureStudio in app folder is created subfolder Calculators. Here are calc files for every of them, so K13, k15 too.

It only comes with a .exe installer, and I don't want to install a Windows VM. Can someone upload the calculator files somewhere?

Lucas

10-24-2021, 10:45 PM

It only comes with a .exe installer, and I don't want to install a Windows VM. Can someone upload the calculator files somewhere?

K13 https://drive.google.com/file/d/1X1ndvtBP7YYDEM2PPZozV6IRFvekY7l8/view?usp=sharing
K15 https://drive.google.com/file/d/1xWD5C7bwmARhcWyuLnr5I14ANG4mUXWs/view?usp=sharing

Komintasavalta

10-25-2021, 01:52 PM

K13 https://drive.google.com/file/d/1X1ndvtBP7YYDEM2PPZozV6IRFvekY7l8/view?usp=sharing
K15 https://drive.google.com/file/d/1xWD5C7bwmARhcWyuLnr5I14ANG4mUXWs/view?usp=sharing

Ok, adding the calculators was straightforward. I copied the `.F` and `.alleles` files to `/usr/local/lib/python3.9/site-packages/admix/data`. Then I modified `admix_models.py` to add entries named K13 and K15 to the array returned by the `models` function, and I added these lines to the `populations` function:

elif model == 'K13':
return [('North_Atlantic','North_Atlantic'),
('Baltic','Baltic'),
('West_Med','West_Med'),
('West_Asian','West_Asian'),
('East_Med','East_Med'),
('Red_Sea','Red_Sea'),
('South_Asian','South_Asian'),
('East_Asian','East_Asian'),
('Siberian','Siberian'),
('Amerindian','Amerindian'),
('Oceanian','Oceanian'),
('Northeast_African','Northeast_African'),
('Sub-Saharan','Sub-Saharan')]
elif model == 'K15':
return [('North_Sea','North_Sea'),
('Atlantic','Atlantic'),
('Baltic','Baltic'),
('Eastern_Euro','Eastern_Euro'),
('West_Med','West_Med'),
('West_Asian','West_Asian'),
('East_Med','East_Med'),
('Red_Sea','Red_Sea'),
('South_Asian','South_Asian'),
('Southeast_Asian','Southeast_Asian'),
('Siberian','Siberian'),
('Amerindian','Amerindian'),
('Oceanian','Oceanian'),
('Northeast_African','Northeast_African'),
('Sub-Saharan','Sub-Saharan')]

I made these averages for K13 from the Reich dataset and from Tambets et al. 2018 (https://evolbio.ut.ee/Tambets2018/) (Khanty, Saami_Kola, and Saami_Sweden):

Aleut,15.28,35.26,3.07,4.61,1.58,0.44,1.38,3.08,17 .02,17.25,0.52,0.15,0.36
Enets,4.74,15.29,0.28,0.92,0.00,0.37,1.68,1.09,70. 16,4.10,0.68,0.00,0.70
Itelmen,0.00,4.39,0.00,0.00,0.00,0.00,1.80,12.25,6 2.76,17.18,1.07,0.00,0.54
Kalmyk,2.52,5.75,0.80,6.79,1.15,0.37,0.84,30.84,48 .41,1.56,0.56,0.06,0.37
Karelian,30.32,50.92,4.11,1.41,0.83,0.69,1.40,0.26 ,7.57,1.28,0.58,0.49,0.16
Kusunda,0.96,0.00,0.90,3.36,0.00,0.00,31.41,40.72, 18.24,0.88,2.46,0.72,0.34
Mansi,8.34,30.51,0.00,4.75,0.00,0.00,4.24,1.92,43. 90,5.26,0.81,0.14,0.13
Nasioi,0.08,0.49,0.34,0.00,0.17,0.23,4.44,21.24,0. 21,0.23,72.24,0.04,0.29
Newar,1.09,2.39,1.12,9.15,0.30,0.63,37.11,30.97,14 .64,0.99,1.01,0.09,0.51
Nganasan,0.00,2.75,0.00,0.00,0.02,0.01,0.44,0.41,9 4.26,1.61,0.21,0.03,0.27
Nogai_Astrakhan,9.15,14.62,4.35,11.10,4.02,1.05,1. 57,19.78,31.69,1.61,0.72,0.20,0.16
Nogai_Karachay_Cherkessia,4.82,15.81,7.60,37.36,5. 83,1.28,1.55,8.50,14.96,0.96,0.67,0.50,0.16
Nogai_Stavropol,9.78,13.59,3.45,17.17,4.16,0.77,3. 38,17.32,27.75,1.40,0.81,0.13,0.29
Tatar_Mishar,22.02,36.72,6.67,10.78,3.49,0.61,2.65 ,3.98,11.20,1.27,0.14,0.14,0.34
Tatar_Siberian,11.35,22.67,0.79,12.78,1.01,0.73,3. 84,10.60,31.58,3.63,0.42,0.21,0.37
Tatar_Siberian_Zabolotniye,7.98,28.63,0.00,9.09,0. 00,0.00,4.28,6.16,39.24,3.75,0.44,0.00,0.43
Thai,0.56,1.94,1.13,0.79,0.60,0.72,15.28,72.41,3.1 5,0.83,2.22,0.20,0.18
Tharu,0.71,1.42,1.98,7.59,0.09,0.05,37.14,32.52,15 .57,0.89,1.76,0.09,0.20
Tlingit,10.16,25.66,0.84,4.18,0.12,0.06,1.74,4.72, 24.47,26.92,0.12,0.42,0.60
Todzin,0.00,8.50,0.23,1.52,0.01,0.23,3.28,13.04,69 .16,3.39,0.53,0.00,0.12
Tofalar,1.43,9.78,0.55,1.74,0.00,0.33,1.32,12.23,6 8.16,3.28,0.98,0.11,0.08
Ulchi,0.00,0.06,0.07,0.00,0.00,0.03,0.13,31.83,64. 44,2.97,0.32,0.09,0.07
Veps,27.06,52.06,3.86,1.66,0.87,1.20,1.72,0.17,8.9 4,1.38,0.61,0.13,0.34
Yukagir_Forest,13.18,28.16,3.70,1.11,3.10,0.61,1.4 6,4.38,40.97,2.04,0.34,0.39,0.56
Yukagir_Tundra,0.00,2.99,0.00,0.12,0.02,0.10,1.06, 8.36,78.20,8.07,0.64,0.08,0.38
Khanty,5.65,31.35,0.00,3.55,0.00,0.00,4.34,0.83,47 .59,6.01,0.56,0.00,0.10
Saami_Kola,24.77,47.67,2.75,1.05,0.12,0.05,1.53,0. 30,17.59,2.79,0.34,0.68,0.37
Saami_Sweden,24.98,43.85,0.00,0.74,0.00,0.00,1.25, 1.23,23.50,3.64,0.41,0.06,0.35

K15:

Aleut,13.39,6.62,19.19,19.15,1.19,2.11,0.57,0.12,1 .22,3.14,15.76,16.78,0.43,0.11,0.22
Enets,3.09,1.88,2.28,15.79,0.16,0.00,0.00,0.10,1.2 1,1.36,69.10,3.80,0.63,0.00,0.60
Itelmen,0.00,0.06,0.10,5.39,0.00,0.00,0.00,0.00,1. 55,12.87,61.69,16.93,0.96,0.00,0.44
Kalmyk,1.98,0.85,1.29,6.45,0.49,5.79,0.85,0.35,0.9 2,31.23,47.33,1.62,0.50,0.06,0.28
Karelian,24.95,14.98,23.62,25.51,1.75,0.26,0.01,0. 08,0.68,0.14,6.14,1.07,0.45,0.28,0.10
Kusunda,0.74,0.20,0.08,0.50,1.01,1.61,0.04,0.04,32 .46,41.51,17.48,0.95,2.47,0.53,0.38
Mansi,9.97,1.13,5.60,28.96,0.00,0.70,0.00,0.00,3.7 5,2.09,42.05,4.93,0.68,0.04,0.09
Nasioi,0.04,0.03,0.67,0.00,0.22,0.00,0.02,0.12,3.8 8,21.80,0.23,0.22,72.52,0.01,0.26
Newar,1.19,1.16,0.98,3.14,0.87,5.35,0.10,0.70,38.6 6,31.38,13.96,1.02,0.86,0.12,0.49
Nganasan,0.00,0.03,0.18,3.19,0.00,0.00,0.00,0.00,0 .24,0.55,93.78,1.51,0.23,0.02,0.26
Nogai_Astrakhan,7.27,4.90,5.78,11.06,2.38,9.26,3.7 6,0.89,1.71,19.96,30.36,1.67,0.71,0.14,0.15
Nogai_Karachay_Cherkessia,3.66,5.98,9.18,8.25,2.86 ,39.24,3.13,1.09,2.01,8.01,14.40,0.94,0.56,0.63,0. 06
Nogai_Stavropol,8.61,4.51,4.79,11.18,1.71,14.54,3. 74,0.76,3.65,17.36,26.68,1.39,0.74,0.09,0.26
Tatar_Mishar,15.09,13.09,19.63,21.62,3.20,7.79,1.8 2,0.20,2.52,3.71,9.93,0.98,0.07,0.08,0.27
Tatar_Siberian,9.27,4.63,7.33,19.39,0.12,9.36,0.44 ,0.46,3.97,10.70,30.11,3.39,0.33,0.14,0.36
Tatar_Siberian_Zabolotniye,9.40,1.11,8.05,24.82,0. 00,4.26,0.00,0.00,4.32,6.28,37.55,3.46,0.37,0.00,0 .38
Thai,0.60,0.43,1.00,0.73,0.90,0.39,0.03,0.77,15.50 ,73.31,3.00,0.70,2.22,0.16,0.26
Tharu,0.15,0.80,0.77,2.89,1.29,4.95,0.18,0.00,38.3 0,32.80,15.04,0.88,1.69,0.15,0.10
Tlingit,10.24,2.20,14.10,14.21,0.00,1.74,0.00,0.00 ,2.10,4.93,23.40,26.38,0.06,0.11,0.54
Todzin,0.00,0.05,0.77,10.12,0.00,0.40,0.00,0.09,2. 90,13.46,68.08,3.61,0.46,0.00,0.06
Tofalar,0.96,0.90,1.33,11.14,0.35,0.23,0.00,0.21,1 .06,12.71,67.03,3.04,0.90,0.06,0.07
Ulchi,0.00,0.00,0.02,0.12,0.04,0.00,0.00,0.03,0.24 ,32.50,63.00,3.36,0.39,0.19,0.11
Veps,21.66,14.23,25.49,26.84,0.88,0.17,0.09,0.36,0 .80,0.12,7.55,1.11,0.40,0.19,0.12
Yukagir_Forest,10.30,7.61,14.56,14.81,2.26,0.81,0. 69,0.36,1.16,4.45,40.01,1.77,0.38,0.26,0.55
Yukagir_Tundra,0.01,0.00,0.46,3.09,0.06,0.08,0.00, 0.11,0.77,8.86,77.66,7.92,0.58,0.03,0.37
Khanty,6.97,0.34,5.33,31.74,0.00,0.15,0.00,0.00,3. 55,0.84,45.06,5.61,0.35,0.01,0.05
Saami_Kola,21.70,10.22,20.56,26.16,0.89,0.15,0.00, 0.00,0.80,0.16,16.08,2.60,0.21,0.26,0.21
Saami_Sweden,23.38,8.25,13.76,27.35,0.00,0.00,0.00 ,0.00,0.37,1.04,22.05,3.40,0.23,0.00,0.17

K12b:

Aleut,5.70,19.08,0.07,1.30,10.16,44.66,1.68,0.13,0 .16,12.75,4.31,0.00
Enets,3.16,66.82,0.00,0.00,0.95,17.61,0.15,0.00,0. 00,11.30,0.00,0.02
Itelmen,2.57,55.38,0.00,1.45,0.00,6.50,1.22,0.00,0 .00,32.82,0.00,0.05
Kalmyk,4.21,33.74,0.04,3.94,1.73,7.66,0.86,0.10,0. 36,44.01,3.35,0.01
Karelian,3.04,6.84,0.23,0.46,18.06,65.75,0.97,0.06 ,0.60,0.73,3.21,0.03
Kusunda,9.46,5.84,0.41,14.24,0.25,1.13,26.66,0.30, 0.02,41.46,0.17,0.06
Mansi,5.75,42.24,0.00,0.76,2.52,38.74,1.29,0.01,0. 00,7.74,0.96,0.00
Nasioi,3.43,4.83,0.54,34.20,1.66,2.03,36.85,3.57,0 .51,8.75,0.05,3.58
Newar,16.22,4.66,0.10,10.98,0.87,3.51,30.34,0.04,0 .25,31.69,1.33,0.00
Nganasan,0.13,90.28,0.06,0.40,0.02,1.09,0.15,0.08, 0.02,7.63,0.00,0.13
Nogai_Astrakhan,7.17,23.65,0.43,2.80,8.09,17.77,1. 16,0.02,1.95,27.43,9.50,0.04
Nogai_Karachay_Cherkessia,13.08,10.90,0.23,1.16,3. 83,20.54,0.52,0.16,0.72,12.86,35.92,0.07
Nogai_Stavropol,10.77,20.06,0.18,2.25,7.03,17.51,2 .10,0.03,1.66,24.76,13.64,0.00
Tatar_Mishar,7.19,10.06,0.01,0.89,16.60,46.04,1.67 ,0.00,1.33,5.20,10.98,0.03
Tatar_Siberian,9.42,26.59,0.25,1.56,6.42,27.29,1.9 6,0.07,0.81,17.86,7.77,0.00
Tatar_Siberian_Zabolotniye,10.85,36.40,0.00,1.13,2 .99,31.94,1.47,0.24,0.00,12.92,2.01,0.03
Thai,3.49,1.38,0.07,57.25,0.68,0.73,12.36,0.15,0.4 5,22.17,1.18,0.10
Tharu,15.85,4.64,0.19,10.28,0.34,2.39,31.17,0.00,0 .13,34.60,0.41,0.00
Tlingit,7.36,27.62,0.00,1.82,4.48,35.86,1.58,0.00, 0.00,19.27,2.00,0.00
Todzin,2.53,61.11,0.00,0.92,0.46,6.92,1.72,0.00,0. 32,26.01,0.00,0.00
Tofalar,2.61,61.25,0.04,0.48,0.97,8.12,0.91,0.14,0 .56,24.37,0.55,0.00
Ulchi,0.05,43.23,0.03,1.24,0.02,0.13,0.43,0.06,0.0 0,54.67,0.04,0.09
Veps,2.67,9.17,0.44,0.30,16.67,63.09,1.03,0.12,1.2 2,1.20,4.04,0.04
Yukagir_Forest,2.01,35.37,0.15,1.02,9.92,31.54,1.5 0,0.12,0.81,11.98,5.47,0.11
Yukagir_Tundra,0.54,68.96,0.06,0.29,0.02,3.30,0.72 ,0.01,0.00,26.06,0.00,0.04
Saami_SWE,4.28,23.14,0.03,0.32,11.85,55.53,0.35,0. 01,0.00,4.49,0.00,0.00
Khanty,8.11,47.13,0.00,0.14,0.92,33.67,1.38,0.01,0 .04,8.57,0.01,0.02
Saami_Kola,3.57,17.22,0.02,0.14,14.72,58.87,1.03,0 .00,0.25,2.60,1.56,0.00

K13 heatmap:

https://i.ibb.co/0BKfJWM/h.png

Here's how you can make a heatmap where the clustering takes FST into account, and where the branches of the clustering tree are ordered based on the value of PC1 in a PCA of the populations:

library(pheatmap)
library(colorspace) # for hex
library(vegan) # for reorder.hclust

t=read.csv(r=1,text=",North_Atlantic,Baltic,West_Med,West_Asian,East_Me d,Red_Sea,South_Asian,East_Asian,Siberian,Amerindi an,Oceanian,Northeast_African,Sub-Saharan
Aleut,15.28,35.26,3.07,4.61,1.58,0.44,1.38,3.08,17 .02,17.25,0.52,0.15,0.36
Enets,4.74,15.29,0.28,0.92,0.00,0.37,1.68,1.09,70. 16,4.10,0.68,0.00,0.70
Itelmen,0.00,4.39,0.00,0.00,0.00,0.00,1.80,12.25,6 2.76,17.18,1.07,0.00,0.54
Kalmyk,2.52,5.75,0.80,6.79,1.15,0.37,0.84,30.84,48 .41,1.56,0.56,0.06,0.37
Karelian,30.32,50.92,4.11,1.41,0.83,0.69,1.40,0.26 ,7.57,1.28,0.58,0.49,0.16
Kusunda,0.96,0.00,0.90,3.36,0.00,0.00,31.41,40.72, 18.24,0.88,2.46,0.72,0.34
Mansi,8.34,30.51,0.00,4.75,0.00,0.00,4.24,1.92,43. 90,5.26,0.81,0.14,0.13
Nasioi,0.08,0.49,0.34,0.00,0.17,0.23,4.44,21.24,0. 21,0.23,72.24,0.04,0.29
Newar,1.09,2.39,1.12,9.15,0.30,0.63,37.11,30.97,14 .64,0.99,1.01,0.09,0.51
Nganasan,0.00,2.75,0.00,0.00,0.02,0.01,0.44,0.41,9 4.26,1.61,0.21,0.03,0.27
Nogai_Astrakhan,9.15,14.62,4.35,11.10,4.02,1.05,1. 57,19.78,31.69,1.61,0.72,0.20,0.16
Nogai_Karachay_Cherkessia,4.82,15.81,7.60,37.36,5. 83,1.28,1.55,8.50,14.96,0.96,0.67,0.50,0.16
Nogai_Stavropol,9.78,13.59,3.45,17.17,4.16,0.77,3. 38,17.32,27.75,1.40,0.81,0.13,0.29
Tatar_Mishar,22.02,36.72,6.67,10.78,3.49,0.61,2.65 ,3.98,11.20,1.27,0.14,0.14,0.34
Tatar_Siberian,11.35,22.67,0.79,12.78,1.01,0.73,3. 84,10.60,31.58,3.63,0.42,0.21,0.37
Tatar_Siberian_Zabolotniye,7.98,28.63,0.00,9.09,0. 00,0.00,4.28,6.16,39.24,3.75,0.44,0.00,0.43
Thai,0.56,1.94,1.13,0.79,0.60,0.72,15.28,72.41,3.1 5,0.83,2.22,0.20,0.18
Tharu,0.71,1.42,1.98,7.59,0.09,0.05,37.14,32.52,15 .57,0.89,1.76,0.09,0.20
Tlingit,10.16,25.66,0.84,4.18,0.12,0.06,1.74,4.72, 24.47,26.92,0.12,0.42,0.60
Todzin,0.00,8.50,0.23,1.52,0.01,0.23,3.28,13.04,69 .16,3.39,0.53,0.00,0.12
Tofalar,1.43,9.78,0.55,1.74,0.00,0.33,1.32,12.23,6 8.16,3.28,0.98,0.11,0.08
Ulchi,0.00,0.06,0.07,0.00,0.00,0.03,0.13,31.83,64. 44,2.97,0.32,0.09,0.07
Veps,27.06,52.06,3.86,1.66,0.87,1.20,1.72,0.17,8.9 4,1.38,0.61,0.13,0.34
Yukagir_Forest,13.18,28.16,3.70,1.11,3.10,0.61,1.4 6,4.38,40.97,2.04,0.34,0.39,0.56
Yukagir_Tundra,0.00,2.99,0.00,0.12,0.02,0.10,1.06, 8.36,78.20,8.07,0.64,0.08,0.38")

fst=as.matrix(as.dist(read.csv(h=F,text=",,,,,,,,,,,,
19,,,,,,,,,,,,
28,36,,,,,,,,,,,
26,32,36,,,,,,,,,,
26,35,28,21,,,,,,,,,
52,62,50,48,39,,,,,,,,
64,65,76,57,60,82,,,,,,,
114,114,122,110,111,127,76,,,,,,
111,111,123,109,112,130,83,56,,,,,
138,137,154,138,144,161,120,113,105,,,,
179,181,187,177,176,191,146,166,177,217,,,
122,127,124,116,108,121,113,145,151,185,203,,
146,150,150,140,135,141,133,164,170,204,220,41,")))

t2=as.matrix(t)%*%cmdscale(fst,ncol(fst)-1)
p=prcomp(t2)$x
hc=hclust(dist(t2))
hc=reorder(hc,p[,1])

pheatmap::pheatmap(
t[,ncol(t):1],
filename="1.png",
clustering_callback=function(...)hc,
cluster_cols=F,
legend=F,
cellwidth=18,
cellheight=18,
fontsize=10,
treeheight_row=100,
treeheight_col=100,
border_color=NA,
display_numbers=T,
number_format="%.0f",
fontsize_number=8,
number_color="black",
colorRampPalette(hex(HSV(c(210,210,170,135,100,60, 30,0),c(0,rep(.4,7)),1)))(256)
)

vbnetkhio

10-25-2021, 02:07 PM

Ok, adding the calculators was straightforward. I copied the `.F` and `.alleles` files to `/usr/local/lib/python3.9/site-packages/admix/data`. Then I modified `admix_models.py` to add entries named K13 and K15 to the array returned by the `models` function, and I added these lines to the `populations` function:

elif model == 'K13':
return [('North_Atlantic','North_Atlantic'),
('Baltic','Baltic'),
('West_Med','West_Med'),
('West_Asian','West_Asian'),
('East_Med','East_Med'),
('Red_Sea','Red_Sea'),
('South_Asian','South_Asian'),
('East_Asian','East_Asian'),
('Siberian','Siberian'),
('Amerindian','Amerindian'),
('Oceanian','Oceanian'),
('Northeast_African','Northeast_African'),
('Sub-Saharan','Sub-Saharan')]
elif model == 'K15':
return [('North_Sea','North_Sea'),
('Atlantic','Atlantic'),
('Baltic','Baltic'),
('Eastern_Euro','Eastern_Euro'),
('West_Med','West_Med'),
('West_Asian','West_Asian'),
('East_Med','East_Med'),
('Red_Sea','Red_Sea'),
('South_Asian','South_Asian'),
('Southeast_Asian','Southeast_Asian'),
('Siberian','Siberian'),
('Amerindian','Amerindian'),
('Oceanian','Oceanian'),
('Northeast_African','Northeast_African'),
('Sub-Saharan','Sub-Saharan')]

I made these averages for K13 from the Reich dataset and from Tambets et al. 2018 (https://evolbio.ut.ee/Tambets2018/) (Khanty, Saami_Kola, and Saami_Sweden):

Aleut,15.28,35.26,3.07,4.61,1.58,0.44,1.38,3.08,17 .02,17.25,0.52,0.15,0.36
Enets,4.74,15.29,0.28,0.92,0.00,0.37,1.68,1.09,70. 16,4.10,0.68,0.00,0.70
Itelmen,0.00,4.39,0.00,0.00,0.00,0.00,1.80,12.25,6 2.76,17.18,1.07,0.00,0.54
Kalmyk,2.52,5.75,0.80,6.79,1.15,0.37,0.84,30.84,48 .41,1.56,0.56,0.06,0.37
Karelian,30.32,50.92,4.11,1.41,0.83,0.69,1.40,0.26 ,7.57,1.28,0.58,0.49,0.16
Kusunda,0.96,0.00,0.90,3.36,0.00,0.00,31.41,40.72, 18.24,0.88,2.46,0.72,0.34
Mansi,8.34,30.51,0.00,4.75,0.00,0.00,4.24,1.92,43. 90,5.26,0.81,0.14,0.13
Nasioi,0.08,0.49,0.34,0.00,0.17,0.23,4.44,21.24,0. 21,0.23,72.24,0.04,0.29
Newar,1.09,2.39,1.12,9.15,0.30,0.63,37.11,30.97,14 .64,0.99,1.01,0.09,0.51
Nganasan,0.00,2.75,0.00,0.00,0.02,0.01,0.44,0.41,9 4.26,1.61,0.21,0.03,0.27
Nogai_Astrakhan,9.15,14.62,4.35,11.10,4.02,1.05,1. 57,19.78,31.69,1.61,0.72,0.20,0.16
Nogai_Karachay_Cherkessia,4.82,15.81,7.60,37.36,5. 83,1.28,1.55,8.50,14.96,0.96,0.67,0.50,0.16
Nogai_Stavropol,9.78,13.59,3.45,17.17,4.16,0.77,3. 38,17.32,27.75,1.40,0.81,0.13,0.29
Tatar_Mishar,22.02,36.72,6.67,10.78,3.49,0.61,2.65 ,3.98,11.20,1.27,0.14,0.14,0.34
Tatar_Siberian,11.35,22.67,0.79,12.78,1.01,0.73,3. 84,10.60,31.58,3.63,0.42,0.21,0.37
Tatar_Siberian_Zabolotniye,7.98,28.63,0.00,9.09,0. 00,0.00,4.28,6.16,39.24,3.75,0.44,0.00,0.43
Thai,0.56,1.94,1.13,0.79,0.60,0.72,15.28,72.41,3.1 5,0.83,2.22,0.20,0.18
Tharu,0.71,1.42,1.98,7.59,0.09,0.05,37.14,32.52,15 .57,0.89,1.76,0.09,0.20
Tlingit,10.16,25.66,0.84,4.18,0.12,0.06,1.74,4.72, 24.47,26.92,0.12,0.42,0.60
Todzin,0.00,8.50,0.23,1.52,0.01,0.23,3.28,13.04,69 .16,3.39,0.53,0.00,0.12
Tofalar,1.43,9.78,0.55,1.74,0.00,0.33,1.32,12.23,6 8.16,3.28,0.98,0.11,0.08
Ulchi,0.00,0.06,0.07,0.00,0.00,0.03,0.13,31.83,64. 44,2.97,0.32,0.09,0.07
Veps,27.06,52.06,3.86,1.66,0.87,1.20,1.72,0.17,8.9 4,1.38,0.61,0.13,0.34
Yukagir_Forest,13.18,28.16,3.70,1.11,3.10,0.61,1.4 6,4.38,40.97,2.04,0.34,0.39,0.56
Yukagir_Tundra,0.00,2.99,0.00,0.12,0.02,0.10,1.06, 8.36,78.20,8.07,0.64,0.08,0.38
Khanty,5.65,31.35,0.00,3.55,0.00,0.00,4.34,0.83,47 .59,6.01,0.56,0.00,0.10
Saami_Kola,24.77,47.67,2.75,1.05,0.12,0.05,1.53,0. 30,17.59,2.79,0.34,0.68,0.37
Saami_Sweden,24.98,43.85,0.00,0.74,0.00,0.00,1.25, 1.23,23.50,3.64,0.41,0.06,0.35

K15:

Aleut,13.39,6.62,19.19,19.15,1.19,2.11,0.57,0.12,1 .22,3.14,15.76,16.78,0.43,0.11,0.22
Enets,3.09,1.88,2.28,15.79,0.16,0.00,0.00,0.10,1.2 1,1.36,69.10,3.80,0.63,0.00,0.60
Itelmen,0.00,0.06,0.10,5.39,0.00,0.00,0.00,0.00,1. 55,12.87,61.69,16.93,0.96,0.00,0.44
Kalmyk,1.98,0.85,1.29,6.45,0.49,5.79,0.85,0.35,0.9 2,31.23,47.33,1.62,0.50,0.06,0.28
Karelian,24.95,14.98,23.62,25.51,1.75,0.26,0.01,0. 08,0.68,0.14,6.14,1.07,0.45,0.28,0.10
Kusunda,0.74,0.20,0.08,0.50,1.01,1.61,0.04,0.04,32 .46,41.51,17.48,0.95,2.47,0.53,0.38
Mansi,9.97,1.13,5.60,28.96,0.00,0.70,0.00,0.00,3.7 5,2.09,42.05,4.93,0.68,0.04,0.09
Nasioi,0.04,0.03,0.67,0.00,0.22,0.00,0.02,0.12,3.8 8,21.80,0.23,0.22,72.52,0.01,0.26
Newar,1.19,1.16,0.98,3.14,0.87,5.35,0.10,0.70,38.6 6,31.38,13.96,1.02,0.86,0.12,0.49
Nganasan,0.00,0.03,0.18,3.19,0.00,0.00,0.00,0.00,0 .24,0.55,93.78,1.51,0.23,0.02,0.26
Nogai_Astrakhan,7.27,4.90,5.78,11.06,2.38,9.26,3.7 6,0.89,1.71,19.96,30.36,1.67,0.71,0.14,0.15
Nogai_Karachay_Cherkessia,3.66,5.98,9.18,8.25,2.86 ,39.24,3.13,1.09,2.01,8.01,14.40,0.94,0.56,0.63,0. 06
Nogai_Stavropol,8.61,4.51,4.79,11.18,1.71,14.54,3. 74,0.76,3.65,17.36,26.68,1.39,0.74,0.09,0.26
Tatar_Mishar,15.09,13.09,19.63,21.62,3.20,7.79,1.8 2,0.20,2.52,3.71,9.93,0.98,0.07,0.08,0.27
Tatar_Siberian,9.27,4.63,7.33,19.39,0.12,9.36,0.44 ,0.46,3.97,10.70,30.11,3.39,0.33,0.14,0.36
Tatar_Siberian_Zabolotniye,9.40,1.11,8.05,24.82,0. 00,4.26,0.00,0.00,4.32,6.28,37.55,3.46,0.37,0.00,0 .38
Thai,0.60,0.43,1.00,0.73,0.90,0.39,0.03,0.77,15.50 ,73.31,3.00,0.70,2.22,0.16,0.26
Tharu,0.15,0.80,0.77,2.89,1.29,4.95,0.18,0.00,38.3 0,32.80,15.04,0.88,1.69,0.15,0.10
Tlingit,10.24,2.20,14.10,14.21,0.00,1.74,0.00,0.00 ,2.10,4.93,23.40,26.38,0.06,0.11,0.54
Todzin,0.00,0.05,0.77,10.12,0.00,0.40,0.00,0.09,2. 90,13.46,68.08,3.61,0.46,0.00,0.06
Tofalar,0.96,0.90,1.33,11.14,0.35,0.23,0.00,0.21,1 .06,12.71,67.03,3.04,0.90,0.06,0.07
Ulchi,0.00,0.00,0.02,0.12,0.04,0.00,0.00,0.03,0.24 ,32.50,63.00,3.36,0.39,0.19,0.11
Veps,21.66,14.23,25.49,26.84,0.88,0.17,0.09,0.36,0 .80,0.12,7.55,1.11,0.40,0.19,0.12
Yukagir_Forest,10.30,7.61,14.56,14.81,2.26,0.81,0. 69,0.36,1.16,4.45,40.01,1.77,0.38,0.26,0.55
Yukagir_Tundra,0.01,0.00,0.46,3.09,0.06,0.08,0.00, 0.11,0.77,8.86,77.66,7.92,0.58,0.03,0.37
Khanty,6.97,0.34,5.33,31.74,0.00,0.15,0.00,0.00,3. 55,0.84,45.06,5.61,0.35,0.01,0.05
Saami_Kola,21.70,10.22,20.56,26.16,0.89,0.15,0.00, 0.00,0.80,0.16,16.08,2.60,0.21,0.26,0.21
Saami_Sweden,23.38,8.25,13.76,27.35,0.00,0.00,0.00 ,0.00,0.37,1.04,22.05,3.40,0.23,0.00,0.17

K12b:

Aleut,5.70,19.08,0.07,1.30,10.16,44.66,1.68,0.13,0 .16,12.75,4.31,0.00
Enets,3.16,66.82,0.00,0.00,0.95,17.61,0.15,0.00,0. 00,11.30,0.00,0.02
Itelmen,2.57,55.38,0.00,1.45,0.00,6.50,1.22,0.00,0 .00,32.82,0.00,0.05
Kalmyk,4.21,33.74,0.04,3.94,1.73,7.66,0.86,0.10,0. 36,44.01,3.35,0.01
Karelian,3.04,6.84,0.23,0.46,18.06,65.75,0.97,0.06 ,0.60,0.73,3.21,0.03
Kusunda,9.46,5.84,0.41,14.24,0.25,1.13,26.66,0.30, 0.02,41.46,0.17,0.06
Mansi,5.75,42.24,0.00,0.76,2.52,38.74,1.29,0.01,0. 00,7.74,0.96,0.00
Nasioi,3.43,4.83,0.54,34.20,1.66,2.03,36.85,3.57,0 .51,8.75,0.05,3.58
Newar,16.22,4.66,0.10,10.98,0.87,3.51,30.34,0.04,0 .25,31.69,1.33,0.00
Nganasan,0.13,90.28,0.06,0.40,0.02,1.09,0.15,0.08, 0.02,7.63,0.00,0.13
Nogai_Astrakhan,7.17,23.65,0.43,2.80,8.09,17.77,1. 16,0.02,1.95,27.43,9.50,0.04
Nogai_Karachay_Cherkessia,13.08,10.90,0.23,1.16,3. 83,20.54,0.52,0.16,0.72,12.86,35.92,0.07
Nogai_Stavropol,10.77,20.06,0.18,2.25,7.03,17.51,2 .10,0.03,1.66,24.76,13.64,0.00
Tatar_Mishar,7.19,10.06,0.01,0.89,16.60,46.04,1.67 ,0.00,1.33,5.20,10.98,0.03
Tatar_Siberian,9.42,26.59,0.25,1.56,6.42,27.29,1.9 6,0.07,0.81,17.86,7.77,0.00
Tatar_Siberian_Zabolotniye,10.85,36.40,0.00,1.13,2 .99,31.94,1.47,0.24,0.00,12.92,2.01,0.03
Thai,3.49,1.38,0.07,57.25,0.68,0.73,12.36,0.15,0.4 5,22.17,1.18,0.10
Tharu,15.85,4.64,0.19,10.28,0.34,2.39,31.17,0.00,0 .13,34.60,0.41,0.00
Tlingit,7.36,27.62,0.00,1.82,4.48,35.86,1.58,0.00, 0.00,19.27,2.00,0.00
Todzin,2.53,61.11,0.00,0.92,0.46,6.92,1.72,0.00,0. 32,26.01,0.00,0.00
Tofalar,2.61,61.25,0.04,0.48,0.97,8.12,0.91,0.14,0 .56,24.37,0.55,0.00
Ulchi,0.05,43.23,0.03,1.24,0.02,0.13,0.43,0.06,0.0 0,54.67,0.04,0.09
Veps,2.67,9.17,0.44,0.30,16.67,63.09,1.03,0.12,1.2 2,1.20,4.04,0.04
Yukagir_Forest,2.01,35.37,0.15,1.02,9.92,31.54,1.5 0,0.12,0.81,11.98,5.47,0.11
Yukagir_Tundra,0.54,68.96,0.06,0.29,0.02,3.30,0.72 ,0.01,0.00,26.06,0.00,0.04
Khanty,6.97,0.34,5.33,31.74,0.00,0.15,0.00,0.00,3. 55,0.84,45.06,5.61,0.35,0.01,0.05
Saami_Kola,21.70,10.22,20.56,26.16,0.89,0.15,0.00, 0.00,0.80,0.16,16.08,2.60,0.21,0.26,0.21
Saami_Sweden,23.38,8.25,13.76,27.35,0.00,0.00,0.00 ,0.00,0.37,1.04,22.05,3.40,0.23,0.00,0.17

K13 heatmap:

https://i.ibb.co/0BKfJWM/h.png

Here's how you can make a heatmap where the clustering takes FST into account, and where the branches of the clustering tree are ordered based on the value of PC1 in a PCA of the populations:

library(pheatmap)
library(colorspace) # for hex
library(vegan) # for reorder.hclust

t=read.csv(r,1=text=",North_Atlantic,Baltic,West_Med,West_Asian,East_Me d,Red_Sea,South_Asian,East_Asian,Siberian,Amerindi an,Oceanian,Northeast_African,Sub-Saharan
Aleut,15.28,35.26,3.07,4.61,1.58,0.44,1.38,3.08,17 .02,17.25,0.52,0.15,0.36
Enets,4.74,15.29,0.28,0.92,0.00,0.37,1.68,1.09,70. 16,4.10,0.68,0.00,0.70
Itelmen,0.00,4.39,0.00,0.00,0.00,0.00,1.80,12.25,6 2.76,17.18,1.07,0.00,0.54
Kalmyk,2.52,5.75,0.80,6.79,1.15,0.37,0.84,30.84,48 .41,1.56,0.56,0.06,0.37
Karelian,30.32,50.92,4.11,1.41,0.83,0.69,1.40,0.26 ,7.57,1.28,0.58,0.49,0.16
Kusunda,0.96,0.00,0.90,3.36,0.00,0.00,31.41,40.72, 18.24,0.88,2.46,0.72,0.34
Mansi,8.34,30.51,0.00,4.75,0.00,0.00,4.24,1.92,43. 90,5.26,0.81,0.14,0.13
Nasioi,0.08,0.49,0.34,0.00,0.17,0.23,4.44,21.24,0. 21,0.23,72.24,0.04,0.29
Newar,1.09,2.39,1.12,9.15,0.30,0.63,37.11,30.97,14 .64,0.99,1.01,0.09,0.51
Nganasan,0.00,2.75,0.00,0.00,0.02,0.01,0.44,0.41,9 4.26,1.61,0.21,0.03,0.27
Nogai_Astrakhan,9.15,14.62,4.35,11.10,4.02,1.05,1. 57,19.78,31.69,1.61,0.72,0.20,0.16
Nogai_Karachay_Cherkessia,4.82,15.81,7.60,37.36,5. 83,1.28,1.55,8.50,14.96,0.96,0.67,0.50,0.16
Nogai_Stavropol,9.78,13.59,3.45,17.17,4.16,0.77,3. 38,17.32,27.75,1.40,0.81,0.13,0.29
Tatar_Mishar,22.02,36.72,6.67,10.78,3.49,0.61,2.65 ,3.98,11.20,1.27,0.14,0.14,0.34
Tatar_Siberian,11.35,22.67,0.79,12.78,1.01,0.73,3. 84,10.60,31.58,3.63,0.42,0.21,0.37
Tatar_Siberian_Zabolotniye,7.98,28.63,0.00,9.09,0. 00,0.00,4.28,6.16,39.24,3.75,0.44,0.00,0.43
Thai,0.56,1.94,1.13,0.79,0.60,0.72,15.28,72.41,3.1 5,0.83,2.22,0.20,0.18
Tharu,0.71,1.42,1.98,7.59,0.09,0.05,37.14,32.52,15 .57,0.89,1.76,0.09,0.20
Tlingit,10.16,25.66,0.84,4.18,0.12,0.06,1.74,4.72, 24.47,26.92,0.12,0.42,0.60
Todzin,0.00,8.50,0.23,1.52,0.01,0.23,3.28,13.04,69 .16,3.39,0.53,0.00,0.12
Tofalar,1.43,9.78,0.55,1.74,0.00,0.33,1.32,12.23,6 8.16,3.28,0.98,0.11,0.08
Ulchi,0.00,0.06,0.07,0.00,0.00,0.03,0.13,31.83,64. 44,2.97,0.32,0.09,0.07
Veps,27.06,52.06,3.86,1.66,0.87,1.20,1.72,0.17,8.9 4,1.38,0.61,0.13,0.34
Yukagir_Forest,13.18,28.16,3.70,1.11,3.10,0.61,1.4 6,4.38,40.97,2.04,0.34,0.39,0.56
Yukagir_Tundra,0.00,2.99,0.00,0.12,0.02,0.10,1.06, 8.36,78.20,8.07,0.64,0.08,0.38")

fst=as.matrix(as.dist(read.csv(h=F,text=",,,,,,,,,,,,
19,,,,,,,,,,,,
28,36,,,,,,,,,,,
26,32,36,,,,,,,,,,
26,35,28,21,,,,,,,,,
52,62,50,48,39,,,,,,,,
64,65,76,57,60,82,,,,,,,
114,114,122,110,111,127,76,,,,,,
111,111,123,109,112,130,83,56,,,,,
138,137,154,138,144,161,120,113,105,,,,
179,181,187,177,176,191,146,166,177,217,,,
122,127,124,116,108,121,113,145,151,185,203,,
146,150,150,140,135,141,133,164,170,204,220,41,")))

t2=as.matrix(t)%*%cmdscale(fst,ncol(fst)-1)
p=prcomp(t2)$x
hc=hclust(dist(t2))
hc=reorder(hc,p[,1])

pheatmap::pheatmap(
t[,ncol(t):1],
filename="1.png",
clustering_callback=function(...)hc,
cluster_cols=F,
legend=F,
cellwidth=18,
cellheight=18,
fontsize=10,
treeheight_row=100,
treeheight_col=100,
border_color=NA,
display_numbers=T,
number_format="%.0f",
fontsize_number=8,
number_color="black",
colorRampPalette(hex(HSV(c(210,210,170,135,100,60, 30,0),c(0,rep(.4,7)),1)))(256)
)

is this script much faster than the regular DiyDodecad, or you have very high CPU/RAM?

could you run these Lithuanians trough k13? https://figshare.com/articles/dataset/Patterns_of_genetic_structure_and_adaptive_positiv e_selection_in_the_Lithuanian_population_from_high-density_SNP_data/7964159

Leto

10-25-2021, 02:13 PM

I wanna borrow some of those averages for Dodecad :D
But the Khanty one is broken, please fix it.

vbnetkhio

10-25-2021, 02:15 PM

I wanna borrow some of those averages for Dodecad :D
But the Khanty one is broken, please fix it.

probably calc effect.
edit: it's not calc effect, those are just k13 values instead of k12b

Leto

10-25-2021, 02:26 PM

I see Lukasz already added most of them. But we need to delete the old Yugakir and replace it with the new ones. Also Khanty, Sámi and Thai should be added.

Leto

10-25-2021, 04:11 PM

Lucas

10-25-2021, 04:19 PM

Lukasz was very quick to add those pops compared to adding what I send but I have a few questions:

Why does the Even have so much European ancestry? Why is the Yukagir Forest almost half European? The same goes for the Aleut average. Something must be wrong with them.

It is not fault of those scripts. In K36 those samples are identical in terms of Euro ancestry. They are mestizos simply. But some full Siberians are among them still.

Leto

10-25-2021, 04:32 PM

It is not fault of those scripts. In K36 those samples are identical in terms of Euro ancestry. They are mestizos simply. But some full Siberians are among them still.
Well, I admit I don't know too much about those tiny ethnic groups. Let's not add Yukagir Forest though.

Add these please

Saami_Sweden,4.28,23.14,0.03,0.32,11.85,55.53,0.35 ,0.01,0.00,4.49,0.00,0.00
Khanty,8.11,47.13,0.00,0.14,0.92,33.67,1.38,0.01,0 .04,8.57,0.01,0.02
Thai,3.49,1.38,0.07,57.25,0.68,0.73,12.36,0.15,0.4 5,22.17,1.18,0.10
Yukagir_Tundra,0.54,68.96,0.06,0.29,0.02,3.30,0.72 ,0.01,0.00,26.06,0.00,0.04

Saami_Kola is like 1500 people, we can dispense with them too.

Komintasavalta

10-25-2021, 04:49 PM

is this script much faster than the regular DiyDodecad, or you have very high CPU/RAM?

could you run these Lithuanians trough k13? https://figshare.com/articles/dataset/Patterns_of_genetic_structure_and_adaptive_positiv e_selection_in_the_Lithuanian_population_from_high-density_SNP_data/7964159

It takes about 3 seconds per sample when I use GNU Parallel to run 10 parallel jobs, and 6 seconds otherwise.

Results of all 412 samples: https://pastebin.com/raw/xDUUK2pA.

In the PCA below, the outliers in the top left corner of the plot got something like 99.5% or 99.7% of Baltic. I don't know if it's because they were used as reference samples in K13. LTG-356 is an outlier because it only got 21.48% North_Atlantic, 74.47% Baltic, and 4.05% West_Med, and 0% all other components. LTG-441 is closest to Russian_Kargopol and LTG-566 is closest to Russian_average.

https://i.ibb.co/QXL8jBJ/1.png

But the Khanty one is broken, please fix it.

Sorry, I fixed it now.

vbnetkhio

10-25-2021, 04:55 PM

Komintasavalta

10-25-2021, 05:39 PM

Why does the Even have so much European ancestry?

There's some mixed Even samples that I probably should've removed. But all Aleut and Forest Yukaghir samples have at least 20% Baltic:

North_AtlanticBalticWest_MedWest_AsianEast_MedRed_ SeaSouth_AsianEast_AsianSiberianAmerindianOceanian Northeast_AfricanSub-Saharan
Even:Nlk30.000.000.610.000.000.001.6411.7283.002.2 20.820.000.00
Even:Nlk54.6120.831.610.591.613.260.0011.2553.062. 200.170.800.00
Even:Nlk62.4311.940.000.000.530.002.429.4671.251.7 80.000.200.00
Even:Nlk108.1222.876.114.915.181.620.665.9243.480. 430.000.000.70
Even:Nlk1414.5921.616.280.002.320.001.045.1345.461 .871.610.000.11
Even:Nlk163.6927.203.002.704.691.900.267.1147.451. 350.660.000.00
Even:Nlk180.001.530.260.000.000.001.539.3884.791.3 70.860.290.00
Even:Nlk1917.2635.055.014.751.301.032.435.2125.750 .351.760.060.06
Yukagir_Forest:Nel1314.9724.734.832.672.310.000.00 7.3740.011.920.000.001.19
Yukagir_Forest:Nel1511.8325.152.212.863.880.001.34 4.8042.282.701.270.940.75
Yukagir_Forest:Nel1611.9431.405.730.002.531.802.03 2.5440.821.210.000.000.00
Yukagir_Forest:Nel1712.5226.982.920.001.911.261.20 3.0345.133.360.431.010.24
Yukagir_Forest:Nel1914.6232.522.830.004.860.002.73 4.1736.621.020.000.000.63
Aleut:Ale208.8122.080.335.900.050.051.586.9222.903 0.770.120.160.35
Aleut:Ale2211.0521.550.184.700.000.001.366.0027.08 27.920.000.000.15
Aleut:Ale3321.1643.783.592.950.001.200.000.6713.32 11.490.680.001.16
Aleut:Ale3414.6631.390.003.290.000.330.994.5822.92 21.060.310.000.47
Aleut:Ale3513.8839.526.915.680.000.002.151.8715.55 12.970.910.450.09
Aleut:Ale3621.4646.288.394.787.910.001.340.175.583 .350.730.000.00
Aleut:Ale3715.9142.252.124.983.091.522.211.3411.76 13.180.900.450.28

There were already a bunch of mixed Aleuts in 1909:

http://collection.kunstkamera.ru/en/entity/OBJECT/31429
http://collection.kunstkamera.ru/en/entity/OBJECT/325966
http://collection.kunstkamera.ru/en/entity/OBJECT/325963
http://collection.kunstkamera.ru/en/entity/OBJECT/326282

Let's not add Yukagir Forest though. ...

Saami_Kola is like 1500 people, we can dispense with them too.

Yukaghiric people are interesting because they were the indigenous population of Yakutia before the Turkic expansion. Also Yukaghiric languages are possibly the closest relatives of Uralic languages, and in the Uralo-Siberian theory of Fortescue, Yukaghiric languages play an important role in connecting Uralic languages to Siberian and Eskimo langugages. One of the most cited papers by the admin of the Finnish anthroforum is titled "Early contacts between Uralic and Yukaghir". The Ymyyakhtakh culture which spread as far as Finland was possibly Yukaghiric, or if Bolshoy Oleniy Ostrov wasn't Uralic, then it might have also been Yukaghiric.

Saami is actually a meta-ethnos which is about as old as the Germanic or Finnic meta-ethnos, and that speaks about 10 languages with limited mutual intelligibility. There are even 5 different Saami languages that are native to the area of Murmansk Oblast. Saami are also genetically very diverse, but I currently only have samples of Kola Saami, Swedish Saami (which are probably Northern Saami), and Finnish Saami from an area that speaks Northern Saami. G25 and the Reich dataset and other sources are missing samples for Inari Saami, Skolt Saami, Southern Saami, Ume Saami, Pite Saami, and Lule Saami (unless the Finnish Saami samples are actually Inari Saami and not Northern Saami). In G25 and K13 updated, there's now samples for most European peoples that speak their own language, but they're still missing samples for most Saami languages. Also Saami are a unique people because they are one of the few arctic reindeer herding people of Europe, and they were possibly the last true hunter-gatherers of Europe (even though it might also have been Sikhirtya who were marine mammal hunters that lived in Nenetsia before the Nenets expansion, or it might have been Mansi who used to live in Komi Republic).

Below is a PCA of population averages from K13 updated along with my new samples. I included the 200 samples that were the closest to a Swedish Saami sample when accounting for FST. Without Saami_Kola, there would actually be a huge gap between Vepsians and Saami_SWE (especially because this is also missing Komis and Russian_Arkhangelsk_Leshukonsky):

https://i.ibb.co/896dMTJ/1.png

This map by Nykyus shows Yukaghir tribes in green:

https://c.radikal.ru/c35/1903/2e/a23bc7cd6b22.jpg
https://forum.paradoxplaza.com/forum/threads/more-possible-siberian-tags.1156514/page-3#post-25248469

Leto

10-25-2021, 05:53 PM

Well, thanks for the valuable information, I was aware of several Saami subgroups but in Murmansk oblast they are all almost extinct by now, perhaps they were never numerous to begin with. In Finland, Sweden and Norway they are a bit better off.

The Yukagir avg that is currently in the spreadsheet should be deleted, it's from the original calculator-affected sheet.

Komintasavalta

10-25-2021, 07:27 PM

Here's averages from Cardona et al. 2014 ("Genome-Wide Analysis of Cold Adaptation in Indigenous Siberian Populations") (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE73996):

#K13
Altai_Teleut,6.66,15.17,0.01,8.69,0.00,0.22,2.51,1 9.64,42.30,3.62,0.63,0.35,0.21
Komi_Siberian,15.73,44.89,2.09,4.75,0.37,0.21,1.90 ,0.73,26.20,2.52,0.30,0.11,0.19
Nenets_Forest,1.42,19.73,0.00,1.58,0.00,0.04,3.21, 0.97,67.21,5.01,0.54,0.02,0.28
Nenets_Tundra,1.70,18.42,0.21,1.76,0.00,0.04,3.69, 1.67,67.12,4.84,0.32,0.11,0.13

#K15
Altai_Teleut,6.41,1.97,3.05,15.08,0.00,5.36,0.00,0 .10,2.71,19.81,41.05,3.52,0.54,0.20,0.21
Komi_Siberian,13.71,8.14,16.28,28.19,0.75,1.23,0.0 8,0.02,1.80,0.94,25.73,2.69,0.28,0.06,0.11
Nenets_Forest,2.28,0.19,1.11,21.88,0.00,0.03,0.00, 0.00,2.46,0.99,65.88,4.52,0.46,0.03,0.15
Nenets_Tundra,3.15,1.60,2.00,20.69,0.12,0.27,0.00, 0.03,2.90,1.63,62.83,4.38,0.28,0.05,0.06

#K12b
Altai_Teleut,8.46,33.04,0.12,2.22,3.20,17.97,1.45, 0.02,0.09,30.88,2.32,0.24
Komi_Siberian,6.10,27.21,0.12,0.05,10.35,46.18,1.1 6,0.13,0.32,4.61,3.73,0.03
Nenets_Forest,4.22,65.36,0.00,0.03,0.05,19.28,0.83 ,0.01,0.00,10.18,0.02,0.03
Nenets_Tundra,3.73,61.84,0.03,0.17,1.16,20.90,0.83 ,0.03,0.07,10.57,0.60,0.07

The only samples which I omitted from the averages were the one Tundra Nenets sample and one Forest Nenets sample which plot the furthest right here:

https://i.ibb.co/f42VqCV/cold.png

I have made a library for shells where I have functions with 1-4 letter names for performing most common tasks. So I actually ran the calculators using a oneliner like this:

x=cold;p Teleut Forest_Nentsi Komi Tundra_Nentsi|rp g/f/karafetpop>$x.pick;keep2 g/p/karafet $x;rmm $x.23;zs 2 $x.fam|, "plink --bfile $x --keep <(awk '\$2==x' x={} $x.fam) --recode 23 --out $x.23/{}";for c in K13 K15 K12b;do rmm $x.$c;p $x.23/*.txt|, "admix -f {} -m $c|grep %>$x.$c/{/.}";for f in $x.$c/*;do rr \ <$f|rc %|jk|aak `be<<<$f`;done|a1k '{print a[$1]":"$0}' <(-sk<g/f/karafetpop) -|nats>g/calc/$x.$c;1nk g/calc/$x.{i,c}|r ':[^,]*'|tav ,|nats>g/calc/$c.$x.a;done

vbnetkhio

10-25-2021, 07:37 PM

It takes about 3 seconds per sample when I use GNU Parallel to run 10 parallel jobs, and 6 seconds otherwise.

Results of all 412 samples: https://pastebin.com/raw/xDUUK2pA.

In the PCA below, the outliers in the top left corner of the plot got something like 99.5% or 99.7% of Baltic. I don't know if it's because they were used as reference samples in K13. LTG-356 is an outlier because it only got 21.48% North_Atlantic, 74.47% Baltic, and 4.05% West_Med, and 0% all other components. LTG-441 is closest to Russian_Kargopol and LTG-566 is closest to Russian_average.

https://i.ibb.co/QXL8jBJ/1.png

Sorry, I fixed it now.

I ran these which were missing in your sheet:

SZ/RA:LTG-1158,32.71,49.24,6.55,3.32,4.84,0.02,2.25,0.31,0,0 .76,0,0,0
RA:LTG-429,30.14,52.01,7.78,2.25,2.82,0,0.57,0.12,2.05,1. 31,0.25,0.16,0.54
PZ:LTG-648,28.11,53.41,9.26,2.05,4.3,0.01,1.47,0.06,0,0.5 3,0.18,0.38,0.23
RA:LTG-423,28.42,54.26,7.64,2.04,3.78,0,0.26,0.56,1.02,1. 23,0.19,0.42,0.17
PZ:LTG-435,25.91,56.05,10.82,3.96,0.9,0,0.42,0,0.15,0.94, 0.84,0,0
RA:LTG-632,27.22,56.52,6.63,3.29,1.12,0,1.91,0,1.98,0.56, 0.4,0.02,0.35
PZ:LTG-436,26.28,57.36,6.76,6.18,0,0.03,0.14,0,1.36,0.48, 0.55,0.86,0
PZ:LTG-645,29.68,57.36,7.14,1.53,0.24,0,1.42,0,0.49,0.3,0 .53,0.01,1.3
PZ:LTG-655,25.91,59.48,5.69,4.59,0.04,0.55,0.72,0,1.11,1. 72,0.04,0,0.16
PZ:LTG-524,26.09,59.52,6.68,3.79,0.01,0,1.3,0,1.41,0.18,0 ,0.97,0.03
PZ:LTG-631,25.07,61.58,6.77,1.93,1.8,0.01,0.28,0,0,1,0.68 ,0,0.88

you can check if i did the averages correctly in the other thread, just in case

Leto

10-25-2021, 07:53 PM

The Nenets averages should be added to D K12b.

vbnetkhio

10-25-2021, 08:22 PM

Komintasavalta

10-25-2021, 08:59 PM

Here's regional Russian and Bashkir averages of samples from the Reich dataset. Most Russian samples and all Bashkir samples are from Jeong et al. 2019, "The genetic history of admixture across inner Eurasia": https://edmond.mpdl.mpg.de/imeji/collection/Aoh9c69DscnxSNjm/item/AzbQ5R1tXvWJSk0b?q=&fq=&filter=&pos=1#pageTitle.

#K13
Bashkir_Central,15.62,31.86,3.18,12.28,3.04,0.74,3 .55,5.38,21.16,2.23,0.37,0.24,0.36
Bashkir_North,17.02,34.88,3.72,10.72,2.30,0.60,3.8 4,4.42,19.44,1.86,0.59,0.23,0.37
Bashkir_South,12.74,24.86,1.24,13.47,1.17,0.30,4.1 9,9.63,28.68,2.98,0.34,0.16,0.24
Russian_Arkhangelsk_Krasnoborsky,28.17,47.65,5.02, 4.22,1.93,0.57,2.25,0.86,7.69,0.93,0.46,0.26,0.01
Russian_Arkhangelsk_Leshukonsky,25.10,48.98,2.01,4 .33,0.96,0.39,1.44,0.32,12.82,1.83,0.75,0.53,0.54
Russian_Arkhangelsk_Pinezhsky,26.31,51.18,3.49,2.7 9,1.01,0.17,2.28,0.32,9.31,1.84,0.56,0.56,0.22
Russian_Belgorod,23.68,47.78,11.25,5.76,5.85,1.50, 0.81,0.68,1.32,0.68,0.28,0.34,0.06
Russian_Kaluga,28.40,48.45,6.76,4.02,5.78,1.72,1.1 0,0.00,2.06,1.15,0.24,0.00,0.34
Russian_Kursk,26.62,47.79,7.60,4.82,7.36,0.36,0.93 ,0.76,1.91,0.90,0.37,0.41,0.18
Russian_Orel,27.52,44.96,8.03,6.18,6.28,1.08,1.24, 0.72,2.32,0.85,0.16,0.34,0.33
Russian_Pskov,27.00,53.07,7.78,4.50,1.25,1.69,0.54 ,0.03,1.87,0.73,0.58,0.45,0.50
Russian_Ryazan,24.89,47.15,8.72,7.10,4.48,0.69,1.6 7,0.40,2.97,0.99,0.32,0.39,0.23
Russian_Smolensk,26.22,48.27,9.39,4.48,6.48,0.42,1 .58,0.64,0.70,0.61,0.42,0.43,0.37
Russian_Tver,24.02,49.02,9.38,6.67,2.18,1.22,1.42, 0.17,3.91,1.26,0.14,0.52,0.10
Russian_Yaroslavl,26.39,50.24,9.22,5.00,0.55,0.74, 0.73,0.00,3.71,1.65,0.71,0.84,0.24

#K15
Bashkir_Central,13.48,7.20,13.69,22.01,1.08,9.26,1 .59,0.51,3.42,5.35,19.73,1.96,0.29,0.15,0.31
Bashkir_North,13.09,8.94,16.00,23.59,1.11,7.65,0.7 1,0.36,3.72,4.30,17.90,1.67,0.44,0.24,0.30
Bashkir_South,10.88,4.87,9.56,19.30,0.29,10.21,0.3 3,0.13,4.28,9.49,27.27,2.83,0.27,0.10,0.20
Russian_Arkhangelsk_Krasnoborsky,21.90,15.15,26.36 ,23.16,1.27,1.34,0.55,0.26,1.71,0.70,6.31,0.75,0.3 5,0.18,0.00
Russian_Arkhangelsk_Leshukonsky,21.32,10.90,23.55, 27.22,0.51,0.82,0.11,0.18,1.13,0.12,11.21,1.64,0.6 3,0.27,0.38
Russian_Arkhangelsk_Pinezhsky,21.03,12.63,24.46,28 .27,1.07,0.66,0.00,0.00,1.49,0.27,7.52,1.73,0.41,0 .38,0.07
Russian_Belgorod,18.05,14.70,30.80,20.34,6.34,4.38 ,2.16,1.01,0.24,0.41,0.57,0.36,0.28,0.37,0.00
Russian_Kaluga,20.85,15.76,31.01,20.91,2.68,3.30,1 .32,1.39,0.86,0.00,0.68,0.92,0.13,0.00,0.20
Russian_Kursk,20.98,13.50,29.62,22.27,3.50,2.94,3. 90,0.06,0.74,0.51,0.79,0.56,0.28,0.12,0.26
Russian_Orel,18.25,17.28,28.83,19.49,3.93,5.58,1.8 5,0.77,0.92,0.29,1.46,0.64,0.15,0.22,0.35
Russian_Pskov,19.25,14.70,33.04,23.84,2.99,2.82,0. 16,0.86,0.08,0.00,0.77,0.49,0.31,0.24,0.45
Russian_Ryazan,19.16,13.56,29.21,21.64,4.57,5.49,1 .62,0.28,1.13,0.27,1.56,0.71,0.22,0.35,0.23
Russian_Smolensk,17.63,16.15,31.95,20.98,4.92,3.31 ,2.29,0.28,1.05,0.20,0.12,0.24,0.25,0.31,0.31
Russian_Tver,17.58,14.28,30.37,22.66,4.68,3.68,1.1 8,0.41,0.93,0.04,2.64,0.97,0.03,0.42,0.15
Russian_Yaroslavl,20.70,12.91,30.86,23.63,5.04,1.7 0,0.00,0.00,0.27,0.00,2.19,1.36,0.50,0.65,0.18

#K12b
Bashkir_Central,8.96,18.31,0.37,0.95,11.03,38.13,1 .49,0.10,1.45,9.59,9.47,0.14
Bashkir_North,8.38,17.54,0.22,0.68,11.69,41.59,1.9 4,0.03,0.52,7.50,9.66,0.25
Bashkir_South,11.08,24.17,0.35,1.20,7.48,29.52,1.8 3,0.12,0.47,15.73,7.89,0.15
Russian_Arkhangelsk_Krasnoborsky,4.77,7.42,0.26,0. 28,18.80,59.08,0.69,0.00,0.54,1.60,6.55,0.00
Russian_Arkhangelsk_Leshukonsky,5.07,12.41,0.28,0. 80,12.12,59.86,0.99,0.39,1.24,1.40,5.40,0.03
Russian_Arkhangelsk_Pinezhsky,4.01,9.51,0.44,0.72, 15.46,62.88,1.26,0.28,0.33,0.58,4.31,0.23
Russian_Belgorod,2.61,1.79,0.14,0.19,20.74,58.38,0 .83,0.00,1.95,0.45,12.86,0.05
Russian_Kaluga,1.85,2.11,0.18,0.50,19.00,60.34,0.6 2,0.00,2.33,0.06,12.99,0.00
Russian_Kursk,3.31,1.57,0.00,0.28,19.46,58.41,1.25 ,0.08,1.93,0.42,13.15,0.15
Russian_Orel,3.64,2.13,0.46,0.22,19.38,56.10,1.51, 0.39,1.10,0.63,14.32,0.12
Russian_Pskov,2.68,1.95,0.04,0.42,20.60,62.03,0.89 ,0.05,1.61,0.01,9.38,0.34
Russian_Ryazan,4.58,3.36,0.35,0.09,20.50,56.92,0.9 6,0.14,0.64,0.33,12.04,0.08
Russian_Smolensk,4.46,1.34,0.25,0.62,21.99,57.22,0 .74,0.13,1.50,0.00,11.63,0.12
Russian_Tver,3.95,3.76,1.19,0.37,19.36,57.28,0.40, 0.00,1.71,0.47,11.17,0.35
Russian_Vologda,3.05,7.38,0.20,0.41,14.05,63.22,0. 95,0.04,1.41,0.77,8.53,0.01
Russian_Yaroslavl,3.36,4.03,0.89,0.00,20.00,60.00, 0.71,0.16,0.63,0.66,9.56,0.00

Individual samples:

#K13
Bashkir_Central:BAS-091,12.07,30.11,0.00,13.69,3.00,0.03,4.74,8.18,23. 64,3.86,0.00,0.00,0.67
Bashkir_Central:BAS-094,18.00,33.01,4.80,10.28,3.13,1.43,1.37,5.06,19. 83,1.88,0.34,0.31,0.55
Bashkir_Central:BAS-096,12.50,30.86,1.74,15.24,0.96,0.00,3.46,6.82,24. 75,1.29,1.10,0.02,1.26
Bashkir_Central:BAS-105,18.83,37.35,5.80,6.04,8.05,1.40,0.56,2.93,14.6 3,1.33,0.80,2.14,0.14
Bashkir_Central:BAS-111,16.80,30.58,5.63,14.17,3.27,0.38,2.51,4.48,18. 30,2.49,0.55,0.00,0.84
Bashkir_Central:BAS-120,12.94,24.40,2.67,17.26,1.70,0.00,5.65,7.45,24. 34,2.53,0.00,0.35,0.71
Bashkir_Central:BAS-121,14.06,30.34,5.10,12.53,4.79,0.22,2.82,5.79,18. 20,2.95,1.53,0.75,0.92
Bashkir_Central:BAS-125,14.43,34.03,4.64,11.36,2.81,0.49,4.41,4.82,20. 97,1.88,0.00,0.16,0.00
Bashkir_Central:BAS-135,16.22,27.20,6.44,10.29,0.12,0.02,3.88,7.60,24. 40,3.29,0.54,0.00,0.00
Bashkir_Central:BAS-600,12.73,30.50,1.51,10.88,2.17,0.00,4.55,9.46,25. 47,2.34,0.00,0.00,0.39
Bashkir_Central:BAS-622,12.71,27.59,2.74,12.10,5.10,3.38,2.40,7.90,24. 65,1.32,0.09,0.00,0.02
Bashkir_Central:BAS-655,15.37,32.37,1.62,10.10,3.92,0.00,4.31,4.93,23. 73,3.46,0.00,0.00,0.18
Bashkir_Central:BAS-661,17.28,30.80,2.33,14.96,0.00,0.00,2.85,4.51,25. 12,1.50,0.04,0.62,0.00
Bashkir_Central:BAS-663,12.63,33.53,1.13,15.89,0.00,0.11,4.73,6.18,22. 83,2.00,0.00,0.13,0.86
Bashkir_Central:BAS-669,16.88,35.15,0.00,15.09,0.68,1.61,2.76,2.92,19. 92,3.50,1.50,0.00,0.00
Bashkir_Central:BAS-672,20.32,30.21,2.75,9.22,3.33,0.84,2.66,8.26,19.8 4,2.28,0.00,0.30,0.00
Bashkir_Central:BAS-1392,20.31,34.89,0.46,10.37,8.09,0.00,2.53,5.81,14 .64,2.19,0.43,0.00,0.27
Bashkir_Central:BAS-1393,17.49,30.85,5.37,13.90,1.35,0.20,5.81,3.90,20 .41,0.30,0.00,0.00,0.42
Bashkir_Central:BAS-1394,13.07,33.64,4.93,10.38,4.36,2.36,5.96,4.59,18 .84,1.46,0.37,0.01,0.03
Bashkir_Central:BAS-1396,17.11,31.72,1.77,12.11,6.24,1.45,6.10,2.95,17 .16,2.80,0.58,0.00,0.00
Bashkir_Central:BAS-1398,18.18,37.79,2.84,11.63,3.78,0.24,1.20,2.90,19 .98,0.81,0.21,0.44,0.00
Bashkir_Central:BAS-1400,13.72,33.93,5.61,12.58,0.00,2.15,2.94,1.03,23 .76,3.53,0.00,0.00,0.74
Bashkir_North:BAS-652,17.84,34.24,3.50,6.88,3.06,0.00,5.24,4.49,22.1 9,1.13,0.53,0.90,0.00
Bashkir_North:BAS-670,18.20,34.23,4.84,7.13,1.91,0.00,3.48,4.78,20.9 3,3.31,0.00,1.19,0.00
Bashkir_North:BAS-671,16.03,35.16,1.36,13.35,0.00,0.00,3.60,4.63,21. 58,2.68,1.20,0.00,0.42
Bashkir_North:BAS-683,11.75,35.91,3.35,11.59,5.38,0.02,1.61,7.70,19. 90,2.14,0.19,0.00,0.46
Bashkir_North:BAS-811,18.10,34.83,3.60,14.37,2.20,0.00,2.61,2.14,18. 41,1.37,1.05,0.00,1.31
Bashkir_North:BAS-813,18.99,36.93,1.56,9.48,3.29,2.38,3.20,3.52,17.4 2,1.81,0.68,0.00,0.72
Bashkir_North:BAS-822,16.70,33.24,5.39,13.12,0.00,0.26,4.09,4.14,19. 17,1.80,1.52,0.57,0.00
Bashkir_North:BAS-825,13.83,35.88,1.75,11.25,4.25,1.60,5.95,3.30,19. 37,2.27,0.56,0.00,0.00
Bashkir_North:BAS-831,20.28,37.05,1.74,9.60,4.62,0.25,3.21,5.36,16.1 4,1.06,0.00,0.00,0.69
Bashkir_North:BAS-833,15.40,35.79,6.10,11.93,0.54,0.00,4.09,4.86,18. 54,2.26,0.49,0.00,0.00
Bashkir_North:BAS-834,18.23,32.77,4.52,11.10,2.39,1.16,5.04,3.64,18. 87,2.17,0.00,0.11,0.00
Bashkir_North:BAS-849,18.88,32.51,6.99,8.88,0.00,1.53,3.95,4.42,20.7 6,0.37,0.87,0.00,0.84
Bashkir_South:BAS-005,12.69,26.52,0.00,12.28,0.00,0.00,6.69,9.23,29. 43,3.17,0.00,0.00,0.00
Bashkir_South:BAS-006,14.84,20.58,0.00,16.88,0.00,1.74,4.48,8.82,29. 45,2.31,0.68,0.22,0.00
Bashkir_South:BAS-008,16.05,21.18,0.00,13.24,0.00,0.00,4.10,10.86,29 .06,4.90,0.48,0.00,0.13
Bashkir_South:BAS-014,17.57,24.22,0.71,8.31,2.87,0.14,3.89,7.11,30.5 3,3.73,0.92,0.00,0.00
Bashkir_South:BAS-017,14.79,20.71,0.82,15.31,0.00,0.12,6.15,10.44,30 .01,0.70,0.00,0.00,0.95
Bashkir_South:BAS-021,11.17,24.69,2.69,13.21,0.17,0.64,4.70,9.16,29. 34,2.91,0.65,0.50,0.17
Bashkir_South:BAS-029,13.31,27.13,0.00,12.31,0.74,0.32,6.54,8.36,27. 08,4.20,0.00,0.00,0.00
Bashkir_South:BAS-031,11.39,22.63,0.00,14.77,0.22,0.29,5.28,12.46,29 .84,2.69,0.00,0.00,0.42
Bashkir_South:BAS-033,13.21,19.98,2.15,16.88,0.00,0.00,4.47,8.49,29. 69,4.39,0.75,0.00,0.00
Bashkir_South:BAS-034,11.97,24.96,0.72,11.56,2.94,0.00,4.68,11.96,27 .96,1.52,0.92,0.43,0.38
Bashkir_South:BAS-042,12.44,26.33,2.83,12.11,0.00,0.00,2.59,8.73,30. 37,3.14,0.00,1.21,0.24
Bashkir_South:BAS-045,12.46,21.30,2.78,14.29,3.02,0.00,2.86,11.22,27 .77,3.42,0.48,0.40,0.00
Bashkir_South:BAS-046,13.50,25.78,0.00,12.67,3.57,0.00,5.08,8.07,28. 43,2.76,0.00,0.08,0.06
Bashkir_South:BAS-060,10.02,27.77,0.28,13.08,1.81,0.00,4.24,9.53,30. 37,2.86,0.00,0.06,0.00
Bashkir_South:BAS-062,10.08,25.57,2.26,13.56,2.13,0.00,3.75,8.48,30. 29,3.89,0.00,0.00,0.00
Bashkir_South:BAS-150,7.73,25.53,4.63,16.83,2.12,0.70,0.14,11.64,26. 89,2.88,0.91,0.00,0.00
Bashkir_South:BAS-153,13.81,25.70,2.54,14.65,0.18,1.24,4.71,7.81,24. 55,3.47,0.21,0.00,1.12
Bashkir_South:BAS-156,11.64,30.60,0.00,12.32,0.56,0.57,3.72,9.17,28. 16,2.50,0.00,0.20,0.55
Bashkir_South:BAS-164,13.43,31.07,1.24,11.71,1.86,0.00,1.51,11.34,25 .69,1.22,0.48,0.00,0.45
Russian_Arkhangelsk_Krasnoborsky:Rakr-203,27.86,48.62,4.44,4.94,0.14,0.26,1.28,2.37,7.81 ,1.35,0.94,0.00,0.00
Russian_Arkhangelsk_Krasnoborsky:Rakr-205,27.36,46.43,4.44,4.03,5.04,1.37,2.70,1.10,5.70 ,0.03,1.20,0.60,0.00
Russian_Arkhangelsk_Krasnoborsky:Rakr-237,27.74,45.53,7.26,3.67,2.68,1.78,0.40,1.41,7.63 ,1.91,0.00,0.00,0.00
Russian_Arkhangelsk_Krasnoborsky:Rakr-248,25.48,50.30,5.62,4.11,1.96,0.03,4.31,0.00,7.61 ,0.00,0.00,0.57,0.00
Russian_Arkhangelsk_Krasnoborsky:Rakr-341,30.12,48.54,3.58,3.10,0.00,0.00,2.60,0.00,10.3 4,1.04,0.28,0.36,0.04
Russian_Arkhangelsk_Krasnoborsky:Rakr-345,30.47,46.46,4.75,5.46,1.77,0.00,2.21,0.25,7.03 ,1.27,0.34,0.00,0.00
Russian_Arkhangelsk_Leshukonsky:Rakrlsh-002,25.95,49.80,0.00,5.87,0.00,0.00,1.33,1.03,13.1 9,1.02,0.91,0.91,0.00
Russian_Arkhangelsk_Leshukonsky:Rakrlsh-140,26.25,45.81,6.11,3.43,0.00,0.00,0.80,0.19,15.0 9,1.03,0.00,0.00,1.29
Russian_Arkhangelsk_Leshukonsky:Rakrlsh-143,24.93,45.99,0.71,6.81,2.51,0.00,2.92,0.00,12.7 9,2.03,0.49,0.00,0.81
Russian_Arkhangelsk_Leshukonsky:Rakrlsh-144,25.19,53.19,0.00,3.18,0.00,0.00,0.15,0.23,13.2 3,2.65,0.98,0.62,0.58
Russian_Arkhangelsk_Leshukonsky:Rakrlsh-149,23.17,50.13,3.24,2.38,2.27,1.97,2.01,0.13,9.79 ,2.41,1.38,1.11,0.01
Russian_Arkhangelsk_Pinezhsky:RPin-114,25.09,49.29,8.92,1.88,0.73,0.00,0.58,0.00,8.36 ,3.42,1.40,0.26,0.08
Russian_Arkhangelsk_Pinezhsky:RPin-123,28.68,51.10,1.58,3.28,0.00,0.00,2.40,0.00,11.4 2,0.00,0.91,0.65,0.00
Russian_Arkhangelsk_Pinezhsky:RPin-143,26.38,49.77,2.57,5.21,1.95,0.41,2.84,1.49,8.59 ,0.79,0.00,0.00,0.00
Russian_Arkhangelsk_Pinezhsky:RPin-145,23.21,50.93,3.49,3.56,2.07,0.44,2.19,0.02,9.24 ,2.53,0.45,1.88,0.00
Russian_Arkhangelsk_Pinezhsky:RPin-151,28.20,54.80,0.91,0.00,0.28,0.00,3.38,0.07,8.94 ,2.48,0.02,0.00,1.00
Russian_Belgorod:Rbgp-200,24.44,48.86,12.68,4.27,4.37,1.23,0.16,0.48,2.1 5,1.36,0.00,0.00,0.00
Russian_Belgorod:Rbgp-201,22.21,49.61,9.69,3.92,7.63,1.15,1.35,0.00,1.91 ,0.75,0.42,1.38,0.00
Russian_Belgorod:Rbgp-203,23.58,42.33,13.17,8.98,7.90,0.79,0.00,1.50,1.1 0,0.00,0.64,0.00,0.00
Russian_Belgorod:Rbgp-205,24.50,50.32,9.46,5.86,3.49,2.83,1.74,0.75,0.13 ,0.61,0.06,0.00,0.26
Russian_Kaluga:Rkbo-12,28.25,48.57,6.63,1.90,7.63,2.02,2.19,0.00,1.35, 1.09,0.00,0.00,0.38
Russian_Kaluga:Rkbo-16,29.49,46.09,6.82,5.18,3.15,3.24,0.15,0.00,3.29, 1.90,0.69,0.00,0.00
Russian_Kaluga:Rkbo-44,28.41,46.71,7.03,2.17,9.29,0.00,2.04,0.00,1.96, 1.62,0.27,0.00,0.51
Russian_Kaluga:Rkbo-58,27.44,52.44,6.57,6.81,3.04,1.61,0.00,0.00,1.63, 0.00,0.00,0.00,0.47
Russian_Kursk:Rkuch-03,25.38,49.87,5.91,3.38,10.21,0.45,0.16,0.00,3.65 ,0.21,0.00,0.52,0.26
Russian_Kursk:Rkuch-05,31.46,47.12,6.94,4.86,5.74,0.00,0.00,0.42,2.31, 0.58,0.38,0.19,0.00
Russian_Kursk:Rkuch-53,22.63,46.39,6.32,6.46,13.49,0.00,0.05,2.60,1.14 ,0.92,0.00,0.00,0.00
Russian_Kursk:Rkuch-58,27.01,47.77,11.24,4.59,0.00,0.98,3.52,0.00,0.53 ,1.88,1.09,0.93,0.46
Russian_Orel:Rorl-102,27.59,45.03,7.95,5.64,3.03,0.00,2.94,0.97,5.18 ,0.00,0.39,0.00,1.28
Russian_Orel:Rorl-110,23.30,48.26,8.83,10.25,4.33,1.36,0.18,1.90,0.0 0,0.18,0.01,1.34,0.04
Russian_Orel:Rorl-114,29.35,41.92,7.12,5.10,10.16,2.22,0.82,0.00,1.8 4,1.47,0.00,0.00,0.00
Russian_Orel:Rorl-155,29.83,44.61,8.23,3.71,7.59,0.75,1.01,0.00,2.24 ,1.76,0.25,0.03,0.00
Russian_Pskov:Rps-004,25.17,58.94,6.28,0.97,0.00,5.23,1.71,0.00,0.00 ,0.00,1.18,0.53,0.00
Russian_Pskov:Rps-006,29.40,54.88,7.35,3.40,0.00,0.76,1.40,0.00,0.69 ,1.15,0.13,0.00,0.83
Russian_Pskov:Rps-012,29.21,52.56,8.13,3.06,2.57,0.00,0.07,0.20,1.98 ,1.06,0.15,1.00,0.00
Russian_Pskov:Rps-090,30.28,52.01,5.70,6.36,0.00,0.09,0.00,0.00,2.73 ,0.00,1.73,0.32,0.78
Russian_Pskov:Rps-091,23.93,49.74,11.25,5.86,1.15,3.40,0.08,0.00,2.2 9,0.79,0.00,0.09,1.41
Russian_Pskov:Rps-098,24.02,50.27,7.95,7.36,3.77,0.65,0.00,0.00,3.54 ,1.36,0.29,0.78,0.00
Russian_Ryazan:Rrzm-08,28.45,43.70,9.59,9.22,4.03,0.32,0.21,0.00,1.58, 1.24,0.65,1.03,0.00
Russian_Ryazan:Rrzm-10,21.97,49.95,7.68,5.10,9.24,0.39,0.47,1.35,1.02, 1.44,0.48,0.56,0.35
Russian_Ryazan:Rrzm-13,21.35,48.63,9.32,8.96,0.31,1.26,2.26,0.00,4.93, 1.40,0.57,1.01,0.00
Russian_Ryazan:Rrzm-16,23.95,47.11,9.08,4.31,7.46,0.23,4.38,1.84,0.00, 0.66,0.29,0.00,0.68
Russian_Ryazan:Rrzs-3,22.11,51.89,8.54,2.05,9.53,0.02,1.00,0.00,3.05,1 .48,0.00,0.00,0.32
Russian_Ryazan:Rrzs-7,23.21,48.56,7.94,9.03,2.88,0.26,1.23,1.09,3.64,1 .59,0.02,0.00,0.56
Russian_Ryazan:Rrzs-11,24.62,45.49,12.24,9.53,0.22,0.00,2.65,0.13,3.59 ,1.52,0.00,0.00,0.00
Russian_Ryazan:Rrzs-32,27.45,48.79,7.74,5.54,2.36,1.82,1.04,0.00,3.69, 0.69,0.00,0.85,0.02
Russian_Ryazan:Rrzs-58,23.59,47.94,8.09,6.28,7.88,0.00,2.44,0.00,3.06, 0.32,0.18,0.00,0.23
Russian_Ryazan:Rrzs-66,28.09,43.46,8.76,10.52,0.00,1.29,1.92,0.00,4.47 ,0.00,0.31,0.85,0.33
Russian_Ryazan:Rrzs-88,29.02,43.09,6.97,7.55,5.37,2.03,0.74,0.03,3.63, 0.52,1.06,0.00,0.00
Russian_Smolensk:Rsm-103,26.39,47.31,10.49,2.31,6.37,1.35,3.91,0.00,1.4 0,0.47,0.00,0.00,0.00
Russian_Smolensk:Rsm-109,27.27,48.64,10.87,5.02,4.77,0.00,0.10,0.82,1.6 8,0.00,0.36,0.46,0.00
Russian_Smolensk:Rsm-166,27.75,46.89,7.81,7.85,6.15,0.00,1.80,0.00,0.23 ,0.79,0.32,0.40,0.00
Russian_Smolensk:Rsm-171,27.98,48.38,10.25,1.21,5.92,0.65,1.80,1.20,0.5 9,0.42,0.79,0.81,0.00
Russian_Smolensk:Rsm-176,21.92,49.99,8.16,5.32,9.02,0.04,2.51,0.58,0.00 ,1.13,0.00,1.33,0.00
Russian_Smolensk:Rsm-179,27.80,46.84,7.49,6.63,6.05,0.89,0.92,0.83,0.99 ,0.15,0.57,0.00,0.83
Russian_Smolensk:Rsm-181,24.44,49.82,10.65,3.01,7.08,0.00,0.00,1.02,0.0 0,1.33,0.88,0.00,1.76
Russian_Tver:Rksh-402,28.04,47.39,8.29,6.89,0.00,0.32,2.18,0.00,4.68 ,1.57,0.58,0.00,0.06
Russian_Tver:Rksh-405,20.95,47.97,10.90,8.86,3.17,3.02,0.00,0.67,2.4 0,2.07,0.00,0.00,0.00
Russian_Tver:Rksh-407,25.32,48.23,8.72,6.55,0.00,0.90,1.43,0.00,5.86 ,0.89,0.00,2.09,0.00
Russian_Tver:Rksh-412,21.76,52.48,9.59,4.38,5.53,0.66,2.06,0.00,2.70 ,0.49,0.00,0.00,0.35
Russian_Yaroslavl:RYAR-173,26.83,51.70,8.58,3.83,1.65,0.00,0.00,0.00,3.95 ,1.49,0.67,0.59,0.73
Russian_Yaroslavl:RYAR-223,24.63,51.44,10.42,2.94,0.00,1.02,0.70,0.00,4.8 8,1.90,0.14,1.93,0.00
Russian_Yaroslavl:RYAR-232,27.72,47.58,8.66,8.22,0.00,1.19,1.49,0.00,2.29 ,1.55,1.31,0.00,0.00

#K15
Bashkir_Central:BAS-091,15.36,0.49,12.95,19.23,0.00,12.21,0.00,0.00,5. 17,7.89,22.39,3.83,0.00,0.00,0.48
Bashkir_Central:BAS-094,17.68,5.07,14.48,22.25,2.83,6.39,3.43,0.67,0.9 0,5.64,18.25,1.79,0.09,0.09,0.45
Bashkir_Central:BAS-096,11.85,5.04,11.80,24.49,0.00,9.79,0.36,0.00,3.6 7,6.70,23.11,1.10,1.02,0.00,1.07
Bashkir_Central:BAS-105,11.60,12.41,19.05,23.16,2.27,4.31,6.30,0.85,0. 08,2.98,13.15,1.05,0.74,1.52,0.53
Bashkir_Central:BAS-111,16.81,5.31,13.84,19.99,3.25,10.25,3.08,0.00,2. 46,4.25,16.98,2.31,0.61,0.00,0.84
Bashkir_Central:BAS-120,7.34,8.84,10.43,19.44,0.00,12.73,1.88,0.00,5.7 3,7.43,22.75,2.47,0.00,0.43,0.54
Bashkir_Central:BAS-121,16.23,4.39,11.41,21.31,1.73,10.76,3.62,0.00,2. 40,5.93,16.75,2.77,1.38,0.40,0.93
Bashkir_Central:BAS-125,11.10,8.93,13.61,25.65,1.30,6.87,2.65,0.08,3.9 6,4.79,19.64,1.42,0.00,0.00,0.00
Bashkir_Central:BAS-135,10.71,10.83,9.60,20.13,2.97,8.27,0.00,0.00,3.6 9,7.49,23.05,2.94,0.33,0.00,0.00
Bashkir_Central:BAS-600,10.52,5.45,13.74,21.45,0.00,8.84,0.00,0.00,4.1 2,9.37,24.03,2.08,0.00,0.00,0.39
Bashkir_Central:BAS-622,10.78,5.95,11.77,20.11,1.40,10.19,1.89,3.33,2. 28,8.15,22.97,1.17,0.00,0.00,0.01
Bashkir_Central:BAS-655,15.23,6.66,12.86,21.81,0.00,7.54,1.28,0.00,4.5 2,4.98,22.04,2.97,0.00,0.00,0.13
Bashkir_Central:BAS-661,15.63,8.32,12.16,21.42,0.00,10.09,0.00,0.00,2. 75,4.49,23.80,1.20,0.00,0.15,0.00
Bashkir_Central:BAS-663,16.51,0.76,11.88,26.24,0.00,10.30,0.00,0.00,4. 66,6.03,21.37,1.56,0.00,0.16,0.54
Bashkir_Central:BAS-669,11.79,8.70,13.49,26.10,0.00,11.48,0.00,0.08,2. 81,2.67,18.30,3.33,1.26,0.00,0.00
Bashkir_Central:BAS-672,17.08,9.01,14.35,19.20,0.87,5.71,1.09,0.78,2.9 7,8.17,18.64,2.02,0.00,0.10,0.00
Bashkir_Central:BAS-1392,15.79,9.74,14.54,22.96,0.00,10.88,2.58,0.00,2 .08,5.87,13.31,1.70,0.49,0.00,0.07
Bashkir_Central:BAS-1393,11.09,11.64,12.45,22.72,2.19,11.39,0.00,0.00, 5.53,3.76,18.96,0.03,0.00,0.00,0.24
Bashkir_Central:BAS-1394,11.42,7.04,18.38,18.78,1.38,9.30,1.86,2.57,5. 64,4.48,17.72,1.31,0.12,0.00,0.00
Bashkir_Central:BAS-1396,11.70,10.04,14.57,21.65,0.00,9.58,3.39,1.30,6 .02,2.99,15.73,2.58,0.44,0.00,0.00
Bashkir_Central:BAS-1398,15.86,7.64,17.27,26.21,0.62,7.95,1.56,0.06,0. 94,2.67,18.55,0.28,0.00,0.38,0.00
Bashkir_Central:BAS-1400,14.52,6.05,16.51,19.83,2.86,8.89,0.00,1.41,2. 82,0.88,22.48,3.24,0.00,0.00,0.52
Bashkir_North:BAS-652,13.48,11.76,14.60,22.75,0.43,3.57,1.09,0.00,4. 93,4.13,20.73,1.07,0.46,1.00,0.00
Bashkir_North:BAS-670,11.29,13.77,16.05,21.82,1.06,4.38,0.00,0.00,3. 01,4.78,19.33,3.17,0.00,1.24,0.11
Bashkir_North:BAS-671,11.53,8.38,14.67,25.75,0.00,7.66,0.00,0.00,3.6 7,4.30,20.16,2.55,0.97,0.00,0.37
Bashkir_North:BAS-683,14.47,1.02,11.58,30.65,2.09,7.89,2.98,0.25,1.6 1,7.69,17.40,1.95,0.13,0.09,0.19
Bashkir_North:BAS-811,12.13,10.24,18.00,22.49,0.45,11.91,0.00,0.00,2 .84,1.92,16.99,1.34,0.65,0.00,1.03
Bashkir_North:BAS-813,16.78,6.67,18.40,23.35,0.00,7.50,0.33,1.99,3.0 8,3.40,15.83,1.58,0.44,0.00,0.65
Bashkir_North:BAS-822,14.77,7.35,15.73,21.83,2.05,8.75,0.00,0.00,4.5 2,3.98,17.98,1.60,1.28,0.16,0.00
Bashkir_North:BAS-825,13.49,5.77,14.80,24.83,0.00,7.88,2.54,1.53,5.8 4,3.15,17.82,1.94,0.41,0.00,0.00
Bashkir_North:BAS-831,15.49,8.91,19.99,22.38,0.00,7.38,1.42,0.00,3.3 0,5.16,14.78,0.68,0.00,0.00,0.51
Bashkir_North:BAS-833,11.59,8.74,17.60,22.74,1.53,10.11,0.00,0.00,3. 34,4.87,17.19,1.97,0.35,0.00,0.00
Bashkir_North:BAS-834,12.21,12.18,15.40,20.52,1.94,9.24,0.00,0.18,5. 04,3.76,17.47,1.93,0.00,0.12,0.00
Bashkir_North:BAS-849,9.82,12.51,15.14,23.99,3.77,5.48,0.21,0.31,3.4 4,4.40,19.16,0.21,0.65,0.21,0.69
Bashkir_South:BAS-005,11.46,2.47,11.22,20.79,0.00,7.09,0.00,0.00,6.8 7,9.16,27.87,3.08,0.00,0.00,0.00
Bashkir_South:BAS-006,14.74,4.47,6.81,15.63,0.00,13.09,0.00,0.87,4.8 0,8.58,28.29,2.09,0.51,0.13,0.00
Bashkir_South:BAS-008,10.31,7.21,8.88,15.58,0.00,10.14,0.00,0.00,4.1 9,10.34,28.25,4.73,0.37,0.00,0.00
Bashkir_South:BAS-014,9.89,11.52,11.52,15.78,0.00,6.52,0.00,0.19,4.1 9,6.83,29.30,3.45,0.80,0.00,0.00
Bashkir_South:BAS-017,11.83,4.98,9.07,14.82,0.00,12.56,0.00,0.00,6.1 6,10.36,29.09,0.49,0.00,0.00,0.64
Bashkir_South:BAS-021,6.42,6.10,10.00,21.86,0.00,10.51,0.00,0.00,4.6 4,9.24,27.26,2.78,0.59,0.59,0.00
Bashkir_South:BAS-029,11.01,4.69,8.04,24.33,0.00,7.58,0.00,0.00,6.68 ,8.53,25.16,3.98,0.00,0.00,0.00
Bashkir_South:BAS-031,4.28,8.31,11.12,15.25,0.00,11.91,0.00,0.00,5.3 4,12.23,28.74,2.66,0.00,0.00,0.16
Bashkir_South:BAS-033,8.03,6.99,8.41,16.41,0.50,13.05,0.00,0.00,4.75 ,8.23,28.28,4.52,0.85,0.00,0.00
Bashkir_South:BAS-034,11.29,3.06,9.52,20.57,0.00,7.53,1.97,0.00,4.64 ,12.16,26.47,1.43,0.71,0.32,0.32
Bashkir_South:BAS-042,14.24,2.08,9.74,19.78,1.16,8.78,0.00,0.00,2.60 ,8.16,28.93,3.20,0.00,0.83,0.49
Bashkir_South:BAS-045,13.16,5.59,6.98,15.61,0.39,12.16,1.37,0.00,2.8 0,11.38,26.65,3.27,0.40,0.00,0.25
Bashkir_South:BAS-046,14.66,2.74,9.51,18.00,0.00,10.84,1.29,0.00,5.3 2,7.80,27.08,2.62,0.00,0.00,0.13
Bashkir_South:BAS-060,12.58,0.28,7.51,23.95,0.03,10.48,0.08,0.00,4.3 9,9.37,28.56,2.75,0.00,0.00,0.00
Bashkir_South:BAS-062,6.16,5.58,9.63,22.62,0.63,9.55,1.32,0.00,4.08, 7.98,29.00,3.47,0.00,0.00,0.00
Bashkir_South:BAS-150,9.45,1.19,11.41,19.87,2.78,14.35,0.07,0.61,0.0 1,11.77,25.42,2.43,0.63,0.00,0.00
Bashkir_South:BAS-153,9.44,9.05,11.52,18.55,0.00,10.82,0.00,0.71,4.7 5,7.71,23.38,3.14,0.03,0.00,0.90
Bashkir_South:BAS-156,15.15,0.00,9.77,24.23,0.00,8.87,0.00,0.00,3.35 ,9.20,26.38,2.53,0.00,0.00,0.53
Bashkir_South:BAS-164,12.63,6.22,10.90,23.15,0.00,8.24,0.21,0.00,1.7 3,11.20,24.10,1.13,0.16,0.00,0.33
Russian_Arkhangelsk_Krasnoborsky:Rakr-203,24.58,12.45,29.34,21.12,0.00,1.07,0.00,0.00,0. 78,2.05,6.83,1.04,0.74,0.00,0.00
Russian_Arkhangelsk_Krasnoborsky:Rakr-205,19.27,16.15,25.55,24.86,0.75,0.63,3.28,0.52,2. 48,0.80,4.09,0.00,1.05,0.57,0.00
Russian_Arkhangelsk_Krasnoborsky:Rakr-237,19.77,17.62,24.33,22.78,3.44,2.09,0.00,1.05,0. 00,0.97,6.39,1.56,0.00,0.00,0.00
Russian_Arkhangelsk_Krasnoborsky:Rakr-248,20.50,11.12,29.73,23.95,2.93,1.90,0.00,0.00,3. 45,0.00,5.95,0.00,0.00,0.47,0.00
Russian_Arkhangelsk_Krasnoborsky:Rakr-341,24.83,13.92,26.84,22.34,0.00,0.00,0.00,0.00,1. 95,0.00,9.19,0.74,0.12,0.07,0.00
Russian_Arkhangelsk_Krasnoborsky:Rakr-345,22.48,19.66,22.40,23.88,0.50,2.32,0.00,0.00,1. 60,0.41,5.41,1.15,0.19,0.00,0.00
Russian_Arkhangelsk_Leshukonsky:Rakrlsh-002,21.50,10.01,24.69,27.23,0.00,1.06,0.00,0.00,1. 48,0.38,11.59,0.90,0.74,0.42,0.00
Russian_Arkhangelsk_Leshukonsky:Rakrlsh-140,25.82,9.87,23.01,22.90,2.54,0.00,0.00,0.00,0.1 6,0.24,13.68,0.84,0.00,0.00,0.93
Russian_Arkhangelsk_Leshukonsky:Rakrlsh-143,18.50,13.93,22.96,24.91,0.00,2.92,0.00,0.00,2. 60,0.00,11.43,1.92,0.43,0.00,0.41
Russian_Arkhangelsk_Leshukonsky:Rakrlsh-144,22.47,7.26,22.22,33.23,0.00,0.00,0.00,0.00,0.0 0,0.00,11.04,2.43,0.81,0.00,0.54
Russian_Arkhangelsk_Leshukonsky:Rakrlsh-149,18.32,13.42,24.89,27.83,0.00,0.10,0.56,0.92,1. 43,0.00,8.33,2.09,1.17,0.95,0.00
Russian_Arkhangelsk_Pinezhsky:RPin-114,19.00,15.35,24.22,24.81,5.34,0.00,0.00,0.00,0. 00,0.00,6.88,3.26,1.16,0.00,0.00
Russian_Arkhangelsk_Pinezhsky:RPin-123,16.36,18.32,20.36,33.35,0.00,0.00,0.00,0.00,1. 55,0.00,9.32,0.00,0.64,0.09,0.00
Russian_Arkhangelsk_Pinezhsky:RPin-143,25.21,10.39,23.03,28.15,0.00,2.19,0.00,0.00,2. 21,1.37,6.83,0.62,0.00,0.00,0.00
Russian_Arkhangelsk_Pinezhsky:RPin-145,19.91,11.77,24.41,29.16,0.00,1.12,0.00,0.00,1. 86,0.00,7.29,2.43,0.26,1.80,0.00
Russian_Arkhangelsk_Pinezhsky:RPin-151,24.67,7.33,30.28,25.90,0.00,0.00,0.00,0.00,1.8 1,0.00,7.30,2.33,0.00,0.00,0.36
Russian_Belgorod:Rbgp-200,20.09,12.96,29.46,23.65,8.35,1.24,1.40,1.09,0. 00,0.08,0.67,1.01,0.00,0.00,0.00
Russian_Belgorod:Rbgp-201,17.80,12.97,31.00,22.21,5.43,3.39,2.90,0.80,0. 94,0.00,0.38,0.41,0.30,1.48,0.00
Russian_Belgorod:Rbgp-203,21.53,14.18,29.46,13.11,6.97,8.16,3.93,0.65,0. 00,1.56,0.03,0.00,0.43,0.00,0.00
Russian_Belgorod:Rbgp-205,12.77,18.67,33.30,22.39,4.63,4.74,0.43,1.49,0. 00,0.00,1.20,0.00,0.39,0.00,0.00
Russian_Kaluga:Rkbo-12,21.90,13.37,32.36,20.08,3.25,1.95,2.18,1.97,1.7 3,0.00,0.27,0.69,0.00,0.00,0.27
Russian_Kaluga:Rkbo-16,20.98,15.62,28.99,20.94,2.50,4.60,0.00,2.54,0.0 0,0.00,1.83,1.63,0.37,0.00,0.00
Russian_Kaluga:Rkbo-44,20.52,15.99,28.74,21.25,3.94,2.40,3.10,0.00,1.6 9,0.00,0.55,1.37,0.16,0.00,0.29
Russian_Kaluga:Rkbo-58,20.00,18.07,33.94,21.36,1.05,4.25,0.00,1.04,0.0 0,0.00,0.06,0.00,0.00,0.00,0.23
Russian_Kursk:Rkuch-03,25.90,8.72,27.38,26.16,2.52,0.95,5.67,0.24,0.00 ,0.00,1.86,0.00,0.00,0.23,0.38
Russian_Kursk:Rkuch-05,22.63,18.70,31.69,17.95,1.52,3.25,2.05,0.00,0.0 0,0.29,1.29,0.34,0.30,0.00,0.00
Russian_Kursk:Rkuch-53,15.75,12.76,30.22,21.13,2.86,6.92,7.90,0.00,0.0 0,1.74,0.00,0.74,0.00,0.00,0.00
Russian_Kursk:Rkuch-58,19.65,13.81,29.17,23.85,7.10,0.62,0.00,0.00,2.9 7,0.00,0.00,1.18,0.80,0.23,0.65
Russian_Orel:Rorl-102,16.80,17.51,27.85,22.42,3.67,3.30,0.00,0.00,2. 75,0.47,3.82,0.00,0.40,0.00,1.02
Russian_Orel:Rorl-110,17.34,12.97,30.41,22.19,4.78,9.33,0.00,1.24,0. 00,0.68,0.00,0.00,0.00,0.69,0.38
Russian_Orel:Rorl-114,22.10,17.11,25.30,17.15,4.30,5.58,4.58,1.41,0. 51,0.00,0.88,1.08,0.00,0.00,0.00
Russian_Orel:Rorl-155,16.77,21.54,31.75,16.20,2.98,4.10,2.81,0.43,0. 40,0.00,1.15,1.47,0.21,0.18,0.00
Russian_Pskov:Rps-002,17.44,9.81,34.61,22.76,3.66,7.72,1.09,0.00,0.0 0,0.00,0.10,1.30,0.00,0.53,0.97
Russian_Pskov:Rps-004,19.18,10.02,37.87,27.10,2.03,0.00,0.00,3.24,0. 00,0.00,0.00,0.00,0.57,0.00,0.00
Russian_Pskov:Rps-006,21.84,15.74,36.35,22.29,1.94,0.00,0.00,0.00,0. 55,0.00,0.00,0.61,0.00,0.00,0.69
Russian_Pskov:Rps-012,19.01,18.51,30.52,26.71,3.54,0.06,0.00,0.00,0. 00,0.00,0.52,0.48,0.00,0.64,0.00
Russian_Pskov:Rps-090,24.20,16.08,30.71,22.60,1.12,2.11,0.00,0.00,0. 00,0.00,1.18,0.00,1.53,0.00,0.48
Russian_Pskov:Rps-091,18.48,13.73,29.84,22.97,6.31,3.83,0.00,2.48,0. 00,0.00,1.20,0.16,0.00,0.00,0.99
Russian_Pskov:Rps-098,14.58,18.99,31.36,22.43,2.32,6.04,0.05,0.32,0. 00,0.00,2.41,0.85,0.10,0.54,0.00
Russian_Ryazan:Rrzm-08,16.48,18.96,27.13,21.46,4.81,8.66,0.44,0.00,0.0 0,0.00,0.00,0.93,0.41,0.72,0.00
Russian_Ryazan:Rrzm-10,23.05,8.69,30.14,21.63,3.84,4.12,4.94,0.13,0.13 ,1.00,0.13,1.16,0.20,0.32,0.53
Russian_Ryazan:Rrzm-13,17.30,10.51,29.50,23.38,5.11,6.53,0.00,0.07,1.5 9,0.00,3.91,1.00,0.29,0.81,0.00
Russian_Ryazan:Rrzm-16,21.42,9.48,32.05,17.97,6.16,3.98,2.86,0.00,4.03 ,1.15,0.00,0.29,0.10,0.00,0.51
Russian_Ryazan:Rrzm-83,16.22,15.55,28.20,23.24,4.78,8.29,0.00,0.00,0.0 0,0.00,0.00,1.65,0.19,1.53,0.35
Russian_Ryazan:Rrzs-3,16.93,13.36,34.91,21.79,3.33,0.44,5.85,0.00,0.65 ,0.00,1.86,0.89,0.00,0.00,0.00
Russian_Ryazan:Rrzs-7,18.90,12.67,27.89,25.18,3.91,6.14,0.00,0.00,0.99 ,0.87,2.04,1.04,0.00,0.00,0.37
Russian_Ryazan:Rrzs-11,19.89,11.45,26.19,23.96,7.41,5.93,0.00,0.00,2.1 6,0.00,1.91,1.09,0.00,0.00,0.00
Russian_Ryazan:Rrzs-32,22.56,14.03,29.59,22.33,4.19,2.28,0.00,1.27,0.3 3,0.00,2.53,0.31,0.00,0.59,0.00
Russian_Ryazan:Rrzs-58,14.47,14.57,30.86,23.08,3.91,5.88,3.47,0.00,2.0 4,0.00,1.33,0.03,0.19,0.00,0.18
Russian_Ryazan:Rrzs-66,21.11,17.10,29.54,14.23,3.41,9.04,0.00,0.17,1.2 1,0.00,2.84,0.00,0.25,0.25,0.85
Russian_Ryazan:Rrzs-88,21.53,16.39,24.53,21.44,3.96,4.56,1.92,1.70,0.4 8,0.22,2.17,0.15,0.95,0.00,0.00
Russian_Smolensk:Rsm-103,15.42,17.04,33.08,21.10,5.60,1.64,1.54,1.19,3. 09,0.00,0.21,0.09,0.00,0.00,0.00
Russian_Smolensk:Rsm-109,17.96,16.25,32.23,21.68,6.88,3.49,0.31,0.00,0. 00,0.17,0.62,0.00,0.21,0.22,0.00
Russian_Smolensk:Rsm-166,14.64,21.86,32.80,18.34,2.19,6.54,1.93,0.00,1. 60,0.00,0.00,0.08,0.02,0.00,0.00
Russian_Smolensk:Rsm-171,16.92,19.50,31.27,21.61,5.46,0.00,2.33,0.05,0. 76,0.85,0.00,0.00,0.64,0.61,0.00
Russian_Smolensk:Rsm-176,18.07,10.78,32.26,21.80,4.92,3.28,5.43,0.00,1. 55,0.00,0.00,0.75,0.00,1.15,0.00
Russian_Smolensk:Rsm-179,21.10,14.18,29.05,22.09,3.53,4.18,3.26,0.75,0. 37,0.41,0.00,0.00,0.39,0.16,0.52
Russian_Smolensk:Rsm-181,19.30,13.44,32.97,20.24,5.86,4.06,1.23,0.00,0. 00,0.00,0.00,0.76,0.48,0.00,1.67
Russian_Tver:Rksh-402,18.41,17.73,27.79,23.75,2.74,3.02,0.00,0.00,1. 66,0.00,3.28,1.51,0.13,0.00,0.00
Russian_Tver:Rksh-405,16.07,14.08,27.50,23.45,6.67,5.93,1.61,1.59,0. 00,0.14,1.40,1.55,0.00,0.00,0.00
Russian_Tver:Rksh-407,17.83,15.53,27.92,24.17,4.25,2.61,0.00,0.04,1. 06,0.00,4.31,0.62,0.00,1.66,0.00
Russian_Tver:Rksh-412,18.01,9.78,38.28,19.26,5.07,3.15,3.09,0.00,0.9 9,0.00,1.59,0.19,0.00,0.00,0.60
Russian_Yaroslavl:RYAR-173,22.36,11.77,32.76,22.72,5.47,0.00,0.00,0.00,0. 00,0.00,2.43,1.22,0.40,0.32,0.55
Russian_Yaroslavl:RYAR-223,16.85,15.06,30.89,25.81,5.02,0.04,0.00,0.00,0. 00,0.00,3.20,1.49,0.00,1.63,0.00
Russian_Yaroslavl:RYAR-232,22.88,11.91,28.92,22.35,4.64,5.07,0.00,0.00,0. 81,0.00,0.95,1.36,1.11,0.00,0.00

#K12b
Bashkir_Central:BAS-091,7.49,21.46,0.52,0.11,8.99,33.59,2.27,0.04,1.16 ,15.01,9.27,0.10
Bashkir_Central:BAS-094,8.49,15.65,1.27,2.27,12.55,38.79,0.38,0.00,2.2 4,8.77,9.34,0.25
Bashkir_Central:BAS-096,9.31,21.72,0.00,0.24,10.10,35.32,1.53,0.00,1.2 7,11.75,8.77,0.00
Bashkir_Central:BAS-105,4.42,12.46,1.02,0.00,14.52,44.20,0.31,0.76,2.2 9,6.42,13.22,0.39
Bashkir_Central:BAS-111,9.96,17.22,0.00,1.59,10.92,39.36,0.00,0.00,0.8 3,7.25,12.19,0.68
Bashkir_Central:BAS-120,10.88,18.97,0.00,0.00,9.53,30.68,2.10,0.00,1.6 0,15.28,10.77,0.19
Bashkir_Central:BAS-121,8.30,17.54,0.00,2.33,8.84,39.79,0.76,0.00,2.13 ,8.32,11.55,0.44
Bashkir_Central:BAS-125,8.60,20.04,0.11,1.70,14.05,37.16,2.04,0.00,2.1 7,7.33,6.81,0.00
Bashkir_Central:BAS-135,8.47,19.86,0.00,0.00,12.73,35.28,3.14,0.86,0.0 0,14.01,5.66,0.00
Bashkir_Central:BAS-600,7.93,21.28,0.00,1.43,7.68,34.18,2.24,0.00,0.00 ,14.98,9.44,0.84
Bashkir_Central:BAS-622,9.13,18.95,1.71,1.78,10.70,33.21,0.00,0.00,3.8 7,13.77,6.87,0.00
Bashkir_Central:BAS-655,8.65,20.56,2.66,0.00,8.71,36.38,1.64,0.00,0.00 ,11.57,9.84,0.00
Bashkir_Central:BAS-661,11.64,21.40,0.00,1.30,9.41,38.35,0.44,0.00,0.0 0,8.46,9.00,0.00
Bashkir_Central:BAS-663,12.19,19.72,0.00,0.99,8.24,39.49,1.69,0.00,1.6 1,10.61,5.46,0.00
Bashkir_Central:BAS-669,8.75,17.25,0.00,0.00,11.32,41.66,0.00,0.00,0.2 6,10.19,10.57,0.00
Bashkir_Central:BAS-672,11.04,17.29,0.00,1.74,14.03,38.76,0.48,0.00,1. 69,9.90,5.07,0.00
Bashkir_Central:BAS-1392,5.29,13.87,0.00,3.34,10.31,43.91,3.78,0.00,0. 00,3.99,15.23,0.28
Bashkir_Central:BAS-1393,10.91,16.79,0.00,1.24,12.68,39.13,2.69,0.00,1 .57,5.33,9.67,0.00
Bashkir_Central:BAS-1394,8.04,15.86,0.86,0.22,10.42,37.76,2.75,0.30,2. 96,7.80,13.03,0.00
Bashkir_Central:BAS-1396,11.40,14.70,0.00,0.00,11.96,38.92,2.51,0.28,4 .27,8.74,7.21,0.00
Bashkir_Central:BAS-1398,8.03,17.97,0.00,0.00,11.47,43.81,0.59,0.00,0. 75,6.42,10.95,0.00
Bashkir_Central:BAS-1400,8.28,22.21,0.00,0.72,13.44,39.05,1.50,0.00,1. 19,5.09,8.52,0.00
Bashkir_North:BAS-652,10.10,19.59,0.00,0.06,12.11,37.97,3.22,0.00,0. 16,10.30,6.48,0.00
Bashkir_North:BAS-670,7.45,17.58,0.00,0.00,11.49,40.53,0.70,0.00,0.0 0,12.38,9.87,0.00
Bashkir_North:BAS-671,10.17,19.08,0.00,0.00,7.57,44.04,2.94,0.00,0.5 7,8.51,6.98,0.14
Bashkir_North:BAS-683,8.09,16.48,0.00,0.00,9.94,38.68,0.00,0.00,0.01 ,12.44,14.36,0.00
Bashkir_North:BAS-811,10.77,16.51,0.00,0.00,14.66,42.48,0.00,0.00,0. 57,5.60,7.52,1.89
Bashkir_North:BAS-813,6.06,14.98,2.48,0.00,11.99,44.09,1.15,0.00,0.6 3,6.58,12.04,0.00
Bashkir_North:BAS-822,7.76,18.15,0.00,0.00,13.75,40.20,2.94,0.26,0.9 4,6.79,9.20,0.00
Bashkir_North:BAS-825,9.46,17.56,0.00,2.29,7.69,41.81,2.67,0.00,2.42 ,4.60,11.16,0.33
Bashkir_North:BAS-831,4.40,15.14,0.00,3.30,11.10,47.53,3.42,0.00,0.6 9,4.25,10.17,0.00
Bashkir_North:BAS-833,8.21,17.98,0.00,0.56,11.45,42.81,2.30,0.00,0.0 0,6.02,10.67,0.00
Bashkir_North:BAS-834,7.63,17.51,0.00,1.98,13.86,40.42,3.06,0.10,0.0 0,5.05,10.09,0.29
Bashkir_North:BAS-849,10.42,19.88,0.14,0.00,14.63,38.57,0.91,0.00,0. 31,7.43,7.35,0.36
Bashkir_South:BAS-005,11.53,24.17,0.00,0.00,7.39,31.70,2.41,0.00,0.1 8,17.49,5.12,0.00
Bashkir_South:BAS-006,12.93,25.82,0.00,1.60,4.46,26.27,1.91,0.24,3.8 1,13.97,8.97,0.00
Bashkir_South:BAS-008,10.09,26.54,0.00,0.16,7.33,28.27,2.05,0.14,0.0 0,16.35,8.60,0.47
Bashkir_South:BAS-014,8.68,25.52,1.04,0.00,9.00,30.61,3.39,0.00,0.09 ,14.53,7.15,0.00
Bashkir_South:BAS-017,11.31,24.29,0.00,0.00,6.40,27.82,3.05,0.00,2.0 2,16.91,8.03,0.17
Bashkir_South:BAS-021,11.77,23.10,0.00,1.29,8.24,27.99,3.16,0.59,0.0 0,16.77,6.75,0.35
Bashkir_South:BAS-029,15.73,23.67,0.00,1.90,4.96,32.54,2.82,0.00,0.5 4,13.48,4.30,0.06
Bashkir_South:BAS-031,9.62,23.80,1.81,0.09,4.06,29.75,1.21,0.00,0.00 ,21.11,8.54,0.00
Bashkir_South:BAS-033,12.96,25.90,0.00,0.67,8.83,24.54,1.67,0.00,0.0 0,16.24,9.19,0.00
Bashkir_South:BAS-034,11.25,23.97,0.00,1.23,6.56,28.24,2.41,0.82,0.0 0,17.79,7.71,0.00
Bashkir_South:BAS-042,11.76,26.64,2.02,1.88,9.02,30.75,2.51,0.00,0.0 0,12.35,3.07,0.00
Bashkir_South:BAS-045,11.46,23.43,0.00,2.37,9.95,25.32,1.09,0.00,0.0 0,16.58,9.53,0.28
Bashkir_South:BAS-046,8.58,23.90,0.24,0.00,7.31,30.44,0.45,0.00,0.00 ,16.31,12.75,0.00
Bashkir_South:BAS-060,10.06,24.24,0.95,0.00,4.82,31.27,1.87,0.00,0.2 3,18.13,8.24,0.18
Bashkir_South:BAS-062,11.69,24.62,0.00,0.00,8.11,30.54,0.00,0.00,0.0 0,17.48,7.46,0.12
Bashkir_South:BAS-150,8.77,22.28,0.00,5.36,8.65,28.04,0.00,0.56,0.48 ,12.47,13.07,0.30
Bashkir_South:BAS-153,12.87,21.21,0.68,0.96,9.47,30.16,2.47,0.00,0.7 4,13.06,7.66,0.72
Bashkir_South:BAS-156,8.58,25.36,0.00,1.17,5.13,34.69,2.21,0.00,0.89 ,13.89,7.86,0.22
Bashkir_South:BAS-164,10.79,20.76,0.00,4.18,12.39,32.03,0.00,0.00,0. 00,13.99,5.86,0.00
Russian_Arkhangelsk_Krasnoborsky:Rakr-203,6.97,5.53,0.00,1.65,17.48,60.12,0.39,0.00,0.71 ,2.78,4.39,0.00
Russian_Arkhangelsk_Krasnoborsky:Rakr-205,3.97,4.98,0.39,0.00,17.53,56.57,0.30,0.02,1.49 ,3.70,11.06,0.00
Russian_Arkhangelsk_Krasnoborsky:Rakr-237,3.06,7.82,0.00,0.00,20.37,57.51,0.10,0.00,0.47 ,1.86,8.80,0.00
Russian_Arkhangelsk_Krasnoborsky:Rakr-248,5.44,8.42,0.00,0.00,18.36,60.97,1.97,0.00,0.58 ,0.00,4.25,0.00
Russian_Arkhangelsk_Krasnoborsky:Rakr-341,3.94,9.77,0.00,0.00,19.81,60.20,1.31,0.00,0.00 ,0.78,4.19,0.00
Russian_Arkhangelsk_Krasnoborsky:Rakr-345,5.23,7.98,1.18,0.04,19.28,59.08,0.08,0.00,0.00 ,0.50,6.63,0.00
Russian_Arkhangelsk_Leshukonsky:Rakrlsh-002,7.72,11.44,0.00,0.75,11.20,60.96,0.75,0.00,2.1 1,2.41,2.66,0.00
Russian_Arkhangelsk_Leshukonsky:Rakrlsh-140,2.70,12.25,0.00,0.49,16.52,58.01,0.77,0.95,0.1 5,3.43,4.74,0.00
Russian_Arkhangelsk_Leshukonsky:Rakrlsh-143,3.71,13.66,0.00,1.24,10.95,57.87,1.43,0.61,1.1 7,0.00,9.21,0.15
Russian_Arkhangelsk_Leshukonsky:Rakrlsh-144,6.05,14.94,0.00,0.00,9.67,63.54,0.73,0.41,0.00 ,0.31,4.34,0.00
Russian_Arkhangelsk_Leshukonsky:Rakrlsh-149,5.17,9.74,1.41,1.53,12.26,58.94,1.25,0.00,2.79 ,0.85,6.06,0.00
Russian_Arkhangelsk_Pinezhsky:RPin-114,4.60,8.21,0.00,1.46,17.65,63.21,0.00,0.80,0.00 ,0.84,3.11,0.12
Russian_Arkhangelsk_Pinezhsky:RPin-123,4.83,10.39,1.71,0.00,17.29,61.79,2.27,0.00,0.0 1,0.00,1.70,0.00
Russian_Arkhangelsk_Pinezhsky:RPin-143,5.57,9.29,0.00,1.57,14.06,61.57,0.49,0.00,0.00 ,0.03,7.42,0.00
Russian_Arkhangelsk_Pinezhsky:RPin-145,0.00,9.23,0.51,0.53,12.08,64.01,2.02,0.00,1.63 ,1.04,7.94,1.01
Russian_Arkhangelsk_Pinezhsky:RPin-151,5.03,10.42,0.00,0.04,16.21,63.80,1.54,0.59,0.0 0,0.99,1.36,0.00
Russian_Belgorod:Rbgp-200,3.90,2.33,0.00,0.00,22.05,57.21,0.00,0.00,2.15 ,0.92,11.45,0.00
Russian_Belgorod:Rbgp-201,2.49,2.39,0.42,0.28,19.96,57.88,0.48,0.00,1.03 ,0.00,14.90,0.16
Russian_Belgorod:Rbgp-205,1.45,0.65,0.00,0.29,20.22,60.06,2.01,0.00,2.67 ,0.42,12.22,0.00
Russian_Kaluga:Rkbo-12,2.46,0.89,0.26,0.66,19.97,60.37,1.29,0.00,3.89, 0.00,10.21,0.00
Russian_Kaluga:Rkbo-16,1.69,3.74,0.00,0.85,17.51,57.08,0.57,0.00,1.75, 0.19,16.62,0.00
Russian_Kaluga:Rkbo-58,1.40,1.71,0.29,0.00,19.51,63.58,0.00,0.00,1.36, 0.00,12.15,0.00
Russian_Kursk:Rkuch-03,1.27,2.81,0.00,0.00,17.36,61.16,0.00,0.30,4.65, 0.00,12.44,0.00
Russian_Kursk:Rkuch-05,3.34,1.06,0.00,0.00,20.83,60.01,0.10,0.00,1.26, 1.66,11.73,0.00
Russian_Kursk:Rkuch-53,4.14,1.78,0.01,1.08,19.35,55.05,0.50,0.00,0.01, 0.00,17.79,0.30
Russian_Kursk:Rkuch-58,4.49,0.64,0.00,0.02,20.31,57.41,4.39,0.00,1.81, 0.00,10.63,0.30
Russian_Orel:Rorl-102,5.78,4.60,0.00,0.00,16.00,56.49,1.29,0.40,1.22 ,1.98,12.25,0.00
Russian_Orel:Rorl-110,3.43,0.00,0.00,0.86,18.82,58.16,1.62,1.16,0.05 ,0.00,15.90,0.00
Russian_Orel:Rorl-114,2.50,2.53,1.86,0.00,21.91,53.07,0.92,0.00,2.13 ,0.00,15.07,0.00
Russian_Orel:Rorl-155,2.84,1.40,0.00,0.00,20.80,56.69,2.21,0.00,0.99 ,0.55,14.05,0.48
Russian_Pskov:Rps-002,2.01,2.25,0.00,0.00,18.79,60.71,1.35,0.28,1.19 ,0.00,12.76,0.65
Russian_Pskov:Rps-004,3.28,0.00,0.00,0.00,18.20,66.84,2.22,0.00,3.40 ,0.00,6.06,0.00
Russian_Pskov:Rps-012,1.58,2.08,0.24,0.97,22.99,63.38,0.01,0.00,0.93 ,0.00,7.81,0.00
Russian_Pskov:Rps-090,3.29,2.68,0.00,0.76,23.42,62.50,0.00,0.00,0.00 ,0.04,6.23,1.06
Russian_Pskov:Rps-091,3.02,2.15,0.00,0.79,19.79,59.66,0.00,0.00,4.04 ,0.00,10.55,0.00
Russian_Pskov:Rps-098,2.91,2.52,0.00,0.00,20.43,59.08,1.78,0.00,0.12 ,0.00,12.85,0.31
Russian_Ryazan:Rrzm-08,2.32,3.69,0.00,0.00,20.15,56.30,0.22,0.00,2.14, 0.03,14.89,0.26
Russian_Ryazan:Rrzm-10,0.31,3.13,1.83,0.17,19.92,57.31,0.22,0.87,1.20, 0.00,14.43,0.60
Russian_Ryazan:Rrzm-13,4.85,5.09,0.72,0.00,18.30,57.60,0.09,0.00,0.83, 1.01,11.51,0.00
Russian_Ryazan:Rrzm-16,7.20,2.34,0.00,0.12,21.81,53.59,2.73,0.00,0.47, 0.00,11.73,0.00
Russian_Ryazan:Rrzm-83,6.92,2.26,0.19,0.20,18.69,57.12,0.23,0.00,0.00, 0.18,14.21,0.00
Russian_Ryazan:Rrzs-3,2.71,3.82,0.00,0.00,22.52,58.33,1.27,0.00,0.65,0 .00,10.70,0.00
Russian_Ryazan:Rrzs-7,6.76,2.54,0.07,0.00,18.71,56.78,1.19,0.00,0.37,1 .80,11.79,0.00
Russian_Ryazan:Rrzs-11,6.39,4.55,0.00,0.00,24.11,55.69,1.32,0.00,0.00, 0.00,7.94,0.00
Russian_Ryazan:Rrzs-32,4.44,3.33,0.29,0.00,21.60,59.99,0.48,0.00,0.80, 0.00,9.06,0.00
Russian_Ryazan:Rrzs-58,3.34,2.91,0.76,0.53,17.51,58.45,1.41,0.00,0.53, 0.00,14.56,0.00
Russian_Ryazan:Rrzs-66,5.10,3.30,0.00,0.00,22.21,54.98,1.45,0.71,0.00, 0.66,11.59,0.00
Russian_Smolensk:Rsm-103,2.22,2.51,0.00,0.00,21.90,58.05,0.53,0.00,2.32 ,0.00,11.83,0.64
Russian_Smolensk:Rsm-109,4.75,1.43,0.43,0.00,24.19,57.95,0.00,0.00,0.00 ,0.00,11.25,0.00
Russian_Smolensk:Rsm-166,9.22,1.97,0.00,0.00,22.24,54.56,0.07,0.42,0.13 ,0.00,11.40,0.00
Russian_Smolensk:Rsm-171,3.26,0.77,0.00,1.89,22.57,59.16,0.59,0.00,1.16 ,0.00,10.60,0.00
Russian_Smolensk:Rsm-176,6.44,0.41,0.00,0.36,21.38,54.07,1.36,0.34,3.98 ,0.00,11.66,0.00
Russian_Smolensk:Rsm-179,5.35,2.32,0.00,0.00,21.38,58.04,0.46,0.14,2.57 ,0.00,9.73,0.00
Russian_Smolensk:Rsm-181,0.00,0.00,1.34,2.06,20.27,58.68,2.18,0.00,0.34 ,0.00,14.95,0.19
Russian_Tver:Rksh-402,5.54,4.45,0.00,1.45,19.68,57.35,1.48,0.00,0.00 ,0.00,9.69,0.37
Russian_Tver:Rksh-405,2.45,4.08,0.39,0.03,18.02,55.36,0.00,0.00,4.45 ,0.00,14.74,0.45
Russian_Tver:Rksh-407,4.58,3.63,4.36,0.00,18.28,56.77,0.06,0.00,0.00 ,1.87,9.88,0.57
Russian_Tver:Rksh-412,3.23,2.90,0.00,0.00,21.45,59.62,0.06,0.00,2.38 ,0.00,10.36,0.00
Russian_Vologda:HGDP00879,3.58,9.15,0.00,0.00,11.7 1,66.78,0.04,0.00,1.63,0.00,7.11,0.00
Russian_Vologda:HGDP00880,7.65,7.68,0.00,2.49,16.6 1,57.47,0.00,0.00,1.23,0.00,6.86,0.00
Russian_Vologda:HGDP00882,5.23,6.14,0.14,0.19,18.9 4,57.86,2.06,0.00,3.50,1.72,4.21,0.00
Russian_Vologda:HGDP00883,3.27,7.36,0.00,0.00,12.8 6,66.26,0.03,0.00,0.08,1.47,8.66,0.00
Russian_Vologda:HGDP00884,2.50,5.99,0.00,0.00,14.9 9,64.53,2.86,0.00,2.08,0.00,7.05,0.00
Russian_Vologda:HGDP00887,2.17,7.59,0.00,0.00,18.8 1,61.41,0.00,0.32,2.20,0.98,6.53,0.00
Russian_Vologda:HGDP00888,3.96,6.96,0.00,0.00,14.1 3,62.43,0.60,0.00,3.09,0.00,8.82,0.00
Russian_Vologda:HGDP00889,0.00,6.34,0.00,0.00,14.0 6,66.17,1.26,0.00,0.92,0.46,10.79,0.00
Russian_Vologda:HGDP00890,1.59,8.04,0.03,0.77,16.4 0,63.94,1.15,0.00,0.00,0.00,8.07,0.00
Russian_Vologda:HGDP00891,1.24,5.19,0.00,0.00,10.6 1,64.08,0.48,0.00,2.54,3.98,11.89,0.00
Russian_Vologda:HGDP00892,3.02,6.68,0.00,0.00,10.8 8,69.65,0.78,0.00,1.20,0.00,7.78,0.00
Russian_Vologda:HGDP00893,0.82,10.94,0.43,0.00,11. 98,64.02,0.43,0.00,0.00,1.16,10.23,0.00
Russian_Vologda:HGDP00894,6.91,9.68,1.74,0.00,17.2 6,58.00,0.00,0.00,0.00,0.00,6.41,0.00
Russian_Vologda:HGDP00895,5.85,8.59,0.00,0.00,12.9 8,64.78,1.54,0.31,0.00,2.02,3.94,0.00
Russian_Vologda:HGDP00896,2.52,8.30,0.00,0.00,11.8 8,64.70,1.13,0.00,3.08,1.04,7.35,0.00
Russian_Vologda:HGDP00897,0.00,6.15,0.00,2.31,10.3 1,65.74,1.59,0.00,3.60,0.00,10.31,0.00
Russian_Vologda:HGDP00898,3.71,8.75,0.27,0.41,11.6 0,65.90,1.86,0.00,0.00,0.00,7.51,0.00
Russian_Vologda:HGDP00899,5.20,6.46,0.00,1.01,18.8 6,55.98,0.00,0.16,0.93,1.43,9.86,0.11
Russian_Vologda:HGDP00900,1.22,4.47,0.57,0.66,11.3 8,64.96,2.92,0.00,1.84,0.00,11.98,0.00
Russian_Vologda:HGDP00901,2.41,8.53,0.00,0.34,18.0 0,59.45,0.00,0.00,0.40,0.80,10.08,0.00
Russian_Vologda:HGDP00902,4.07,6.46,1.11,0.00,12.2 6,64.29,2.13,0.00,0.00,0.98,8.69,0.00
Russian_Vologda:HGDP00903,0.26,7.01,0.00,0.79,12.5 5,62.41,0.00,0.00,2.63,0.90,13.46,0.00
Russian_Yaroslavl:RYAR-173,3.88,3.61,2.46,0.00,20.60,59.38,0.00,0.00,0.32 ,0.59,9.15,0.00
Russian_Yaroslavl:RYAR-223,1.33,5.01,0.22,0.00,18.21,60.78,0.26,0.45,1.56 ,1.38,10.81,0.00
Russian_Yaroslavl:RYAR-232,4.87,3.47,0.00,0.00,21.18,59.83,1.88,0.03,0.00 ,0.00,8.73,0.00

K12b updated already has Bashkirs divided under Bashkir_North, Bashkir_Central, and Bashkir_South, but it might use a different division than my samples, because I divided the samples based on their latitude rounded to the nearest integer: 53 for South, 55 for Central, and 56 for North.

I omitted the samples from Vologda from K13, because some of them got over 60% Baltic, and two samples from Vologda and one sample from Pskov even got over 99.5% Baltic. I also omitted the samples from Vologda from K15, because some of them got over 90% Eastern_Euro. And I omitted 4 Russian samples from K12b, because they got over 90% North_European.

Here's a PLINK PCA of the same samples:

https://i.ibb.co/xJKNXtm/bashkir-russian.png

I ran these which were missing in your sheet:

Oh, I figured out why they were missing. I ran the samples in two batches. In the second batch, I omitted samples where my target directory already had a file with the same basename without extension as the sample, but the target directory only had PLINK log files for the samples and not 23andme raw data files.

Leto

10-25-2021, 09:14 PM

The Vologda samples were in the original Dodecad spreadsheet too.

I made the Bashkir averages but the North-Center-South division was made according to the disticts the samples were taken from.

Leto

10-25-2021, 09:17 PM

Too fucking bad you cannot convert data to G25 format. xD Literally no one wants to convert the Tajiks and Kumyks from Yunusbayev. What a fucking pity!

Lucas

10-26-2021, 09:51 AM

In the PCA below, the outliers in the top left corner of the plot got something like 99.5% or 99.7% of Baltic. I don't know if it's because they were used as reference samples in K13. LTG-356 is an outlier because it only got 21.48% North_Atlantic, 74.47% Baltic, and 4.05% West_Med, and 0% all other components. LTG-441 is closest to Russian_Kargopol and LTG-566 is closest to Russian_average.
.

I said it before. During such big runs always few random samples have strange results like this. Try to check them again separately, should be normal. And I am sure they are not references in old K13 it was different survey so it is not calc effect.

BTW Vologda Russians are references everywhere so they are score those high values for real unlike those new Lithuanians.

Komintasavalta

10-26-2021, 11:46 AM

I said it before. During such big runs always few random samples have strange results like this. Try to check them again separately, should be normal. And I am sure they are not references in old K13 it was different survey so it is not calc effect.

BTW Vologda Russians are references everywhere so they are score those high values for real unlike those new Lithuanians.

Actually I think you need to make the tolerance parameter (`-t`) smaller (https://github.com/stevenliuyi/admix#faq):

This package utilizes the optimization function `scipy.optimize.minimize` from the SciPy library, which has a parameter `tol` to control the tolerance for termination of the optimizer. The default tolerance is set to `1e-3` here. It works most of time, but sometimes `1e-3` is too big and causes early termination. You can manually set a smaller tolerance (say `1e-4`) to obtain correct results, although it will take longer to run the optimizer.

michal3141 also got the wrong results in K36 by using the default threshold, and he said that "probably e-7 or at least e-6 is the way to go": https://anthrogenica.com/showthread.php?25056-Has-anyone-tried-this-program&p=810669&viewfull=1#post810669.

When I tried doing another run of one of the samples from Vologda that got over 99% Baltic (HGDP00899), it first got the same results, because the algorithm doesn't use a random seed like ADMIXTURE, but it gives the same result each time. After I decreased the tolerance to 1e-4, the results started to resemble other samples from Vologda. Between 1e-4 and 1e-5, some admixture proportions still changed by more than 0.3 percentage points, but there was no further change between 1e-5 and 1e-6:

~ admix -f a.txt -mK13

Admixture calculation models: K13

Calcuation is started...

K13
North_Atlantic: 0.12%
Baltic: 99.76%
West_Med: 0.00%
West_Asian: 0.00%
East_Med: 0.00%
Red_Sea: 0.00%
South_Asian: 0.00%
East_Asian: 0.00%
Siberian: 0.07%
Amerindian: 0.00%
Oceanian: 0.05%
Northeast_African: 0.00%
Sub-Saharan: 0.00%

~ admix -f a.txt -mK13 -t1e-4

Admixture calculation models: K13

Calcuation is started...

K13
North_Atlantic: 3.95%
Baltic: 71.60%
West_Med: 5.06%
West_Asian: 2.74%
East_Med: 6.62%
Red_Sea: 0.67%
South_Asian: 0.00%
East_Asian: 0.16%
Siberian: 6.24%
Amerindian: 1.26%
Oceanian: 1.31%
Northeast_African: 0.04%
Sub-Saharan: 0.36%

~ admix -f a.txt -mK13 -t1e-5

Admixture calculation models: K13

Calcuation is started...

K13
North_Atlantic: 4.09%
Baltic: 71.69%
West_Med: 4.73%
West_Asian: 2.64%
East_Med: 6.46%
Red_Sea: 0.91%
South_Asian: 0.00%
East_Asian: 0.11%
Siberian: 6.05%
Amerindian: 1.37%
Oceanian: 1.55%
Northeast_African: 0.03%
Sub-Saharan: 0.36%

~ admix -f a.txt -mK13 -t1e-6

Admixture calculation models: K13

Calcuation is started...

K13
North_Atlantic: 4.09%
Baltic: 71.69%
West_Med: 4.73%
West_Asian: 2.64%
East_Med: 6.46%
Red_Sea: 0.91%
South_Asian: 0.00%
East_Asian: 0.11%
Siberian: 6.05%
Amerindian: 1.37%
Oceanian: 1.55%
Northeast_African: 0.03%
Sub-Saharan: 0.36%

I ran K13 at different tolerance parameters for all 87 samples from the Reich dataset with the population name "Russian", because they included some problematic samples in my earlier K13 run. Now the average difference in the admixture percentages became less than 0.01 between 1e-4 and 1e-5, and less than 0.0001 between 1e-5 and 1e-6:

ToleranceAverage difference in admixture percentages
compared to previous toleranceRunning time
per sample
1e-1-1.22
1e-23.1448101.65
1e-33.5153493.12
1e-40.3167373.47
1e-50.0023873.64
1e-60.0000973.51
1e-70.0000623.65
1e-80.0000883.65

So it's probably better to change the tolerance to at least 1e-5, even though in this case even 1e-8 was about as fast.

Lucas

10-26-2021, 12:05 PM

Leto

10-26-2021, 12:58 PM

Hey Komin, what is Komi_Siberia? Another mixed group?

Target: Komi_Siberian
Distance: 0.3028% / 0.30276589 | R3P
51.6 Khanty
37.3 North_Russian
11.1 Russian_Oryol

Looks like a biracial Khanty-Russian mix :D The two principal Komi subgroups, the Zyryans and the Permyaks all live west of the Urals.

Komintasavalta

10-26-2021, 01:38 PM

Yes, you are right indeed. Must be this causing problems sometimes. In original calc files for all calculators in .par file is by default used 1d-7 parameter (not 1e). Now is evident it makes sense.

I'll start to use 1e-7 too then. DIYDodecad was made with Fortran, and 1d-7 is Fortran syntax for specifying a double.

Here's fixed averages made with `-t 1e-7`. I now also excluded one Tofalar sample with high Caucasoid ancestry. I omitted 19 out of 22 samples from Vologda from K13 because they scored over 60% Baltic, and most even scored over 70%, but the few samples from Vologda that didn't suffer from the calculator effect only got 49% Baltic on average. I also omitted the same samples from Vologda from K15.

#K13, Reich
Bashkir_Central,15.64,31.88,3.15,12.27,3.05,0.74,3 .52,5.41,21.15,2.23,0.36,0.23,0.37
Bashkir_North,17.00,34.88,3.73,10.73,2.31,0.60,3.8 5,4.42,19.45,1.86,0.59,0.23,0.37
Bashkir_South,12.75,24.85,1.26,13.47,1.15,0.30,4.2 0,9.62,28.69,2.98,0.34,0.17,0.22
Russian_Archangelsk_Krasnoborsky,28.17,47.65,5.02, 4.22,1.93,0.57,2.25,0.85,7.70,0.93,0.45,0.25,0.00
Russian_Archangelsk_Leshukonsky,25.10,48.98,2.02,4 .35,0.93,0.41,1.43,0.29,12.83,1.83,0.76,0.53,0.54
Russian_Archangelsk_Pinezhsky,26.34,51.18,3.49,2.8 5,0.91,0.16,2.27,0.33,9.33,1.84,0.55,0.57,0.20
Russian_Belgorod,23.61,47.87,11.19,5.60,6.10,1.40, 0.36,0.49,2.03,0.53,0.47,0.34,0.00
Russian_Kaluga,28.40,48.45,6.76,4.02,5.78,1.72,1.1 0,0.00,2.06,1.16,0.24,0.00,0.34
Russian_Kursk,26.60,47.80,7.64,4.88,7.31,0.35,0.92 ,0.74,1.90,0.91,0.37,0.41,0.18
Russian_Orel,27.62,44.88,8.10,6.22,6.20,1.00,1.26, 0.69,2.34,0.84,0.16,0.35,0.33
Russian_Pskov,26.08,52.91,7.78,5.09,1.91,1.44,0.50 ,0.00,1.89,0.84,0.53,0.48,0.56
Russian_Ryazan,25.00,47.16,8.76,7.31,4.37,0.59,1.4 8,0.37,2.78,1.05,0.36,0.53,0.24
Russian_Smolensk,26.24,48.27,9.35,4.46,6.54,0.41,1 .56,0.65,0.70,0.63,0.42,0.40,0.37
Russian_Tver,24.04,49.02,9.38,6.68,2.17,1.20,1.42, 0.16,3.91,1.26,0.14,0.52,0.11
Russian_Vologda,24.60,49.08,7.98,3.85,1.74,0.00,3. 08,0.00,6.61,2.00,0.16,0.17,0.74
Russian_Yaroslavl,26.40,50.28,9.30,4.97,0.55,0.69, 0.62,0.00,3.72,1.64,0.71,0.88,0.23
Aleut,15.27,35.26,3.11,4.56,1.59,0.43,1.38,3.07,17 .01,17.26,0.51,0.19,0.33
Enets,4.66,15.37,0.28,0.91,0.00,0.37,1.70,1.02,70. 19,4.12,0.69,0.00,0.69
Itelmen,0.00,4.38,0.00,0.00,0.00,0.00,1.82,12.25,6 2.76,17.18,1.06,0.00,0.54
Kalmyk,2.55,5.75,0.80,6.78,1.15,0.36,0.84,30.85,48 .42,1.56,0.55,0.06,0.36
Karelian,30.33,50.92,4.10,1.41,0.82,0.68,1.40,0.26 ,7.58,1.28,0.58,0.49,0.16
Kusunda,0.97,0.00,0.89,3.37,0.00,0.00,31.42,40.74, 18.24,0.87,2.46,0.71,0.35
Mansi,8.40,30.52,0.00,4.71,0.00,0.00,4.25,1.90,43. 88,5.29,0.76,0.15,0.13
Nasioi,0.07,0.51,0.33,0.00,0.17,0.20,4.46,21.25,0. 22,0.23,72.25,0.04,0.29
Newar,1.05,2.41,1.13,9.15,0.30,0.64,37.11,30.97,14 .65,0.99,1.01,0.09,0.51
Nganasan,0.00,2.97,0.00,0.00,0.03,0.01,0.43,0.41,9 3.88,1.75,0.22,0.03,0.26
Nogai_Astrakhan,9.15,14.62,4.35,11.10,4.02,1.04,1. 57,19.77,31.69,1.61,0.72,0.20,0.16
Nogai_Karachay_Cherkessia,4.75,15.83,7.60,37.42,5. 82,1.30,1.51,8.53,14.96,0.96,0.68,0.57,0.06
Nogai_Stavropol,9.78,13.60,3.46,17.20,4.09,0.77,3. 39,17.33,27.75,1.39,0.81,0.13,0.29
Tatar_Mishar,22.05,36.75,6.64,10.80,3.49,0.56,2.66 ,4.01,11.19,1.26,0.12,0.15,0.33
Tatar_Siberian,11.36,22.66,0.76,12.78,1.02,0.76,3. 86,10.60,31.58,3.63,0.42,0.19,0.37
Tatar_Siberian_Zabolotniye,8.03,28.55,0.00,9.07,0. 00,0.00,4.27,6.27,39.17,3.73,0.43,0.08,0.40
Thai,0.69,1.99,0.91,0.76,0.59,0.70,15.28,72.43,3.1 9,0.82,2.25,0.19,0.19
Tharu,0.69,1.48,1.94,7.63,0.11,0.02,37.16,32.53,15 .52,0.88,1.77,0.14,0.12
Tlingit,10.18,25.66,0.88,4.12,0.12,0.00,1.81,4.69, 24.46,26.98,0.14,0.45,0.52
Todzin,0.00,8.49,0.23,1.52,0.00,0.22,3.29,13.04,69 .15,3.40,0.54,0.00,0.12
Tofalar,0.07,8.03,0.09,1.43,0.00,0.35,1.28,12.84,7 1.34,3.49,0.94,0.10,0.04
Ulchi,0.00,0.06,0.07,0.00,0.00,0.03,0.13,31.83,64. 44,2.97,0.32,0.09,0.07
Veps,27.02,52.08,3.78,1.59,0.97,1.23,1.62,0.17,8.9 9,1.44,0.60,0.19,0.32
Yukagir_Forest,13.18,28.14,3.71,1.11,3.10,0.61,1.4 6,4.39,40.97,2.04,0.34,0.39,0.56
Yukagir_Tundra,0.00,2.99,0.00,0.12,0.01,0.10,1.05, 8.37,78.20,8.07,0.64,0.08,0.37

#K13, Cardona 2014
Altaian_Teleut,6.62,15.20,0.00,8.71,0.00,0.22,2.51 ,19.65,42.29,3.61,0.63,0.35,0.20
Forest_Nenets,1.66,19.86,0.00,1.48,0.00,0.01,3.26, 1.00,66.86,5.05,0.55,0.02,0.26
Komi_Siberian,17.18,40.27,2.10,5.42,0.35,0.30,2.29 ,1.03,27.39,2.96,0.38,0.13,0.18
Tundra_Nenets,3.23,20.09,0.20,2.18,0.00,0.03,3.44, 1.54,63.99,4.75,0.32,0.10,0.12

#K15, Reich
Bashkir_Central,13.49,7.21,13.69,22.00,1.07,9.26,1 .59,0.51,3.42,5.35,19.72,1.96,0.30,0.15,0.30
Bashkir_North,13.09,8.92,16.01,23.59,1.13,7.65,0.7 1,0.35,3.73,4.30,17.92,1.65,0.44,0.21,0.30
Bashkir_South,10.87,4.87,9.55,19.32,0.29,10.22,0.3 3,0.13,4.28,9.49,27.27,2.83,0.26,0.09,0.20
Russian_Archangelsk_Krasnoborsky,21.90,15.16,26.36 ,23.16,1.27,1.34,0.54,0.26,1.71,0.70,6.31,0.75,0.3 5,0.18,0.00
Russian_Archangelsk_Leshukonsky,21.35,10.89,23.54, 27.21,0.51,0.81,0.12,0.18,1.13,0.10,11.23,1.64,0.6 4,0.28,0.38
Russian_Archangelsk_Pinezhsky,21.02,12.63,24.46,28 .27,1.06,0.66,0.00,0.00,1.49,0.28,7.52,1.73,0.41,0 .38,0.07
Russian_Belgorod,18.05,14.69,30.80,20.34,6.35,4.39 ,2.15,1.01,0.24,0.41,0.58,0.36,0.28,0.37,0.00
Russian_Kaluga,20.85,15.76,31.00,20.91,2.69,3.30,1 .32,1.38,0.86,0.00,0.68,0.92,0.13,0.00,0.20
Russian_Kursk,20.98,13.50,29.60,22.28,3.50,2.94,3. 90,0.06,0.74,0.51,0.79,0.56,0.28,0.11,0.26
Russian_Orel,18.25,17.29,28.84,19.48,3.93,5.58,1.8 5,0.77,0.92,0.28,1.46,0.64,0.15,0.22,0.35
Russian_Pskov,19.25,14.69,33.04,23.83,2.99,2.82,0. 16,0.86,0.08,0.00,0.78,0.49,0.31,0.24,0.45
Russian_Ryazan,19.17,13.56,29.21,21.65,4.56,5.47,1 .63,0.28,1.12,0.27,1.56,0.71,0.22,0.35,0.23
Russian_Smolensk,17.63,16.14,31.97,20.99,4.90,3.33 ,2.30,0.28,1.04,0.20,0.12,0.24,0.25,0.30,0.32
Russian_Tver,17.48,14.68,30.17,22.77,4.72,3.51,1.1 0,0.41,0.99,0.04,2.66,0.95,0.04,0.41,0.06
Russian_Vologda,16.63,15.64,26.89,26.81,3.22,0.92, 0.14,0.00,2.44,0.00,5.02,1.62,0.03,0.00,0.64
Russian_Yaroslavl,20.68,12.86,30.85,23.65,5.09,1.6 9,0.00,0.00,0.27,0.00,2.17,1.39,0.50,0.66,0.19
Aleut,13.39,6.61,19.19,19.15,1.19,2.12,0.57,0.12,1 .23,3.14,15.75,16.78,0.42,0.12,0.22
Enets,3.15,1.82,2.29,15.80,0.14,0.00,0.00,0.10,1.2 0,1.39,69.09,3.80,0.62,0.00,0.59
Itelmen,0.00,0.06,0.10,5.40,0.00,0.00,0.00,0.00,1. 55,12.88,61.69,16.92,0.96,0.00,0.44
Kalmyk,2.00,0.91,1.26,6.42,0.35,5.81,0.96,0.35,0.8 6,31.31,47.32,1.62,0.50,0.05,0.28
Karelian,24.98,15.04,23.60,25.41,1.74,0.26,0.01,0. 08,0.67,0.14,6.18,1.07,0.44,0.28,0.10
Kusunda,0.76,0.16,0.12,0.50,1.02,1.62,0.00,0.00,32 .50,41.52,17.50,0.93,2.46,0.52,0.40
Mansi,9.98,1.12,5.60,28.97,0.00,0.69,0.00,0.00,3.7 6,2.08,42.05,4.93,0.69,0.04,0.09
Nasioi,0.04,0.03,0.69,0.00,0.18,0.00,0.01,0.11,3.9 1,21.82,0.21,0.22,72.52,0.01,0.26
Newar,1.17,1.23,1.03,3.08,0.82,5.42,0.08,0.68,38.6 6,31.38,13.98,0.99,0.87,0.10,0.51
Nganasan,0.00,0.03,0.20,3.15,0.00,0.00,0.00,0.00,0 .23,0.57,93.75,1.56,0.22,0.02,0.26
Nogai_Astrakhan,7.23,4.91,5.79,11.06,2.37,9.23,3.8 2,0.87,1.71,19.96,30.37,1.68,0.71,0.14,0.15
Nogai_Karachay_Cherkessia,3.58,5.97,9.22,8.31,2.88 ,39.22,3.05,1.16,1.97,8.01,14.45,0.93,0.58,0.65,0. 01
Nogai_Stavropol,8.62,4.49,4.78,11.21,1.69,14.53,3. 76,0.75,3.66,17.36,26.68,1.38,0.75,0.08,0.26
Tatar_Mishar,15.11,13.11,19.62,21.62,3.20,7.78,1.8 3,0.20,2.51,3.72,9.93,0.98,0.06,0.08,0.26
Tatar_Siberian,9.28,4.63,7.32,19.39,0.11,9.36,0.43 ,0.47,3.98,10.70,30.11,3.39,0.33,0.14,0.36
Tatar_Siberian_Zabolotniye,9.40,1.11,8.05,24.82,0. 00,4.26,0.00,0.00,4.32,6.28,37.55,3.46,0.37,0.00,0 .38
Thai,0.59,0.44,1.01,0.74,0.89,0.39,0.03,0.76,15.50 ,73.31,2.98,0.71,2.22,0.18,0.24
Tharu,0.15,0.56,0.77,2.89,1.28,5.15,0.19,0.00,38.3 7,32.94,14.80,0.93,1.71,0.15,0.12
Tlingit,10.21,2.20,14.14,14.20,0.00,1.72,0.00,0.00 ,2.11,4.95,23.40,26.38,0.06,0.11,0.53
Todzin,0.08,0.04,0.78,10.22,0.01,0.40,0.00,0.09,2. 94,13.57,68.09,3.24,0.47,0.00,0.08
Tofalar,0.09,0.06,0.06,10.61,0.06,0.11,0.00,0.23,1 .00,13.39,70.21,3.23,0.87,0.06,0.05
Ulchi,0.00,0.00,0.02,0.11,0.04,0.00,0.00,0.03,0.24 ,32.49,63.02,3.35,0.39,0.19,0.11
Veps,21.73,14.20,25.50,26.83,0.86,0.16,0.07,0.37,0 .77,0.09,7.59,1.12,0.41,0.17,0.12
Yukagir_Forest,10.30,7.62,14.57,14.81,2.25,0.82,0. 70,0.36,1.16,4.46,40.01,1.77,0.38,0.26,0.55
Yukagir_Tundra,0.01,0.00,0.50,3.07,0.05,0.08,0.00, 0.11,0.75,8.85,77.66,7.92,0.59,0.03,0.37

#K13, Cardona 2014
Altaian_Teleut,6.44,1.97,3.06,15.03,0.00,5.34,0.00 ,0.10,2.72,19.79,41.07,3.52,0.52,0.21,0.21
Forest_Nenets,2.38,0.19,1.18,21.60,0.00,0.03,0.00, 0.00,2.55,1.16,65.58,4.68,0.47,0.02,0.16
Komi_Siberian,13.73,8.14,16.26,28.19,0.74,1.23,0.0 8,0.02,1.80,0.93,25.74,2.69,0.28,0.06,0.10
Tundra_Nenets,3.14,1.61,2.01,20.70,0.11,0.26,0.00, 0.02,2.88,1.67,62.83,4.38,0.28,0.05,0.05

#K12b, Reich
Bashkir_Central,8.96,18.31,0.37,0.95,11.03,38.13,1 .49,0.10,1.45,9.60,9.47,0.14
Bashkir_North,8.37,17.54,0.22,0.68,11.69,41.61,1.9 4,0.04,0.52,7.50,9.66,0.24
Bashkir_South,11.08,24.18,0.34,1.20,7.50,29.53,1.8 1,0.12,0.47,15.74,7.88,0.15
Russian_Archangelsk_Krasnoborsky,4.77,7.42,0.26,0. 28,18.80,59.08,0.69,0.00,0.55,1.61,6.55,0.00
Russian_Archangelsk_Leshukonsky,5.06,12.41,0.28,0. 80,12.13,59.84,0.99,0.41,1.25,1.40,5.40,0.03
Russian_Archangelsk_Pinezhsky,4.02,9.51,0.46,0.73, 15.45,62.86,1.25,0.28,0.33,0.58,4.31,0.23
Russian_Belgorod,2.61,1.68,0.10,0.43,21.58,57.10,0 .62,0.00,1.68,0.48,13.67,0.04
Russian_Kaluga,1.82,2.15,0.10,0.33,19.05,59.85,1.1 0,0.00,1.79,0.04,13.76,0.01
Russian_Kursk,3.38,1.62,0.00,0.28,19.58,58.39,1.23 ,0.07,1.76,0.42,13.12,0.16
Russian_Orel,3.71,2.13,0.46,0.22,19.40,56.10,1.50, 0.32,1.10,0.63,14.28,0.14
Russian_Pskov,2.84,2.01,0.24,0.35,20.43,62.64,0.79 ,0.04,1.38,0.01,8.98,0.29
Russian_Ryazan,4.57,3.49,0.32,0.08,20.52,56.73,0.8 8,0.13,0.81,0.32,12.06,0.07
Russian_Smolensk,4.45,1.33,0.43,0.62,21.93,57.20,0 .74,0.13,1.49,0.00,11.57,0.12
Russian_Tver,3.93,3.69,1.18,0.42,19.36,57.31,0.38, 0.18,1.71,0.46,11.11,0.28
Russian_Vologda,3.04,7.38,0.17,0.43,14.03,63.23,0. 95,0.04,1.39,0.75,8.59,0.00
Russian_Yaroslavl,3.41,4.09,0.85,0.00,19.94,59.97, 0.69,0.16,0.62,0.70,9.56,0.00
Aleut,5.69,19.08,0.07,1.31,10.15,44.66,1.68,0.13,0 .16,12.75,4.31,0.00
Enets,3.16,66.82,0.00,0.00,0.95,17.61,0.15,0.00,0. 00,11.30,0.00,0.02
Itelmen,2.56,55.40,0.00,1.45,0.00,6.50,1.21,0.00,0 .00,32.81,0.00,0.08
Kalmyk,4.20,33.75,0.04,3.95,1.74,7.66,0.85,0.10,0. 36,44.01,3.34,0.01
Karelian,3.23,7.38,0.24,0.47,19.10,63.44,0.97,0.06 ,0.77,0.82,3.50,0.03
Kusunda,9.46,5.84,0.41,14.25,0.24,1.14,26.66,0.30, 0.02,41.46,0.16,0.06
Mansi,7.44,42.79,0.00,0.61,2.73,34.80,1.82,0.01,0. 00,8.99,0.81,0.00
Nasioi,3.46,4.82,0.60,34.24,1.67,2.01,36.86,3.54,0 .50,8.71,0.00,3.59
Newar,16.23,4.65,0.09,10.98,0.85,3.53,30.33,0.03,0 .25,31.70,1.34,0.00
Nganasan,0.12,89.74,0.06,0.48,0.02,1.15,0.15,0.08, 0.02,8.04,0.00,0.14
Nogai_Astrakhan,7.16,23.65,0.43,2.80,8.10,17.77,1. 16,0.02,1.95,27.43,9.50,0.04
Nogai_Karachay_Cherkessia,13.08,10.90,0.23,1.14,3. 84,20.54,0.51,0.16,0.71,12.88,35.94,0.07
Nogai_Stavropol,10.77,20.06,0.17,2.25,7.03,17.51,2 .11,0.03,1.67,24.76,13.64,0.00
Tatar_Mishar,7.19,10.06,0.01,0.88,16.61,46.04,1.67 ,0.00,1.32,5.20,10.99,0.03
Tatar_Siberian,9.41,26.59,0.25,1.56,6.42,27.29,1.9 6,0.07,0.81,17.87,7.77,0.00
Tatar_Siberian_Zabolotniye,10.85,36.40,0.00,1.12,2 .99,31.94,1.47,0.24,0.00,12.92,2.01,0.03
Thai,3.50,1.39,0.07,57.25,0.68,0.73,12.36,0.15,0.4 4,22.16,1.19,0.10
Tharu,15.85,4.64,0.19,10.28,0.34,2.39,31.17,0.00,0 .12,34.61,0.41,0.00
Tlingit,7.36,27.62,0.00,1.82,4.48,35.86,1.58,0.00, 0.00,19.27,2.00,0.00
Todzin,2.58,61.22,0.00,0.84,0.45,6.84,1.76,0.00,0. 32,25.99,0.00,0.00
Tofalar,2.33,64.08,0.00,0.48,0.07,5.86,0.83,0.13,0 .59,25.55,0.07,0.00
Ulchi,0.05,43.22,0.03,1.24,0.02,0.13,0.44,0.06,0.0 0,54.67,0.04,0.10
Veps,2.70,9.19,0.44,0.30,16.67,63.10,1.00,0.12,1.2 2,1.19,4.05,0.04
Yukagir_Forest,2.01,35.39,0.15,1.02,9.92,31.55,1.5 0,0.12,0.81,11.97,5.45,0.11
Yukagir_Tundra,0.58,68.94,0.04,0.29,0.02,3.27,0.68 ,0.05,0.00,26.08,0.00,0.04

#K12b, Cardona 2014
Altaian_Teleut,8.43,33.04,0.12,2.22,3.22,17.99,1.4 5,0.02,0.09,30.88,2.31,0.24
Forest_Nenets,4.21,65.37,0.00,0.03,0.05,19.27,0.84 ,0.01,0.00,10.18,0.01,0.03
Komi_Siberian,6.11,27.21,0.13,0.05,10.35,46.18,1.1 6,0.13,0.32,4.61,3.72,0.03
Tundra_Nenets,4.06,62.07,0.03,0.18,1.15,20.52,0.88 ,0.07,0.06,10.29,0.60,0.08

Hey Komin, what is Komi_Siberia? Another mixed group?

Target: Komi_Siberian
Distance: 0.3028% / 0.30276589 | R3P
51.6 Khanty
37.3 North_Russian
11.1 Russian_Oryol

Looks like a biracial Khanty-Russian mix :D The two principal Komi subgroups, the Zyryans and the Permyaks all live west of the Urals.

They're Komis whose location is listed as "Northwestern Siberia", which probably means Yamalo-Nenets Autonomous Okrug, or maybe Khanty-Mansi AO. They're from Cardona et al. 2014, "Genome-Wide Analysis of Cold Adaptation in Indigenous Siberian Populations": https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE73996.

Some Komis from Yamal are mixed with Khanty or Nenetses:

https://i.ibb.co/jJn5TdH/RY-2702-06m.jpg
"RY.2702-06: Marina Valeeva (right) a young Komi woman together with her mother, Marina Zatrueva, who is Khanty. inside her family's tent at a winter camp in the forest. Priuralsky District, Yamal, NW Siberia."
https://www.arcticphoto.com/supergal/ry/ry27/ry2702-06.htm

https://i.ibb.co/HYnbN3z/RY-2703-18m.jpg
https://www.arcticphoto.com/supergal/ry/ry27/ry2703-18.htm
"Two Komi sisters, Ksusha (left) and Albina Valeeva, wearing traditional reindeer skin clothing. Priuralsky District of the Yamal. NW Siberia, Russia"

In K13, 1 sample has Vepsian-level Siberian admixture, 7 are in the range of regular Komis, 3 samples are in the Mari range, 3 are in the range of Khanty and Mansi, and 1 has Nenets-level Siberian admixture:

North_AtlanticBalticWest_MedWest_AsianEast_MedRed_ SeaSouth_AsianEast_AsianSiberianAmerindianOceanian Northeast_AfricanSub-Saharan
Komi_Siberian:GRC1104969525.7544.186.356.973.260.0 01.980.009.920.730.810.000.05
Komi_Siberian:GRC1104969325.5143.135.935.640.000.4 22.470.0013.242.750.680.230.00
Komi_Siberian:GRC1104970028.2842.202.174.190.001.1 21.492.5813.653.110.290.000.93
Komi_Siberian:GRC1104969819.5047.624.528.290.170.0 01.871.0514.122.870.000.000.00
Komi_Siberian:GRC1104969221.9447.895.634.000.000.9 43.060.0014.390.931.210.000.00
Komi_Siberian:GRC1004501720.6748.960.009.870.510.1 81.190.0014.652.970.000.001.00
Komi_Siberian:GRC1104969924.7846.000.318.100.000.5 92.740.0014.842.480.000.090.07
Komi_Siberian:GRC1104969424.4547.432.253.550.000.0 02.030.7515.402.990.600.000.56
Komi_Siberian:GRC1104969114.0342.874.414.421.300.0 51.800.0028.472.640.000.000.00
Komi_Siberian:GRC1104968916.0939.350.005.850.001.2 31.673.0129.932.870.000.000.00
Komi_Siberian:GRC1104969015.5142.070.006.450.000.0 00.321.2031.000.991.021.440.00
Komi_Siberian:GRC110496969.0134.430.004.330.000.00 3.151.0242.265.730.070.000.00
Komi_Siberian:GRC110522396.9529.830.003.000.000.00 2.654.1847.765.540.000.000.10
Komi_Siberian:GRC110496975.2229.250.005.220.000.00 4.871.6048.583.961.080.230.00
Komi_Siberian:GRC110522380.0018.840.001.450.000.00 3.100.1072.673.830.000.000.00

Kolvin Nenetses are komified Nenetses who call themselves Komi, who speak Komi, and who wear Komi clothes, so it's not clear if they should be counted as a subgroup of Komi or Nenets, but they mostly live on the European side of the Urals, so I don't think these samples are Kolvin.

Leto

10-26-2021, 02:02 PM

Thanks for clarifying that, Komin!

Can you merge Kursk, Belgorod and Oryol into one new Russian_Southwest average? Would be better than the old Davidski shit, at least here we know the sample size. I will probably consider adding some of those Russians to the updated K13 spreadsheet.

EDIT: wait, I can do it myself :)

vbnetkhio

10-26-2021, 02:14 PM

Leto

10-26-2021, 02:35 PM

why not add all of them?
Some of them are just 3-4 samples. And also I don't want those "Arkhangelsk" pops either, they aren't even represenative of Northern Russia.

vbnetkhio

10-26-2021, 08:56 PM

Actually I think you need to make the tolerance parameter (`-t`) smaller (https://github.com/stevenliuyi/admix#faq):

This package utilizes the optimization function `scipy.optimize.minimize` from the SciPy library, which has a parameter `tol` to control the tolerance for termination of the optimizer. The default tolerance is set to `1e-3` here. It works most of time, but sometimes `1e-3` is too big and causes early termination. You can manually set a smaller tolerance (say `1e-4`) to obtain correct results, although it will take longer to run the optimizer.

michal3141 also got the wrong results in K36 by using the default threshold, and he said that "probably e-7 or at least e-6 is the way to go": https://anthrogenica.com/showthread.php?25056-Has-anyone-tried-this-program&p=810669&viewfull=1#post810669.

When I tried doing another run of one of the samples from Vologda that got over 99% Baltic (HGDP00899), it first got the same results, because the algorithm doesn't use a random seed like ADMIXTURE, but it gives the same result each time. After I decreased the tolerance to 1e-4, the results started to resemble other samples from Vologda. Between 1e-4 and 1e-5, some admixture proportions still changed by more than 0.3 percentage points, but there was no further change between 1e-5 and 1e-6:

~ admix -f a.txt -mK13

Admixture calculation models: K13

Calcuation is started...

K13
North_Atlantic: 0.12%
Baltic: 99.76%
West_Med: 0.00%
West_Asian: 0.00%
East_Med: 0.00%
Red_Sea: 0.00%
South_Asian: 0.00%
East_Asian: 0.00%
Siberian: 0.07%
Amerindian: 0.00%
Oceanian: 0.05%
Northeast_African: 0.00%
Sub-Saharan: 0.00%

~ admix -f a.txt -mK13 -t1e-4

Admixture calculation models: K13

Calcuation is started...

K13
North_Atlantic: 3.95%
Baltic: 71.60%
West_Med: 5.06%
West_Asian: 2.74%
East_Med: 6.62%
Red_Sea: 0.67%
South_Asian: 0.00%
East_Asian: 0.16%
Siberian: 6.24%
Amerindian: 1.26%
Oceanian: 1.31%
Northeast_African: 0.04%
Sub-Saharan: 0.36%

~ admix -f a.txt -mK13 -t1e-5

Admixture calculation models: K13

Calcuation is started...

K13
North_Atlantic: 4.09%
Baltic: 71.69%
West_Med: 4.73%
West_Asian: 2.64%
East_Med: 6.46%
Red_Sea: 0.91%
South_Asian: 0.00%
East_Asian: 0.11%
Siberian: 6.05%
Amerindian: 1.37%
Oceanian: 1.55%
Northeast_African: 0.03%
Sub-Saharan: 0.36%

~ admix -f a.txt -mK13 -t1e-6

Admixture calculation models: K13

Calcuation is started...

K13
North_Atlantic: 4.09%
Baltic: 71.69%
West_Med: 4.73%
West_Asian: 2.64%
East_Med: 6.46%
Red_Sea: 0.91%
South_Asian: 0.00%
East_Asian: 0.11%
Siberian: 6.05%
Amerindian: 1.37%
Oceanian: 1.55%
Northeast_African: 0.03%
Sub-Saharan: 0.36%

I ran K13 at different tolerance parameters for all 87 samples from the Reich dataset with the population name "Russian", because they included some problematic samples in my earlier K13 run. Now the average difference in the admixture percentages became less than 0.01 between 1e-4 and 1e-5, and less than 0.0001 between 1e-5 and 1e-6:

ToleranceAverage difference in admixture percentages
compared to previous toleranceRunning time
per sample
1e-1-1.22
1e-23.1448101.65
1e-33.5153493.12
1e-40.3167373.47
1e-50.0023873.64
1e-60.0000973.51
1e-70.0000623.65
1e-80.0000883.65

So it's probably better to change the tolerance to at least 1e-5, even though in this case even 1e-8 was about as fast.

I ran the Lithuanian outliers in DiyDodecad:

PZ:LTG-890,25.8,59.06,7.33,4.06,0.02,0.66,0.51,0.84,0.17, 0.39,0.65,0.28,0.23
SZ:LTG-1205,29.9,52.24,7.97,5.91,0.03,1,1.08,0,0.98,0.31, 0,0,0.59
PA:LTG-781,26.45,52.62,10.68,5.6,0.12,0.47,0.12,0.62,0.92 ,1.02,0.38,0.45,0.56
RA:LTG-181,30.5,47.1,9.91,7.05,1.98,0.05,2.09,0.42,0,0.81 ,0.05,0,0.03
PZ:LTG-1162,29.47,59.79,6.51,0.06,0,1.31,0.74,0,1.33,0.27 ,0.52,0,0
SZ:LTG-356,19.23,76.46,4.32,0,0,0,0,0,0,0,0,0,0

LTG-356 still has weird results, and he has 50% gentype rate, while all other samples have 90%. so there is something wrong with this sample.

Komintasavalta

10-26-2021, 09:21 PM

I ran the Lithuanian outliers in DiyDodecad:

PZ:LTG-890,25.8,59.06,7.33,4.06,0.02,0.66,0.51,0.84,0.17, 0.39,0.65,0.28,0.23
SZ:LTG-1205,29.9,52.24,7.97,5.91,0.03,1,1.08,0,0.98,0.31, 0,0,0.59
PA:LTG-781,26.45,52.62,10.68,5.6,0.12,0.47,0.12,0.62,0.92 ,1.02,0.38,0.45,0.56
RA:LTG-181,30.5,47.1,9.91,7.05,1.98,0.05,2.09,0.42,0,0.81 ,0.05,0,0.03
PZ:LTG-1162,29.47,59.79,6.51,0.06,0,1.31,0.74,0,1.33,0.27 ,0.52,0,0
SZ:LTG-356,19.23,76.46,4.32,0,0,0,0,0,0,0,0,0,0

LTG-356 still has weird results, and he has 50% gentype rate, while all other samples have 90%. so there is something wrong with this sample.

Maybe it would just be better to use DIYDodecad for consistency. Even when I used a tolerance of 1e-7, the results of the Python admix script sometimes differed by more than 1 percentage points from your results:

LTG-1162/DIYDodecad29.4759.796.510.0601.310.7401.330.270.52 00LTG-1162/python30.9758.107.380.000.000.490.650.000.811.150. 450.000.00
LTG-1205/DIYDodecad29.952.247.975.910.0311.0800.980.31000.5 9LTG-1205/python30.9253.037.994.230.000.860.860.000.680.730. 000.000.70
LTG-181/DIYDodecad30.547.19.917.051.980.052.090.4200.810.0 500.03LTG-181/python31.6345.9510.467.630.720.272.390.000.000.890 .000.000.05
LTG-356/DIYDodecad19.2376.464.320000000000LTG-356/python21.4774.484.050.000.000.000.000.000.000.000. 000.000.00
LTG-781/DIYDodecad26.4552.6210.685.60.120.470.120.620.921. 020.380.450.56LTG-781/python27.6851.549.276.160.001.230.001.331.280.740. 270.000.51
LTG-890/DIYDodecad25.859.067.334.060.020.660.510.840.170.3 90.650.280.23LTG-890/python26.1059.086.634.530.001.370.190.930.430.040. 500.080.11

The developer of Admixture Studio wrote that he developed it as a GUI for DIYDodecad, so I guess it produces the same results as DIYDodecad? (https://anthrogenica.com/showthread.php?4879-Tutorial-%96-How-to-use-DIY-calculator-files-and-oracle-data-sheets/page4)

Hi! I developed a windows tool for simplify the use of DIYDodecad calculators and ADMIX-4, I called Admixture Studio. It runs the Kxxx file in DIYDodecad and Anc_oracle_097.exe. The application converts the RAW File to genotype.exe reordered format as DIYDodecad requires.

So, you don't need to use R or command lines tools :).

Feel free to use it. It is still in beta.
https://wilhelmhgenealogy.wordpress.com/admixture-studio/

could you run the Greek and Polish from here?
https://data.mendeley.com/datasets/ckz9mtgrjj/3

K13 with tolerance 1e-7:

Greek:GRE201,14.57,15.80,23.52,12.68,28.01,4.12,0. 04,0.00,0.00,0.31,0.23,0.00,0.72
Greek:GRE202,15.37,10.01,21.26,13.93,32.88,4.88,0. 00,0.65,0.00,0.02,1.00,0.00,0.00
Greek:GRE204,14.79,11.81,20.78,19.14,25.96,4.90,1. 11,0.00,0.48,0.53,0.07,0.42,0.00
Greek:Greek1,14.47,16.03,23.43,12.36,27.98,4.26,0. 26,0.00,0.00,0.35,0.18,0.00,0.69
Greek:Greek2,15.20,10.09,21.45,13.86,33.07,4.59,0. 00,0.57,0.00,0.18,0.99,0.00,0.00
Greek:Greek3,15.15,11.81,20.66,18.83,25.94,4.88,1. 19,0.00,0.43,0.57,0.06,0.47,0.00
Greek:Greek4,18.77,15.44,20.66,10.37,28.59,4.84,0. 00,0.00,1.14,0.11,0.08,0.00,0.00
Greek:Greek5,16.46,16.47,22.05,13.87,27.38,2.87,0. 00,0.20,0.00,0.00,0.69,0.00,0.00
Greek:Greek6,19.09,14.03,22.03,15.59,26.02,2.93,0. 00,0.00,0.08,0.23,0.00,0.00,0.00
Greek:Greek7,20.99,16.17,21.06,10.25,27.70,3.24,0. 00,0.00,0.39,0.00,0.20,0.00,0.00
Greek:Greek8,15.50,16.43,22.96,13.27,27.73,1.90,0. 26,0.24,0.26,0.00,1.00,0.00,0.46
Greek:Greek9,17.77,15.40,25.49,12.49,24.42,3.15,0. 00,0.00,0.00,1.29,0.00,0.00,0.00
Greek:Greek10,19.53,18.14,18.97,13.70,26.34,1.72,0 .00,1.09,0.00,0.00,0.00,0.52,0.00
Greek:Greek11,17.36,12.86,20.29,14.67,27.10,6.51,0 .00,0.00,0.56,0.64,0.00,0.00,0.00
Greek:Greek12,18.88,17.70,22.61,11.85,24.79,3.12,0 .63,0.00,0.00,0.03,0.38,0.00,0.00
Greek:Greek13,20.72,13.40,22.02,13.82,23.73,5.38,0 .00,0.00,0.13,0.00,0.26,0.55,0.00
Greek:Greek14,15.64,14.50,21.03,13.77,28.74,4.93,0 .00,0.00,0.00,0.57,0.81,0.00,0.00
Greek:Greek15,17.91,17.57,20.46,13.05,23.85,4.40,0 .00,0.56,1.01,0.21,0.98,0.00,0.00
Greek:Greek16,20.16,15.31,21.87,11.28,25.96,3.84,0 .14,1.44,0.00,0.00,0.00,0.00,0.00
Greek:Greek17,12.52,9.99,23.11,16.35,29.88,5.55,0. 08,0.44,0.79,0.00,0.38,0.90,0.00
Greek:Greek18,13.25,10.55,19.09,23.50,29.15,3.39,0 .34,0.00,0.37,0.00,0.37,0.00,0.00
Greek:Greek19,15.43,9.58,19.23,15.85,33.37,5.81,0. 00,0.00,0.00,0.00,0.73,0.00,0.00
Greek:Greek20,15.21,17.52,24.48,14.42,24.48,3.00,0 .00,0.46,0.00,0.00,0.43,0.00,0.00
Greek:K28,18.82,15.60,20.57,10.38,28.66,4.65,0.00, 0.00,1.23,0.07,0.01,0.00,0.00
Greek:K29,16.45,16.55,21.92,13.81,27.40,3.01,0.00, 0.22,0.00,0.00,0.65,0.00,0.00
Greek:K30,19.00,13.74,22.26,15.85,25.98,2.88,0.00, 0.00,0.14,0.14,0.00,0.00,0.00
Greek:KOR22,20.98,16.25,21.12,10.04,27.80,3.21,0.0 0,0.00,0.31,0.00,0.30,0.00,0.00
Greek:KOR24,15.65,16.37,22.93,13.16,27.83,1.79,0.2 9,0.11,0.45,0.00,0.94,0.00,0.48
Greek:KOR29,18.07,15.58,24.99,12.41,24.47,3.22,0.0 0,0.00,0.00,1.25,0.00,0.00,0.00
Greek:KOR30,19.81,17.90,19.07,13.79,26.17,1.73,0.0 0,1.01,0.00,0.00,0.00,0.52,0.00
Greek:KOR31,17.55,12.87,20.19,14.79,26.91,6.58,0.0 0,0.00,0.50,0.61,0.00,0.00,0.00
Greek:XAL90,18.70,17.78,22.61,11.99,24.54,3.24,0.7 7,0.00,0.00,0.05,0.32,0.00,0.00
Greek:XAL91,20.71,13.26,21.87,14.03,23.85,5.48,0.0 0,0.00,0.05,0.00,0.26,0.50,0.00
Greek:XAL92,15.95,14.31,21.18,13.61,28.64,4.95,0.0 0,0.00,0.00,0.59,0.76,0.00,0.00
Greek:XAL93,17.91,17.57,20.38,12.85,24.09,4.43,0.0 0,0.60,0.93,0.24,0.99,0.00,0.00
Greek:XAL94,20.13,15.68,21.69,11.03,26.01,3.90,0.1 1,1.46,0.00,0.00,0.00,0.00,0.00
Greek:XAL95,12.39,9.94,23.06,16.63,30.07,5.31,0.04 ,0.49,0.84,0.00,0.35,0.88,0.00
Greek:XAL96,13.12,10.54,18.94,24.12,28.99,3.45,0.1 4,0.00,0.43,0.00,0.26,0.00,0.00
Greek:XAL97,15.54,9.61,19.02,15.54,33.57,5.96,0.00 ,0.00,0.00,0.00,0.76,0.00,0.00
Greek:XAL98,15.57,17.34,24.52,14.06,24.62,2.93,0.0 0,0.62,0.00,0.00,0.33,0.00,0.00
Polish:POL002,28.84,47.62,11.06,7.32,3.09,0.00,0.0 0,0.00,0.00,1.15,0.28,0.03,0.62
Polish:POL016,30.59,47.07,12.43,5.85,1.24,0.00,0.0 0,0.00,0.61,0.86,0.00,1.10,0.23
Polish:POL026,26.73,47.53,10.09,5.93,4.45,0.74,0.2 9,0.00,1.65,1.78,0.00,0.29,0.53
Polish:POL039R,29.79,38.93,12.98,5.49,9.16,1.18,0. 84,0.38,0.72,0.39,0.00,0.00,0.15
Polish:POL049,24.90,49.31,13.07,5.68,1.89,0.25,2.4 8,0.00,0.65,0.67,1.09,0.00,0.00
Polish:POL052,27.18,47.37,9.55,2.94,9.47,0.00,1.45 ,0.00,0.46,1.30,0.28,0.00,0.00
Polish:POL059,32.28,45.68,10.15,5.93,2.36,0.00,0.8 2,0.43,0.44,0.47,0.25,0.00,1.20
Polish:POL062,28.76,43.98,11.30,6.39,5.42,0.00,2.0 6,0.00,0.03,1.51,0.00,0.55,0.00
Polish:POL069,32.86,37.08,12.49,6.99,8.45,0.65,0.0 6,0.00,0.53,0.00,0.00,0.14,0.75
Polish:POL072,26.97,45.59,11.81,7.62,4.61,0.14,1.2 3,0.00,0.51,1.12,0.00,0.39,0.00
Polish:POL079,25.39,52.43,8.19,6.09,4.58,0.00,1.65 ,0.00,1.30,0.00,0.05,0.00,0.31
Polish:POL082,33.39,45.84,9.43,4.55,1.17,2.06,0.29 ,0.33,0.15,0.65,0.56,0.84,0.74
Polish:POL089,26.38,46.59,13.43,7.38,2.76,0.36,0.3 3,0.00,1.02,0.15,0.83,0.78,0.00
Polish:POL108,30.60,43.74,9.40,7.94,4.05,0.80,0.72 ,0.12,1.40,0.49,0.46,0.00,0.28
Polish:POL118,29.38,46.85,10.57,5.46,4.38,1.44,0.2 3,0.00,0.61,0.37,0.34,0.39,0.00
Polish:POL150,29.44,47.20,10.66,9.07,0.86,0.00,0.5 7,0.20,0.17,0.00,1.17,0.00,0.66
Polish:POL199,31.62,44.36,11.65,7.83,0.49,0.38,0.6 0,0.00,2.17,0.75,0.00,0.16,0.00
Polish:Polish1,28.95,47.69,10.97,7.15,3.17,0.00,0. 00,0.00,0.00,1.14,0.24,0.00,0.69
Polish:Polish2,25.21,52.85,8.34,5.93,4.39,0.00,1.5 5,0.00,1.28,0.03,0.00,0.00,0.41
Polish:Polish3,26.37,46.44,13.71,7.49,2.48,0.42,0. 41,0.00,0.97,0.15,0.75,0.82,0.00
Polish:Polish4,30.23,44.07,9.31,7.88,4.33,0.77,0.6 2,0.04,1.50,0.43,0.52,0.00,0.31
Polish:Polish5,31.69,44.30,11.48,7.79,0.62,0.42,0. 55,0.00,2.23,0.81,0.00,0.12,0.00
Polish:Polish6,30.76,47.02,12.32,5.80,1.44,0.00,0. 00,0.00,0.63,0.80,0.00,0.94,0.29
Polish:Polish7,26.72,47.57,9.90,6.22,4.19,0.85,0.2 1,0.00,1.62,1.79,0.00,0.37,0.54
Polish:Polish8,24.84,49.28,13.08,5.83,1.76,0.25,2. 49,0.00,0.71,0.66,1.11,0.00,0.00
Polish:Polish9,27.83,47.04,9.50,2.71,9.38,0.00,1.4 3,0.00,0.38,1.44,0.30,0.00,0.00
Polish:Polish10,32.69,45.50,10.18,5.71,2.22,0.00,0 .90,0.34,0.21,0.59,0.36,0.00,1.28
Polish:Polish11,28.97,43.93,11.27,6.36,5.32,0.00,1 .97,0.00,0.07,1.49,0.00,0.62,0.00
Polish:Polish12,32.86,37.12,12.75,6.94,8.38,0.48,0 .00,0.00,0.55,0.00,0.00,0.15,0.78
Polish:Polish13,26.79,45.64,12.02,7.76,4.50,0.00,1 .08,0.00,0.60,1.13,0.00,0.48,0.00
Polish:Polish14,33.20,45.93,9.23,4.74,1.24,2.12,0. 28,0.25,0.16,0.72,0.58,0.70,0.86
Polish:Polish15,29.35,47.06,10.48,5.59,4.07,1.31,0 .35,0.00,0.64,0.26,0.31,0.58,0.00
Polish:Polish16,29.19,47.49,10.51,9.08,1.07,0.00,0 .57,0.26,0.02,0.00,1.14,0.00,0.66

Leto

10-26-2021, 09:42 PM

Tambets seems to have quite a few Estonian samples. Can you run them and then compare to the old Eurogenes average? I have like 15 non-academic Estonian kits but let's stick to these data sets.

vbnetkhio

10-27-2021, 07:44 AM

Maybe it would just be better to use DIYDodecad for consistency. Even when I used a tolerance of 1e-7, the results of the Python admix script sometimes differed by more than 1 percentage

LTG-1162/DIYDodecad29.4759.796.510.0601.310.7401.330.270.52 00LTG-1162/python30.9758.107.380.000.000.490.650.000.811.150. 450.000.00
LTG-1205/DIYDodecad29.952.247.975.910.0311.0800.980.31000.5 9LTG-1205/python30.9253.037.994.230.000.860.860.000.680.730. 000.000.70
LTG-181/DIYDodecad30.547.19.917.051.980.052.090.4200.810.0 500.03LTG-181/python31.6345.9510.467.630.720.272.390.000.000.890 .000.000.05
LTG-356/DIYDodecad19.2376.464.320000000000LTG-356/python21.4774.484.050.000.000.000.000.000.000.000. 000.000.00
LTG-781/DIYDodecad26.4552.6210.685.60.120.470.120.620.921. 020.380.450.56LTG-781/python27.6851.549.276.160.001.230.001.331.280.740. 270.000.51
LTG-890/DIYDodecad25.859.067.334.060.020.660.510.840.170.3 90.650.280.23LTG-890/python26.1059.086.634.530.001.370.190.930.430.040. 500.080.11

lower tolerance runs seem slightly biased towards North Atlantic?

Lucas

10-27-2021, 10:06 AM

Maybe it would just be better to use DIYDodecad for consistency. Even when I used a tolerance of 1e-7, the results of the Python admix script sometimes differed by more than 1 percentage points from your results:

]

But DYIDodecad isn't a gold standard. We really don't know which calculation is better (also we must add here Admixture Studio which also have little different values). Dodecad was first this is why is more popular. But maybe if the code would be public you could see there some things which aren't better then admix.

Komintasavalta

10-27-2021, 11:46 AM

Most monkeys and Neandersovans got at least 2% Oceanian. But Marmoset and Macaque got surprisingly high North Atlantic.

North_AtlanticBalticWest_MedWest_AsianEast_MedRed_ SeaSouth_AsianEast_AsianSiberianAmerindianOceanian Northeast_AfricanSub-Saharan
Chimp_HO0.000.000.000.000.000.000.000.000.000.361. 5922.1075.95
Gorilla0.000.000.000.000.000.000.000.000.000.002.6 823.6873.64
Gorilla.REF0.000.000.000.000.000.000.000.000.000.4 62.5123.7373.30
Macaque3.120.000.000.000.000.000.002.211.460.633.4 422.5666.59
Marmoset5.111.220.000.000.000.000.655.460.001.633. 9121.4060.63
Orang0.850.130.000.000.000.000.001.390.001.012.992 2.8970.73
Denisova_light0.000.000.000.000.000.000.000.000.00 0.002.8215.6381.55
Denisova_snpAD.DG0.000.000.000.000.000.000.000.000 .000.002.5414.7682.70
Denisova_published.DG0.000.000.000.000.000.000.000 .000.000.002.6715.3382.00
Denisova11.SG0.000.000.000.000.000.000.000.000.000 .003.4317.9678.62
Vindija_light0.000.070.000.000.000.000.000.000.000 .003.1518.1278.66
Altai_published.DG0.000.000.000.000.000.000.000.00 0.000.002.0118.2279.77
Les_Cottes_final_provisional.SG0.000.040.400.000.0 00.000.000.000.000.004.1518.4077.00
Altai_snpAD.DG0.000.000.000.000.000.000.000.000.00 0.001.8517.9280.23
Mezmaiskaya1_final_provisional.SG0.420.550.000.000 .000.000.000.000.000.003.7517.6477.63
Vindija_snpAD.DG0.000.000.000.000.000.000.000.000. 000.002.1717.3880.45
Mezmaiskaya2_final_provisional.SG0.460.620.000.000 .000.000.000.000.080.024.0118.4676.34
Spy_final_provisional.SG1.520.000.000.000.000.000. 000.110.000.005.1619.8473.37
VindijaG1_final_provisional.SG0.000.000.240.000.00 0.000.000.000.000.004.2819.9575.53
Goyet_final_provisional.SG0.000.000.000.000.000.00 0.000.000.000.002.9118.1878.91
Chagyrskaya.SG0.000.000.000.000.000.000.000.000.00 0.002.1817.3780.45

BTW does anyone know if there is some way to calculate the fit of a model using the .F and .alleles files?

Komintasavalta

10-27-2021, 10:06 PM

Tambets seems to have quite a few Estonian samples. Can you run them and then compare to the old Eurogenes average? I have like 15 non-academic Estonian kits but let's stick to these data sets.

Here's all samples from Tambets et al. 2018 (https://evolbio.ut.ee/Tambets2018/). The Buryat sample looks hapa, so I don't know why it was included here. I didn't omit any sample from the averages.

#K13 average
Buryats,13.53,27.77,2.72,4.76,1.24,1.43,1.14,12.50 ,33.11,0.87,0.52,0.40,0.00
Estonians,30.71,51.59,6.53,3.34,1.61,0.44,1.24,0.3 3,2.55,0.76,0.44,0.19,0.28
Finns,31.78,48.09,5.53,2.37,1.54,0.71,1.17,0.27,6. 22,1.16,0.46,0.29,0.42
Gagauzes,17.84,23.73,18.94,12.92,21.07,2.04,0.65,0 .00,2.20,0.00,0.00,0.61,0.00
Germans,43.14,22.63,15.79,4.12,11.13,0.72,0.00,0.0 0,0.33,1.26,0.28,0.00,0.60
Ingrian,30.84,49.64,5.29,2.84,1.50,0.30,0.62,0.70, 5.94,1.09,0.49,0.22,0.53
Karels,29.51,44.12,5.80,6.00,3.76,0.48,1.30,0.00,6 .62,1.82,0.00,0.30,0.28
Khanty,5.66,31.37,0.00,3.53,0.00,0.00,4.34,0.82,47 .60,6.01,0.57,0.00,0.10
Latvians,30.73,49.48,8.23,4.90,4.07,0.00,0.00,0.98 ,0.23,1.17,0.21,0.00,0.00
Mansi,15.63,38.60,2.88,5.77,0.92,0.31,3.32,0.63,27 .39,3.69,0.48,0.16,0.23
Maris,12.70,44.99,1.37,9.59,0.00,0.18,2.62,3.04,22 .64,2.50,0.00,0.37,0.00
Poles,27.65,48.46,7.22,6.67,3.16,0.43,0.99,0.03,3. 64,0.87,0.61,0.10,0.15
Russians_Central,25.51,47.04,9.13,5.08,4.78,0.62,2 .34,0.32,3.66,0.44,0.71,0.10,0.28
Saami_Kola,24.79,47.67,2.76,1.03,0.12,0.05,1.56,0. 26,17.62,2.77,0.34,0.69,0.34
Saami_SWE,24.98,43.86,0.00,0.72,0.00,0.00,1.24,1.2 3,23.51,3.64,0.41,0.06,0.34
Swedes,39.89,37.58,10.25,3.76,2.26,1.09,0.34,0.12, 3.55,0.77,0.06,0.00,0.33
Tatars,18.86,30.88,5.01,12.42,7.20,0.58,5.54,4.22, 12.84,1.47,0.64,0.22,0.12
Vepsas,27.66,50.63,4.37,3.44,0.42,0.24,2.15,0.19,8 .68,1.60,0.27,0.00,0.34

#K13
Buryats:buryat_V43501,13.53,27.77,2.72,4.76,1.24,1 .43,1.14,12.50,33.11,0.87,0.52,0.40,0.00
Estonians:100218,28.41,54.08,9.69,1.03,0.25,0.00,2 .66,1.22,2.62,0.00,0.04,0.00,0.00
Estonians:100228,27.27,57.56,5.34,4.86,0.00,0.00,1 .41,1.94,0.42,0.93,0.11,0.17,0.00
Estonians:100230,30.63,52.18,4.42,3.99,3.36,0.69,0 .00,0.00,3.82,0.00,0.33,0.07,0.51
Estonians:100232,33.62,53.56,5.42,2.04,0.00,0.00,0 .00,0.00,2.63,2.11,0.61,0.00,0.00
Estonians:100233,33.81,49.97,7.81,0.96,2.62,0.00,0 .21,0.00,2.59,1.17,0.86,0.00,0.00
Estonians:100235,30.93,52.32,5.20,5.12,0.00,0.34,2 .44,0.03,2.26,0.45,0.00,0.91,0.00
Estonians:100243,24.00,57.98,5.90,4.53,2.03,0.00,2 .90,0.52,1.92,0.09,0.00,0.00,0.14
Estonians:100248,36.70,49.69,6.62,1.25,0.00,0.00,0 .09,0.24,3.21,1.32,0.04,0.00,0.85
Estonians:100249,27.98,55.51,6.47,3.75,0.04,0.73,0 .90,0.71,0.82,1.29,0.49,1.31,0.00
Estonians:100252,30.84,55.92,6.27,1.25,0.41,0.00,2 .53,0.00,2.03,0.00,0.07,0.00,0.67
Estonians:100253,28.59,56.65,7.49,0.45,0.54,0.32,1 .57,0.00,2.10,0.00,0.74,0.47,1.07
Estonians:100254,28.95,54.38,5.00,2.22,0.00,2.72,1 .88,0.96,2.52,0.97,0.40,0.00,0.00
Estonians:100257,30.98,52.24,4.17,1.36,2.98,0.00,2 .09,0.00,4.82,1.15,0.21,0.00,0.00
Estonians:100258,29.28,53.10,7.26,0.00,4.81,0.77,1 .09,0.00,2.55,0.00,0.75,0.00,0.38
Estonians:100259,34.46,49.13,6.79,1.80,0.00,0.26,1 .69,0.00,2.70,1.46,1.02,0.00,0.68
Estonians:100261,25.10,54.37,7.79,5.26,1.43,0.00,2 .70,0.78,1.06,0.64,0.00,0.55,0.31
Estonians:100263,25.57,61.18,6.01,1.59,0.00,0.74,0 .51,0.00,2.00,1.32,0.45,0.00,0.62
Estonians:100520,29.55,53.18,6.79,3.79,0.60,0.00,0 .11,0.01,3.96,0.59,0.79,0.00,0.62
Estonians:100531,34.75,47.94,6.75,2.48,0.00,0.36,2 .07,0.00,4.11,0.58,0.60,0.00,0.35
Estonians:100550,30.59,51.99,8.90,3.39,0.00,0.00,0 .00,0.30,2.70,0.72,1.15,0.26,0.00
Estonians:100557,33.10,50.87,5.10,4.47,0.00,0.81,1 .17,1.00,2.49,0.41,0.04,0.00,0.54
Estonians:100558,29.52,54.11,6.61,2.52,3.50,0.00,0 .00,0.74,1.69,0.29,0.00,0.02,0.99
Estonians:400204,26.95,55.73,5.68,1.43,2.91,1.22,0 .54,1.26,1.95,1.37,0.07,0.89,0.00
Estonians:400206,38.32,46.54,4.73,1.73,0.00,0.00,1 .21,0.00,4.78,1.58,0.85,0.00,0.26
Estonians:400209,34.09,49.15,3.70,3.01,3.51,0.00,1 .79,0.00,4.17,0.41,0.09,0.00,0.07
Estonians:400210,25.95,51.36,6.17,7.36,1.50,1.65,0 .39,0.00,4.20,0.00,1.42,0.00,0.00
Estonians:400221,31.28,49.79,5.49,5.79,2.04,0.12,0 .65,0.00,3.82,0.00,0.96,0.00,0.05
Estonians:400235,28.74,36.29,9.05,13.70,8.28,1.31, 0.61,0.00,1.38,0.00,0.64,0.00,0.00
Estonians:400236,38.99,42.92,5.14,6.93,0.00,0.00,1 .23,0.00,3.91,0.65,0.24,0.00,0.00
Estonians:400237,25.82,51.70,5.81,5.61,6.22,0.33,0 .99,0.00,1.31,0.98,0.00,1.24,0.00
Estonians:400238,33.79,51.44,7.51,2.21,0.00,0.00,2 .25,0.00,1.42,1.23,0.14,0.00,0.00
Estonians:400240,32.78,54.33,5.98,2.29,0.00,0.00,1 .93,0.00,1.40,0.68,0.00,0.00,0.61
Estonians:evo_3,31.12,52.40,8.20,1.28,0.74,0.00,1. 25,1.35,0.76,1.66,0.95,0.05,0.26
Estonians:evo_4,33.03,54.80,4.85,1.63,0.00,0.00,1. 58,0.34,1.12,1.09,0.85,0.71,0.00
Estonians:evo_6,32.03,46.87,9.39,5.53,0.00,0.12,0. 00,0.00,2.79,1.58,0.81,0.00,0.89
Estonians:evo_7,28.14,35.90,11.45,3.76,10.03,3.23, 2.13,0.61,3.79,0.49,0.00,0.26,0.21
Finns:Finland65,37.86,45.05,4.01,0.17,0.00,0.92,2. 13,0.00,7.15,1.73,0.65,0.16,0.17
Finns:Finland67,33.20,48.73,3.16,1.33,2.95,0.00,0. 92,0.00,6.23,1.96,0.11,0.81,0.59
Finns:Finland69,33.84,48.96,4.56,0.50,0.14,0.00,1. 87,0.00,8.46,0.92,0.75,0.00,0.00
Finns:Finland74,33.51,47.08,4.95,2.00,0.00,0.21,0. 00,1.08,8.80,0.72,0.00,0.05,1.59
Finns:Finland76,34.39,49.13,3.62,3.13,0.00,0.00,1. 68,0.00,6.20,0.86,0.99,0.00,0.00
Finns:Finland78,29.96,47.15,6.27,1.88,4.07,1.23,1. 90,0.11,5.56,1.08,0.57,0.00,0.21
Finns:Finland84,31.30,45.71,7.90,2.74,3.29,1.37,0. 47,0.33,4.05,1.73,1.07,0.05,0.00
Finns:Finland86,35.30,49.18,1.98,2.69,0.00,0.00,0. 00,0.00,7.89,2.03,0.19,0.00,0.74
Finns:Finland87,32.18,50.34,5.27,0.00,0.00,0.76,1. 26,0.95,6.47,1.99,0.00,0.08,0.70
Finns:Finland94,31.47,49.69,6.93,3.85,0.00,0.93,0. 09,1.36,3.76,0.68,0.69,0.00,0.55
Finns:Finland95,26.52,50.03,7.14,1.15,1.98,0.00,3. 50,0.00,8.04,0.44,0.93,0.00,0.26
Finns:Finland97,32.72,51.15,3.89,0.52,0.32,1.34,0. 58,0.00,7.45,0.71,0.63,0.00,0.68
Finns:Finland101,24.35,38.84,12.68,3.78,10.28,1.36 ,0.00,0.00,6.00,0.98,0.00,1.27,0.47
Finns:Finland106,30.90,46.99,6.28,7.57,1.58,0.00,0 .67,0.00,4.49,0.95,0.58,0.00,0.00
Finns:Finland109,31.24,49.98,9.29,0.00,4.31,0.61,0 .97,1.01,1.07,0.46,0.00,0.82,0.25
Finns:Finland111,30.43,48.72,4.81,4.02,0.00,0.98,2 .46,0.00,6.41,0.79,0.39,0.81,0.18
Finns:Finland117,30.23,50.72,5.50,2.76,0.00,1.25,1 .11,0.00,5.53,0.87,0.52,0.00,1.50
Finns:Finland118,32.07,46.91,4.43,7.02,0.02,1.14,0 .40,0.31,4.38,1.83,0.00,1.37,0.12
Finns:Finland119,32.30,49.27,2.47,0.00,0.26,1.33,2 .19,0.00,10.20,1.30,0.67,0.00,0.00
Gagauzes:Gagauz10,17.84,23.73,18.94,12.92,21.07,2. 04,0.65,0.00,2.20,0.00,0.00,0.61,0.00
Germans:German7,43.14,22.63,15.79,4.12,11.13,0.72, 0.00,0.00,0.33,1.26,0.28,0.00,0.60
Ingrian:ingerian_V06336,32.26,50.19,3.81,1.48,1.93 ,0.00,0.35,2.04,5.94,0.10,0.83,0.00,1.09
Ingrian:ingerian_V22241,32.96,48.45,5.57,1.11,1.38 ,0.00,1.46,0.00,7.10,0.89,0.01,0.69,0.38
Ingrian:ingerian_V24378,30.27,47.41,6.82,5.01,1.98 ,0.00,0.99,0.00,4.74,1.63,0.28,0.31,0.56
Ingrian:ingerian_V33586,32.72,48.37,3.24,4.76,0.00 ,0.00,0.00,2.08,6.57,1.70,0.48,0.00,0.09
Ingrian:ingerian_V42764,24.84,51.78,7.11,4.69,3.73 ,1.80,0.15,0.05,3.66,0.37,0.81,0.33,0.68
Ingrian:ingerian_V46386,31.99,51.67,5.20,0.00,0.00 ,0.00,0.74,0.00,7.66,1.83,0.52,0.00,0.39
Karels:karelian_V04898,28.04,43.55,5.06,7.43,4.17, 0.00,0.87,0.00,8.47,1.91,0.00,0.00,0.51
Karels:karelian_V11080,30.98,44.70,6.55,4.56,3.36, 0.97,1.74,0.00,4.76,1.73,0.00,0.60,0.04
Khanty:hant1,4.76,32.74,0.00,3.46,0.00,0.00,4.46,0 .00,47.62,5.88,1.08,0.00,0.00
Khanty:hant2,6.18,31.11,0.00,3.27,0.00,0.00,4.17,1 .42,46.04,6.81,0.84,0.00,0.17
Khanty:hant3,7.80,30.98,0.00,3.25,0.00,0.00,4.85,0 .00,46.86,6.26,0.00,0.00,0.00
Khanty:hant4,4.44,26.32,0.00,4.63,0.00,0.00,4.47,0 .00,54.83,5.31,0.00,0.00,0.00
Khanty:hant5,8.84,29.40,0.00,3.22,0.00,0.00,6.05,1 .21,45.66,5.26,0.28,0.00,0.07
Khanty:hant6,2.62,33.35,0.00,6.04,0.00,0.00,1.64,1 .77,46.13,5.69,1.88,0.04,0.82
Khanty:hant7,4.84,31.56,0.00,3.52,0.00,0.00,4.86,0 .79,47.94,6.50,0.00,0.00,0.00
Khanty:hant8,6.80,32.49,0.00,0.33,0.00,0.00,5.33,0 .00,47.88,7.17,0.00,0.00,0.00
Khanty:hant9,6.83,32.07,0.00,0.84,0.00,0.00,4.59,0 .95,49.29,5.11,0.32,0.00,0.00
Khanty:hant10,3.79,33.21,0.00,5.45,0.00,0.00,3.75, 0.84,45.92,5.69,1.35,0.00,0.00
Khanty:khanty_V32243,5.36,31.79,0.00,4.83,0.00,0.0 0,3.56,2.03,45.48,6.45,0.49,0.00,0.00
Latvians:latvian51E3,30.73,49.48,8.23,4.90,4.07,0. 00,0.00,0.98,0.23,1.17,0.21,0.00,0.00
Mansi:Mansi1,16.33,37.25,1.52,6.85,3.33,0.00,2.37, 0.59,28.55,2.06,0.93,0.23,0.00
Mansi:Mansi2,5.14,31.37,0.00,3.32,0.00,0.00,4.30,0 .00,47.31,7.63,0.00,0.33,0.61
Mansi:Mansi3,17.13,36.86,2.50,5.29,0.28,0.52,5.91, 0.18,28.36,2.19,0.36,0.42,0.00
Mansi:Mansi13,21.39,46.63,6.94,6.30,0.00,1.39,2.72 ,0.00,11.14,2.48,1.02,0.00,0.00
Mansi:Mansi15,23.44,45.74,6.47,5.13,5.51,0.00,3.66 ,0.47,7.13,1.57,0.00,0.87,0.00
Mansi:Mansi17,16.67,39.47,0.95,5.05,0.00,0.69,3.76 ,1.40,27.37,3.84,0.63,0.17,0.00
Mansi:Mansi19,24.18,48.64,5.74,8.32,2.61,0.37,0.00 ,0.00,7.56,2.30,0.00,0.00,0.29
Mansi:Mansi22,19.51,45.25,6.63,8.56,0.07,0.00,1.57 ,0.46,15.52,2.21,0.00,0.00,0.23
Mansi:Mansi23,26.72,44.40,8.24,5.42,2.63,0.00,2.39 ,0.00,7.80,1.20,0.64,0.56,0.00
Mansi:Mansi24,13.36,40.54,0.00,8.03,0.00,0.00,4.11 ,1.01,27.51,4.93,0.11,0.00,0.42
Mansi:Mansi25,17.39,41.56,4.06,5.95,0.00,1.21,2.88 ,0.00,23.19,3.27,0.01,0.49,0.00
Mansi:Mansi80,8.48,30.31,0.00,2.95,0.00,0.00,5.16, 1.25,45.78,5.81,0.27,0.00,0.00
Mansi:Mansi85,6.94,31.99,0.00,2.58,0.00,0.00,3.42, 1.89,45.71,6.11,0.90,0.00,0.46
Mansi:Mansi93,17.30,37.72,3.48,9.64,0.00,0.00,3.02 ,0.00,25.27,2.13,1.43,0.00,0.00
Mansi:Mansi110,2.01,30.88,0.00,5.21,0.00,0.00,2.87 ,0.23,50.93,6.53,1.35,0.00,0.00
Mansi:Mansi125,15.47,42.21,0.88,6.78,0.00,1.60,3.9 3,0.68,22.81,4.47,0.96,0.00,0.20
Mansi:Mansi128,9.39,28.91,0.00,4.53,0.00,0.00,5.70 ,0.28,45.22,5.54,0.00,0.00,0.43
Mansi:Mansi138,11.23,31.69,0.00,1.35,0.00,0.00,3.5 8,0.29,44.52,5.83,1.30,0.00,0.21
Mansi:Mansi172,11.72,38.61,0.00,4.16,0.00,0.00,5.0 5,1.88,33.16,4.15,0.25,0.00,1.02
Mansi:Mansi211,24.60,41.07,8.69,6.48,3.90,1.25,1.8 4,0.04,9.53,2.20,0.00,0.30,0.10
Mansi:Mansi218,20.09,38.39,0.00,10.10,0.00,0.00,1. 00,1.13,25.94,1.75,0.63,0.00,0.96
Mansi:Mansi228,4.83,33.35,0.00,3.55,0.00,0.00,4.85 ,2.65,45.12,5.51,0.00,0.13,0.00
Mansi:Mansi230,26.21,45.01,10.17,7.14,2.83,0.00,2. 37,0.00,4.46,1.08,0.22,0.13,0.37
Maris:Nenets986,12.70,44.99,1.37,9.59,0.00,0.18,2. 62,3.04,22.64,2.50,0.00,0.37,0.00
Poles:Poland135,29.38,41.03,7.90,7.31,4.79,1.37,1. 08,0.00,4.32,1.73,0.79,0.30,0.00
Poles:Poland148,31.90,53.67,6.89,2.31,0.00,0.57,0. 00,0.00,2.10,0.76,1.14,0.00,0.65
Poles:Poland149,26.62,44.75,3.52,10.34,2.40,0.20,1 .41,0.15,9.40,0.99,0.00,0.22,0.00
Poles:Poland150,26.40,48.55,8.11,6.42,6.97,0.00,1. 02,0.00,0.42,0.86,1.14,0.00,0.12
Poles:Poland151,23.96,54.30,9.70,6.99,1.64,0.00,1. 44,0.00,1.96,0.00,0.00,0.00,0.00
Russians_Central:C_Russian1006,23.32,48.37,9.17,6. 75,2.33,0.33,2.58,0.09,5.42,0.38,0.70,0.00,0.56
Russians_Central:C_Russian1012,27.70,45.71,9.09,3. 41,7.23,0.91,2.09,0.54,1.89,0.51,0.72,0.20,0.00
Saami_Kola:SaamiKola5,25.81,47.62,0.00,0.00,0.00,0 .00,2.17,0.70,19.01,3.28,0.57,0.64,0.20
Saami_Kola:SaamiKola6,23.93,46.99,1.08,0.00,0.00,0 .00,0.60,0.08,20.69,4.90,0.00,1.59,0.14
Saami_Kola:SaamiKola7,22.28,50.08,5.56,1.92,0.00,0 .00,3.32,0.56,12.98,2.40,0.00,0.66,0.24
Saami_Kola:SaamiKola25,23.30,47.14,1.60,0.97,0.00, 0.00,0.10,0.00,21.67,3.67,0.60,0.00,0.95
Saami_Kola:SaamiKola40,24.26,47.51,0.80,0.05,0.00, 0.00,1.85,0.09,20.88,3.28,0.83,0.00,0.45
Saami_Kola:SaamiKola47,29.53,47.74,1.62,0.59,0.94, 0.40,0.64,0.00,15.87,0.90,0.48,0.76,0.52
Saami_Kola:SaamiKola49,23.87,48.01,6.21,4.73,0.00, 0.00,1.39,0.67,12.61,1.44,0.09,0.99,0.00
Saami_Kola:SaamiKola74,25.36,46.27,5.23,0.00,0.00, 0.00,2.41,0.00,17.26,2.31,0.12,0.85,0.19
Saami_SWE:saami1,21.14,46.52,0.00,0.00,0.00,0.00,0 .85,2.29,24.46,3.28,0.31,0.00,1.13
Saami_SWE:saami2,22.76,43.01,0.00,0.00,0.00,0.00,1 .46,0.54,27.31,4.49,0.05,0.17,0.19
Saami_SWE:saami3,23.34,44.72,0.00,1.61,0.00,0.00,1 .92,0.00,24.51,2.69,0.59,0.62,0.00
Saami_SWE:saami4,27.43,45.92,0.00,0.91,0.00,0.00,0 .00,0.00,20.99,2.98,0.52,0.00,1.24
Saami_SWE:saami5,27.80,40.10,0.00,0.00,0.00,0.00,1 .34,1.49,23.29,4.76,0.32,0.00,0.90
Saami_SWE:saami6,28.20,43.69,0.00,0.00,0.00,0.00,2 .42,2.28,20.64,2.76,0.00,0.00,0.00
Saami_SWE:saami7,24.04,43.42,0.00,2.99,0.00,0.00,0 .00,0.85,23.19,4.76,0.66,0.00,0.09
Saami_SWE:saami8,26.84,42.00,0.00,0.00,0.00,0.00,1 .13,2.34,23.72,3.49,0.49,0.00,0.00
Saami_SWE:saami9,26.71,43.12,0.00,1.50,0.00,0.00,0 .76,1.79,22.80,3.32,0.00,0.00,0.00
Saami_SWE:saami11,22.71,43.21,0.00,0.00,0.00,0.00, 1.62,2.27,26.12,3.45,0.60,0.00,0.00
Saami_SWE:saami12,23.92,46.30,0.00,1.35,0.00,0.00, 1.01,0.00,22.82,3.08,0.62,0.00,0.90
Saami_SWE:saami13,24.71,44.28,0.00,0.98,0.00,0.00, 2.46,0.64,23.26,3.61,0.06,0.00,0.00
Saami_SWE:saami14,25.10,43.94,0.00,0.00,0.00,0.00, 1.19,1.45,22.51,4.71,1.11,0.00,0.00
Swedes:swede_V49245,39.89,37.58,10.25,3.76,2.26,1. 09,0.34,0.12,3.55,0.77,0.06,0.00,0.33
Tatars:Tatar1003,14.89,21.65,4.93,16.77,7.77,1.16, 8.96,7.82,13.94,1.37,0.29,0.44,0.00
Tatars:Tatar1008,22.83,40.11,5.09,8.06,6.62,0.00,2 .12,0.62,11.75,1.57,1.00,0.00,0.23
Vepsas:vepsa50,27.00,53.58,4.67,0.77,0.85,0.00,2.2 1,0.30,8.38,1.58,0.00,0.00,0.67
Vepsas:vepsian_V21441,28.33,47.68,4.07,6.10,0.00,0 .49,2.09,0.08,8.99,1.63,0.54,0.00,0.00

#K12b average
Buryats,3.34,25.01,0.03,0.92,8.95,32.50,0.38,0.00, 1.05,21.69,5.75,0.38
Estonians,3.39,2.62,0.07,0.23,21.13,64.24,0.69,0.0 2,0.50,0.17,6.93,0.01
Finns,3.49,6.36,0.23,0.35,19.90,62.76,0.69,0.00,1. 07,0.39,4.75,0.00
Gagauzes,4.76,1.07,0.65,0.00,25.60,29.59,0.08,0.36 ,7.28,1.38,29.22,0.00
Germans,7.34,0.90,0.24,0.44,37.43,39.86,0.00,0.00, 2.13,0.00,11.65,0.00
Ingrian,3.27,6.15,0.24,0.12,19.34,64.00,0.54,0.05, 0.97,0.55,4.58,0.19
Karels,4.86,6.26,0.00,0.00,19.16,57.82,0.73,0.08,1 .18,1.02,8.63,0.25
Khanty,8.10,47.12,0.00,0.15,0.91,33.68,1.40,0.01,0 .03,8.56,0.01,0.02
Latvians,5.53,1.07,0.00,0.45,22.46,61.31,0.00,0.00 ,0.00,0.00,9.15,0.03
Mansi,7.04,26.99,0.05,0.20,10.07,44.66,1.22,0.01,0 .27,5.02,4.46,0.00
Maris,7.69,22.76,0.00,0.51,9.91,46.08,0.00,0.00,0. 00,5.93,7.12,0.00
Poles,4.60,3.53,0.00,0.06,20.69,59.30,0.16,0.03,0. 62,0.81,10.21,0.00
Russians_Central,3.69,3.48,0.00,0.24,19.60,57.78,2 .10,0.00,1.32,0.60,11.20,0.00
Saami_Kola,3.59,17.23,0.02,0.14,14.72,58.87,1.03,0 .01,0.25,2.59,1.56,0.00
Saami_SWE,4.27,23.16,0.03,0.32,11.84,55.49,0.35,0. 02,0.00,4.51,0.00,0.00
Swedes,5.69,2.89,0.72,0.00,29.07,54.29,0.00,0.00,0 .73,0.00,6.46,0.16
Tatars,11.40,10.80,0.10,0.78,14.84,38.59,3.74,0.00 ,1.52,6.60,11.61,0.00
Vepsas,4.86,8.04,0.24,0.19,17.59,62.62,0.49,0.00,0 .23,1.44,4.18,0.10

#K12b
Buryats:buryat_V43501,3.34,25.01,0.03,0.92,8.95,32 .50,0.38,0.00,1.05,21.69,5.75,0.38
Estonians:100218,3.24,1.83,0.00,0.59,21.86,65.70,1 .99,0.00,0.00,0.00,4.80,0.00
Estonians:100228,3.74,1.12,0.00,1.23,18.59,68.67,0 .93,0.00,0.00,0.00,5.72,0.00
Estonians:100230,2.05,3.57,0.00,0.19,19.80,64.36,0 .24,0.00,0.08,0.00,9.71,0.00
Estonians:100232,4.24,2.77,0.00,0.00,22.87,65.62,0 .10,0.00,0.00,0.15,4.25,0.00
Estonians:100233,2.24,2.78,0.00,0.06,24.84,63.69,0 .71,0.00,0.00,0.00,5.68,0.00
Estonians:100235,2.80,2.15,0.22,0.00,19.43,65.95,1 .39,0.00,0.20,0.00,7.87,0.00
Estonians:100243,4.05,1.60,0.13,0.61,18.25,67.54,1 .61,0.00,0.00,0.00,6.22,0.00
Estonians:100248,2.21,3.41,0.00,0.79,22.86,65.69,0 .00,0.00,0.19,0.00,4.85,0.00
Estonians:100249,3.32,2.60,0.00,0.04,19.55,67.47,0 .19,0.00,0.00,0.27,6.56,0.00
Estonians:100252,2.13,1.86,0.00,0.11,20.33,67.07,1 .93,0.00,0.00,0.00,6.57,0.00
Estonians:100253,1.86,2.65,0.00,0.05,20.68,67.45,0 .69,0.00,1.25,0.00,5.37,0.00
Estonians:100254,4.45,3.13,0.26,0.00,20.20,65.66,1 .02,0.00,0.74,0.00,4.54,0.00
Estonians:100257,2.97,4.56,0.00,0.00,20.03,63.41,0 .58,0.00,0.00,0.61,7.83,0.00
Estonians:100258,0.09,1.92,0.00,0.00,20.22,65.78,1 .85,0.00,0.61,0.00,9.46,0.08
Estonians:100259,4.06,3.14,0.00,0.00,21.90,63.97,1 .18,0.00,0.59,0.09,4.90,0.16
Estonians:100261,2.93,1.96,0.00,0.35,20.00,64.50,1 .58,0.00,0.31,0.00,8.37,0.00
Estonians:100263,3.26,1.97,0.00,0.00,20.11,70.50,0 .61,0.00,0.66,0.00,2.89,0.00
Estonians:100520,4.35,2.09,0.37,0.00,20.93,65.06,0 .00,0.00,0.00,1.40,5.80,0.00
Estonians:100531,5.00,3.11,0.00,0.00,22.09,63.80,0 .52,0.18,0.00,0.63,4.65,0.00
Estonians:100550,2.98,2.65,0.00,0.41,21.36,65.67,0 .00,0.00,0.00,0.00,6.93,0.00
Estonians:100557,4.24,3.06,0.00,0.00,21.94,65.07,0 .34,0.00,0.00,0.00,5.34,0.00
Estonians:100558,2.03,1.84,0.00,0.51,21.31,65.13,0 .00,0.00,0.22,0.15,8.82,0.00
Estonians:400204,2.33,2.51,0.00,0.89,20.80,65.94,0 .52,0.00,0.39,0.00,6.63,0.00
Estonians:400206,4.78,5.37,0.00,0.36,24.42,62.25,0 .22,0.00,0.00,0.00,2.61,0.00
Estonians:400209,3.10,3.84,0.00,0.00,21.52,63.69,0 .15,0.00,0.00,0.04,7.67,0.00
Estonians:400210,3.51,3.51,0.00,1.11,19.76,61.49,0 .00,0.00,1.17,0.00,9.46,0.00
Estonians:400221,1.83,3.63,0.00,0.58,19.90,63.90,0 .38,0.00,1.14,0.00,8.64,0.00
Estonians:400235,7.16,1.35,0.00,0.00,20.42,50.32,0 .05,0.00,2.40,0.00,18.29,0.00
Estonians:400236,6.36,3.25,0.00,0.00,22.71,61.22,0 .09,0.00,0.00,0.10,6.19,0.08
Estonians:400237,2.33,1.87,0.15,0.00,18.59,60.41,1 .08,0.32,2.08,0.00,13.17,0.00
Estonians:400238,4.10,1.74,0.00,0.11,23.69,65.44,0 .87,0.00,0.00,0.20,3.85,0.00
Estonians:400240,2.92,2.27,0.00,0.00,21.44,67.62,0 .00,0.00,0.00,0.00,5.75,0.00
Estonians:evo_3,1.78,1.76,0.00,0.00,20.91,66.74,1. 75,0.00,0.53,0.27,6.26,0.00
Estonians:evo_4,3.55,2.11,0.00,0.22,21.30,67.26,1. 77,0.00,0.00,0.00,3.80,0.00
Estonians:evo_6,5.76,2.56,0.56,0.00,21.44,60.30,0. 00,0.12,0.00,0.66,8.60,0.00
Estonians:evo_7,4.36,2.80,0.95,0.00,24.79,48.38,0. 64,0.00,5.32,1.43,11.32,0.00
Finns:Finland65,4.19,6.85,0.00,0.00,20.39,63.53,0. 75,0.00,1.60,1.41,1.28,0.00
Finns:Finland67,4.56,7.73,0.77,0.00,19.55,62.74,0. 16,0.00,0.51,0.00,3.96,0.00
Finns:Finland69,3.22,8.50,0.00,0.00,19.96,64.10,0. 78,0.00,0.31,0.24,2.89,0.00
Finns:Finland74,3.38,7.66,0.00,1.54,20.63,63.97,0. 00,0.00,0.52,0.48,1.81,0.00
Finns:Finland76,4.29,6.32,0.00,0.00,19.55,65.61,0. 62,0.00,0.00,0.63,2.98,0.00
Finns:Finland78,2.31,5.48,0.00,0.00,19.19,62.08,1. 75,0.00,2.70,0.61,5.88,0.00
Finns:Finland84,3.38,3.71,0.16,1.45,21.15,60.81,0. 78,0.00,2.24,0.00,6.35,0.00
Finns:Finland86,2.95,8.42,0.00,0.55,18.57,66.01,0. 00,0.00,0.00,0.00,3.50,0.00
Finns:Finland87,3.33,7.83,0.94,0.19,20.95,65.42,0. 00,0.00,0.31,0.42,0.61,0.00
Finns:Finland94,4.39,3.85,0.00,0.60,19.84,63.62,0. 07,0.00,1.27,0.86,5.49,0.00
Finns:Finland95,3.50,7.35,0.00,0.00,17.96,61.37,1. 58,0.00,1.20,1.47,5.57,0.00
Finns:Finland97,1.97,6.74,0.00,0.62,18.46,66.44,0. 44,0.00,0.70,0.37,4.26,0.00
Finns:Finland101,2.70,5.84,2.53,0.30,21.08,48.71,0 .86,0.01,2.64,0.00,15.32,0.00
Finns:Finland106,5.23,5.16,0.00,0.00,21.74,61.33,0 .00,0.00,0.52,0.00,6.03,0.00
Finns:Finland109,1.54,0.82,0.00,0.70,22.39,64.16,1 .38,0.03,1.64,0.00,7.34,0.00
Finns:Finland111,2.14,6.70,0.00,0.00,18.03,63.66,2 .00,0.00,0.75,0.00,6.72,0.00
Finns:Finland117,4.51,6.19,0.00,0.34,21.17,64.27,0 .49,0.00,1.73,0.30,1.00,0.00
Finns:Finland118,4.85,4.87,0.00,0.31,18.65,60.92,0 .91,0.00,0.90,0.55,8.05,0.00
Finns:Finland119,3.91,10.88,0.00,0.00,18.88,63.76, 0.63,0.00,0.78,0.00,1.18,0.00
Gagauzes:Gagauz10,4.76,1.07,0.65,0.00,25.60,29.59, 0.08,0.36,7.28,1.38,29.22,0.00
Germans:German7,7.34,0.90,0.24,0.44,37.43,39.86,0. 00,0.00,2.13,0.00,11.65,0.00
Ingrian:ingerian_V06336,4.30,7.08,0.36,0.65,19.71, 64.39,0.85,0.00,0.92,0.00,1.49,0.25
Ingrian:ingerian_V22241,3.33,7.06,0.00,0.00,21.06, 63.21,0.95,0.30,1.66,0.00,2.44,0.00
Ingrian:ingerian_V24378,4.51,4.86,0.84,0.00,20.10, 61.07,0.30,0.00,0.32,0.00,7.67,0.32
Ingrian:ingerian_V33586,5.25,7.13,0.00,0.07,17.27, 65.98,0.00,0.00,0.00,1.61,2.68,0.00
Ingrian:ingerian_V42764,1.17,2.89,0.00,0.00,18.73, 62.31,0.07,0.00,1.53,1.38,11.53,0.40
Ingrian:ingerian_V46386,1.04,7.88,0.25,0.00,19.20, 67.05,1.08,0.00,1.37,0.31,1.66,0.15
Karels:karelian_V04898,6.54,7.59,0.00,0.00,19.08,5 5.53,0.00,0.00,0.88,2.02,7.94,0.41
Karels:karelian_V11080,3.18,4.93,0.00,0.00,19.23,6 0.12,1.46,0.16,1.49,0.03,9.32,0.09
Khanty:hant1,7.79,47.09,0.00,0.00,1.43,33.31,1.81, 0.00,0.00,8.57,0.00,0.00
Khanty:hant2,8.23,47.17,0.00,0.57,1.10,33.28,1.59, 0.00,0.00,8.07,0.00,0.00
Khanty:hant3,8.39,46.80,0.00,0.00,1.15,35.83,0.92, 0.00,0.05,6.85,0.00,0.00
Khanty:hant4,8.77,54.08,0.00,0.00,0.05,28.25,0.74, 0.00,0.00,8.11,0.00,0.00
Khanty:hant5,7.19,45.31,0.00,0.53,2.19,34.47,2.31, 0.01,0.00,7.99,0.00,0.00
Khanty:hant6,6.89,45.74,0.00,0.09,1.82,34.74,0.72, 0.00,0.00,9.87,0.12,0.00
Khanty:hant7,8.49,47.07,0.00,0.00,0.00,33.77,1.12, 0.09,0.00,9.46,0.00,0.00
Khanty:hant8,7.44,47.01,0.00,0.00,0.59,34.24,1.60, 0.00,0.22,8.91,0.00,0.00
Khanty:hant9,7.63,47.36,0.00,0.00,0.83,32.65,1.77, 0.00,0.07,9.69,0.00,0.00
Khanty:hant10,9.61,44.76,0.00,0.00,0.54,35.02,1.14 ,0.00,0.04,8.89,0.00,0.00
Khanty:khanty_V32243,8.64,45.88,0.00,0.51,0.35,34. 97,1.71,0.00,0.00,7.70,0.00,0.23
Latvians:latvian51E3,5.53,1.07,0.00,0.45,22.46,61. 31,0.00,0.00,0.00,0.00,9.15,0.03
Mansi:Mansi1,6.26,27.78,0.38,0.00,9.87,43.24,1.33, 0.02,0.00,3.93,7.19,0.00
Mansi:Mansi2,7.97,46.66,0.00,0.00,1.20,33.42,1.58, 0.00,0.00,9.17,0.00,0.00
Mansi:Mansi3,7.48,26.78,0.00,0.00,11.50,43.21,2.65 ,0.00,0.33,4.87,3.18,0.00
Mansi:Mansi13,5.95,11.61,0.13,0.00,15.63,54.92,1.5 8,0.00,1.44,2.07,6.67,0.00
Mansi:Mansi15,4.61,7.79,0.00,1.98,17.48,54.11,1.83 ,0.00,0.59,0.10,11.51,0.00
Mansi:Mansi17,6.50,28.67,0.00,1.11,12.00,44.88,1.4 5,0.00,0.00,3.21,2.18,0.00
Mansi:Mansi19,4.78,7.87,0.00,0.35,17.04,57.35,0.00 ,0.00,1.14,1.06,10.41,0.00
Mansi:Mansi22,4.28,14.69,0.00,0.00,14.14,54.90,0.3 3,0.00,0.00,3.39,8.28,0.00
Mansi:Mansi23,6.49,7.55,0.21,0.00,20.69,54.43,1.15 ,0.00,0.20,1.58,7.72,0.00
Mansi:Mansi24,8.66,28.21,0.00,0.00,9.47,45.44,1.28 ,0.00,0.00,5.61,1.33,0.00
Mansi:Mansi25,5.63,22.87,0.00,0.00,13.10,45.04,1.8 9,0.00,0.00,3.06,8.41,0.00
Mansi:Mansi80,9.06,43.94,0.00,0.00,0.70,35.29,1.66 ,0.00,0.00,9.35,0.00,0.00
Mansi:Mansi85,8.12,44.10,0.00,0.00,1.12,35.77,1.14 ,0.00,0.00,9.75,0.00,0.00
Mansi:Mansi93,6.30,23.33,0.00,0.00,10.94,46.18,1.1 9,0.00,0.00,4.88,7.17,0.00
Mansi:Mansi110,8.03,49.41,0.00,0.00,1.23,31.25,0.0 0,0.00,0.00,10.08,0.00,0.00
Mansi:Mansi125,6.46,23.83,0.00,0.60,8.85,48.91,1.9 6,0.00,1.61,4.10,3.67,0.00
Mansi:Mansi128,9.83,44.73,0.00,0.00,2.62,34.09,1.2 8,0.00,0.00,7.45,0.00,0.00
Mansi:Mansi138,5.77,43.47,0.14,0.00,3.71,36.09,1.2 8,0.00,0.21,9.34,0.00,0.00
Mansi:Mansi172,8.20,33.21,0.00,0.27,6.38,41.86,1.9 5,0.18,0.00,6.51,1.44,0.00
Mansi:Mansi211,6.04,9.43,0.00,0.00,19.62,50.72,0.6 9,0.00,0.67,2.04,10.78,0.00
Mansi:Mansi218,9.83,24.90,0.00,0.04,10.81,46.25,0. 13,0.00,0.00,4.88,3.05,0.11
Mansi:Mansi228,8.52,45.07,0.00,0.00,1.65,34.66,1.1 0,0.00,0.00,9.01,0.00,0.00
Mansi:Mansi230,7.11,4.96,0.25,0.27,21.95,55.25,0.6 6,0.00,0.00,0.00,9.55,0.00
Maris:Nenets986,7.69,22.76,0.00,0.51,9.91,46.08,0. 00,0.00,0.00,5.93,7.12,0.00
Poles:Poland135,5.16,5.07,0.00,0.00,23.04,54.11,0. 21,0.00,1.44,0.79,10.18,0.00
Poles:Poland148,3.34,2.87,0.00,0.00,22.24,65.47,0. 28,0.06,0.82,0.00,4.91,0.00
Poles:Poland149,6.53,7.80,0.00,0.00,15.98,55.09,0. 00,0.08,0.08,2.21,12.24,0.00
Poles:Poland150,3.67,0.46,0.00,0.28,21.27,59.60,0. 00,0.00,0.76,1.07,12.88,0.00
Poles:Poland151,4.29,1.43,0.00,0.00,20.90,62.22,0. 32,0.00,0.00,0.00,10.85,0.00
Russians_Central:C_Russian1006,4.70,4.63,0.00,0.47 ,17.08,58.83,2.27,0.00,0.30,0.54,11.19,0.00
Russians_Central:C_Russian1012,2.68,2.34,0.00,0.02 ,22.11,56.72,1.94,0.00,2.33,0.66,11.21,0.00
Saami_Kola:SaamiKola5,1.11,18.62,0.00,0.00,13.18,6 0.73,2.45,0.00,0.00,3.91,0.00,0.00
Saami_Kola:SaamiKola6,3.84,20.42,0.00,0.00,12.85,5 8.18,0.90,0.00,0.00,3.80,0.00,0.00
Saami_Kola:SaamiKola7,3.04,12.87,0.00,0.77,16.07,5 8.34,1.88,0.00,0.25,1.85,4.92,0.00
Saami_Kola:SaamiKola25,4.08,21.28,0.00,0.00,12.76, 58.55,0.60,0.00,0.00,2.71,0.02,0.00
Saami_Kola:SaamiKola40,4.18,19.97,0.00,0.00,13.32, 58.24,0.50,0.00,0.00,3.80,0.00,0.00
Saami_Kola:SaamiKola47,3.14,14.85,0.00,0.00,16.12, 60.65,0.09,0.00,1.39,1.60,2.17,0.00
Saami_Kola:SaamiKola49,4.85,12.84,0.16,0.35,16.30, 58.22,0.78,0.01,0.37,0.74,5.38,0.00
Saami_Kola:SaamiKola74,4.45,16.98,0.00,0.00,17.16, 58.05,1.01,0.03,0.00,2.32,0.00,0.01
Saami_SWE:saami1,2.38,24.09,0.00,0.00,10.64,56.27, 0.95,0.00,0.00,5.66,0.00,0.00
Saami_SWE:saami2,3.67,26.51,0.02,0.00,9.29,55.02,0 .00,0.03,0.00,5.46,0.00,0.00
Saami_SWE:saami3,5.79,23.18,0.00,0.58,11.87,54.11, 0.54,0.17,0.00,3.76,0.00,0.00
Saami_SWE:saami4,4.12,19.91,0.19,0.00,13.60,58.61, 0.00,0.00,0.00,3.58,0.00,0.00
Saami_SWE:saami5,4.27,23.21,0.14,0.00,12.35,53.77, 0.21,0.00,0.00,6.05,0.00,0.00
Saami_SWE:saami6,4.12,20.80,0.00,0.68,14.39,55.36, 0.74,0.00,0.00,3.91,0.00,0.00
Saami_SWE:saami7,4.75,24.28,0.00,0.89,10.85,55.98, 0.00,0.00,0.00,3.25,0.00,0.00
Saami_SWE:saami8,3.24,22.70,0.00,0.00,13.39,54.42, 0.00,0.00,0.00,6.25,0.00,0.00
Saami_SWE:saami9,5.08,21.99,0.00,0.00,12.80,54.80, 0.00,0.00,0.00,5.34,0.00,0.00
Saami_SWE:saami11,4.80,25.25,0.10,0.00,9.67,53.89, 0.57,0.00,0.00,5.72,0.00,0.00
Saami_SWE:saami12,5.13,22.77,0.00,0.00,12.92,55.38 ,1.27,0.00,0.00,2.53,0.00,0.00
Saami_SWE:saami13,3.97,22.46,0.00,0.00,11.70,56.74 ,0.00,0.00,0.00,5.12,0.00,0.00
Saami_SWE:saami14,4.21,23.87,0.00,2.04,10.48,57.08 ,0.32,0.00,0.00,2.00,0.00,0.00
Swedes:swede_V49245,5.69,2.89,0.72,0.00,29.07,54.2 9,0.00,0.00,0.73,0.00,6.46,0.16
Tatars:Tatar1003,14.43,11.33,0.21,1.25,12.09,27.89 ,5.78,0.00,3.05,10.48,13.49,0.00
Tatars:Tatar1008,8.37,10.28,0.00,0.31,17.60,49.29, 1.70,0.00,0.00,2.71,9.73,0.00
Vepsas:vepsa50,3.23,8.02,0.24,0.00,17.61,63.59,0.7 2,0.00,0.00,1.38,5.21,0.00
Vepsas:vepsian_V21441,6.49,8.05,0.24,0.38,17.57,61 .66,0.26,0.00,0.46,1.51,3.16,0.21

K13 updated only has a combined average for Mordovians, but here's separate results for Erzya and Moksha. The samples are from Jeong et al. 2019.

Erzya:MOE-001,18.69,51.58,7.78,5.87,4.07,0.20,1.37,2.61,5.95 ,1.07,0.12,0.70,0.00
Erzya:MOE-002,22.82,46.96,4.83,7.27,4.18,0.00,3.89,1.76,5.78 ,0.79,1.57,0.15,0.00
Erzya:MOE-010,21.55,45.63,7.96,11.00,0.00,1.36,0.94,0.92,7.7 0,1.77,0.90,0.26,0.00
Erzya:MOE-036,21.01,46.41,9.81,7.69,3.33,0.00,2.54,0.07,7.87 ,0.76,0.38,0.00,0.14
Erzya:MOE-043,21.98,48.45,8.33,7.03,0.32,0.00,3.29,0.43,6.84 ,1.68,0.52,1.13,0.00
Erzya:MOE-045,20.97,48.23,5.41,9.37,4.43,0.00,1.27,0.46,6.50 ,2.26,1.12,0.00,0.00
Erzya:MOE-475,23.90,50.73,6.68,6.15,1.44,1.23,1.16,0.00,7.27 ,0.60,0.84,0.00,0.00
Erzya:MOE-485,24.84,45.69,6.23,6.04,3.88,1.29,3.00,1.86,5.55 ,0.60,1.04,0.00,0.00
Erzya:MOE-491,24.61,44.42,10.25,9.27,0.00,0.30,2.09,1.97,4.6 4,1.08,0.70,0.00,0.67
Erzya:MOE-492,24.14,45.76,7.08,6.73,6.28,0.00,1.08,0.46,6.56 ,1.70,0.00,0.20,0.00
Erzya:MOE-495,28.71,47.77,4.58,5.58,3.03,2.20,3.47,0.00,2.44 ,1.35,0.87,0.00,0.00
Erzya:MOE-497,23.30,51.79,4.07,6.86,2.77,0.06,1.07,2.48,4.69 ,2.34,0.28,0.00,0.28
Moksha:MOE-014,19.51,44.70,12.20,6.62,3.82,0.00,2.66,0.75,7.2 5,2.33,0.17,0.00,0.00
Moksha:MOE-015,24.29,50.71,5.18,6.53,4.04,1.69,0.09,0.00,5.26 ,1.34,0.17,0.69,0.00
Moksha:MOE-020,18.49,48.54,11.76,8.13,2.07,0.00,1.53,1.10,5.7 5,1.99,0.00,0.00,0.64
Moksha:MOE-025,21.73,46.06,4.47,11.47,5.92,0.00,2.59,0.00,5.9 9,1.46,0.06,0.23,0.00
Moksha:MOE-433,30.25,41.16,9.72,2.22,4.36,1.44,1.43,1.28,4.00 ,2.39,0.00,1.74,0.00
Moksha:MOE-445,23.28,46.96,3.74,8.13,5.46,1.70,0.00,2.14,5.32 ,1.55,0.60,0.00,1.11
Moksha:MOE-450,24.34,47.80,4.46,8.20,4.18,1.74,0.56,0.00,5.73 ,0.78,1.28,0.89,0.06
Moksha:MOE-451,26.37,48.05,7.34,3.79,3.15,0.00,2.23,2.21,5.99 ,0.61,0.27,0.00,0.00
Moksha:MOE-452,25.36,45.61,4.10,9.13,5.93,0.75,0.14,2.05,5.35 ,0.77,0.01,0.00,0.81
Moksha:MOE-455,23.32,47.93,6.66,7.59,2.67,2.12,1.74,0.03,6.04 ,0.45,0.64,0.82,0.00

Leto

10-27-2021, 10:33 PM

Thanks! The old Estonian average is not too different from this one but I think we can still replace it.
For some odd reason the Polish average is straight up Russian, lol

Komintasavalta

10-27-2021, 11:26 PM

Thanks! The old Estonian average is not too different from this one but I think we can still replace it.
For some odd reason the Polish average is straight up Russian, lol

Some of those are the infamous Estonian Poles from Behar 2013. The samples that got the highest Baltic are Poland151 (54.3%) and Poland148 (53.7%). In one-to-many on GEDmatch, Poland151 (XD1211284) got some Latvians among the closest matches, and Poland148 (KC6230115) got Estonians and Finns (https://www.eupedia.com/forum/threads/38292-Polish-DNA-from-studies-on-GEDmatch?p=573169&viewfull=1#post573169).

Poland149 even got 9.4% Siberian in my K13 run. In this PCA that is based on K13 multiplied by MDS of FST, it actually plots further east on PC1 than three Mansi samples:

https://i.ibb.co/55QGMS4/1.png

In a real PCA of the same samples that I made with PLINK, PC2 differentiates Saami from other populations, because even after accounting for FST, K13 underestimates the distance of Saami to other Northern Europeans. But even here, Poland149 plots further east on PC1 than three of the Mansi samples:

https://i.ibb.co/25KTvm3/2.png

Lucas

10-28-2021, 12:23 PM

Yes "Estonian Poles" are the most ridiculous reference still used in academic genetics of European populations.

Komintasavalta

11-02-2021, 02:17 AM

Literally no one wants to convert the Tajiks and Kumyks from Yunusbayev

Here's all samples from Yunusbayev et al. 2011, "The Caucasus as an Asymmetric Semipermeable Barrier to Ancient Human Migrations": https://evolbio.ut.ee/caucasus/, https://academic.oup.com/mbe/article/29/1/359/1750206.

#K12b
Abhkasian,17.18,0.99,0.08,0.46,1.55,12.54,0.29,0.0 3,1.72,0.61,64.45,0.09
Armenian,17.61,0.09,0.12,0.15,9.31,3.89,0.48,0.00, 13.76,0.09,54.50,0.00
Balkar,15.41,4.10,0.00,0.55,2.35,20.78,0.41,0.00,0 .72,3.30,52.38,0.00
Bulgarian,2.44,0.68,0.66,0.06,24.84,34.78,0.51,0.0 1,5.84,0.55,29.62,0.02
Chechen,21.28,2.24,0.02,0.72,2.47,23.65,0.34,0.01, 1.45,0.85,46.97,0.00
Kumyk,20.17,3.47,0.00,0.58,3.16,18.98,0.44,0.03,3. 58,3.90,45.68,0.02
Kurd,27.49,0.91,0.43,0.63,5.95,5.97,1.55,0.15,13.6 3,0.17,43.10,0.01
Mordovian,3.46,6.09,0.06,0.77,11.85,62.86,1.04,0.0 0,1.03,0.99,11.85,0.00
Nogai_Kuban,13.00,10.64,0.23,0.74,4.75,21.83,0.66, 0.00,0.70,11.84,35.61,0.00
North_Ossetian,17.26,4.00,0.13,0.34,1.24,18.84,0.1 6,0.03,0.57,3.74,53.69,0.00
Tajik,33.22,6.73,0.32,1.22,4.18,18.19,7.11,0.02,2. 92,7.87,18.21,0.00
Turkmen,26.94,7.19,0.65,1.95,4.87,10.76,5.57,0.11, 6.79,7.81,27.28,0.08
Ukranian,1.32,0.93,0.19,0.24,16.72,60.89,0.81,0.01 ,2.78,0.46,15.64,0.00

#K13
Abhkasian,1.26,3.94,11.86,64.89,13.20,0.97,0.68,1. 70,0.55,0.14,0.51,0.19,0.09
Armenian,1.69,1.16,10.48,40.00,40.15,3.83,1.74,0.2 8,0.06,0.14,0.37,0.03,0.05
Balkar,5.60,11.62,9.75,53.47,9.20,0.38,0.78,3.24,4 .35,0.62,0.52,0.30,0.18
Bulgarian,12.50,32.63,20.44,9.49,21.88,0.87,0.29,0 .57,0.42,0.29,0.41,0.10,0.10
Chechen,9.72,13.53,4.10,58.72,5.49,2.04,1.43,1.40, 1.68,1.04,0.61,0.16,0.08
Kumyk,6.66,11.29,6.58,49.47,12.61,1.86,2.57,2.76,4 .25,0.95,0.47,0.40,0.14
Kurd,2.99,2.97,4.27,44.58,32.08,4.58,6.02,0.46,0.6 6,0.58,0.47,0.01,0.32
Mordovian,9.33,63.95,6.14,6.35,3.34,0.65,1.46,0.85 ,5.96,1.08,0.32,0.23,0.35
Nogai_Kuban,5.81,16.39,7.82,36.74,6.32,1.25,1.78,7 .94,14.13,0.97,0.46,0.30,0.08
North_Ossetian,3.17,11.10,9.99,56.73,8.09,0.79,0.8 7,2.84,4.74,0.50,0.53,0.47,0.17
Tajik,10.40,11.56,0.44,40.69,4.44,0.85,15.21,5.12, 8.31,1.97,0.38,0.31,0.32
Turkmen,4.82,7.44,3.39,36.18,17.06,1.97,11.32,6.21 ,9.27,1.19,0.39,0.26,0.50
Ukranian,13.41,59.61,9.85,3.83,8.06,1.63,0.98,0.59 ,0.78,0.44,0.41,0.09,0.32

#K12b
Abhkasian:abh100,18.33,1.05,0.67,0.43,2.85,14.01,0 .41,0.00,5.48,1.34,55.43,0.00
Abhkasian:abh107,20.97,1.62,0.00,0.38,2.81,11.28,0 .00,0.00,5.03,0.00,57.90,0.00
Abhkasian:abh119,18.54,1.20,0.00,0.31,0.00,10.71,0 .00,0.00,0.00,1.04,68.21,0.00
Abhkasian:abh122,12.88,0.72,0.00,0.00,0.00,12.85,0 .44,0.00,0.00,1.71,71.40,0.00
Abhkasian:abh133,18.94,0.00,0.00,0.46,0.00,9.34,0. 00,0.00,0.00,0.55,70.70,0.00
Abhkasian:abh135,15.95,0.15,0.00,1.08,1.36,11.93,1 .09,0.00,0.00,0.00,68.43,0.00
Abhkasian:abh137,16.20,0.85,0.00,1.18,0.78,10.06,0 .00,0.00,1.46,0.00,69.46,0.00
Abhkasian:abh147,18.25,0.22,0.00,1.22,0.00,11.23,0 .00,0.00,0.00,0.00,69.08,0.00
Abhkasian:abh154,17.11,0.19,0.00,0.62,0.00,7.31,0. 00,0.00,0.64,1.09,73.04,0.00
Abhkasian:abh165,9.52,2.98,0.00,0.48,9.75,36.66,1. 01,0.07,3.72,0.00,35.80,0.00
Abhkasian:abh24,18.60,0.16,0.75,0.00,4.64,8.93,1.6 0,0.00,6.00,0.91,56.66,1.74
Abhkasian:abh27,15.48,2.00,0.00,0.12,0.38,11.36,0. 00,0.00,0.00,0.00,70.66,0.00
Abhkasian:abh41,21.33,0.49,0.00,0.11,2.89,13.43,0. 00,0.00,4.50,1.66,55.60,0.00
Abhkasian:abh45,14.59,0.65,0.00,0.97,0.00,13.00,0. 00,0.00,0.00,0.00,70.80,0.00
Abhkasian:abh53,16.02,1.85,0.00,0.00,0.19,12.43,0. 50,0.00,0.00,1.50,67.50,0.00
Abhkasian:abh60,17.34,2.12,0.00,0.02,0.00,10.84,0. 16,0.00,0.00,0.00,69.52,0.00
Abhkasian:abh71,19.20,1.64,0.16,0.20,0.52,9.71,0.0 0,0.52,0.00,0.53,67.52,0.00
Abhkasian:abh74,19.92,0.90,0.00,0.20,4.92,14.32,0. 15,0.00,7.15,1.17,51.26,0.00
Abhkasian:abh85,16.34,0.00,0.00,1.10,0.00,10.90,0. 00,0.00,0.46,0.80,70.40,0.00
Abhkasian:abh9,18.19,0.96,0.00,0.25,0.00,10.55,0.4 7,0.00,0.00,0.00,69.59,0.00
Armenian:armenia102,16.16,0.00,0.10,0.00,6.38,7.13 ,0.85,0.00,10.85,0.42,58.12,0.00
Armenian:armenia106,19.43,0.00,0.00,0.00,7.58,5.78 ,1.27,0.00,11.40,0.00,54.54,0.00
Armenian:armenia139,15.72,0.00,0.08,0.00,9.64,0.72 ,0.00,0.00,17.71,0.33,55.80,0.00
Armenian:armenia162,16.82,0.00,0.00,0.00,7.72,3.96 ,0.00,0.00,15.96,0.00,55.55,0.00
Armenian:armenia176,17.71,0.00,0.01,0.88,11.03,2.0 9,0.07,0.00,13.33,0.00,54.89,0.00
Armenian:armenia191,18.61,0.45,0.00,0.00,8.18,6.97 ,0.00,0.00,10.49,0.19,55.11,0.00
Armenian:armenia279,16.02,0.00,0.92,0.63,9.09,0.30 ,0.00,0.00,17.08,0.00,55.97,0.00
Armenian:armenia293,18.44,0.00,0.00,0.51,8.23,3.66 ,1.15,0.00,12.91,0.00,55.11,0.00
Armenian:armenia3,19.21,0.12,0.00,0.00,10.82,5.57, 0.00,0.00,10.32,0.00,53.95,0.00
Armenian:armenia36,16.82,0.33,0.00,0.00,8.59,2.25, 0.47,0.00,14.06,0.00,57.48,0.00
Armenian:armenia7,16.27,0.00,0.62,0.00,12.34,5.34, 0.12,0.00,16.14,0.20,48.98,0.00
Armenian:armenia71,19.71,0.00,0.14,0.00,7.22,5.93, 1.20,0.00,13.73,0.00,52.08,0.00
Armenian:armenia73,20.73,0.00,0.00,0.24,9.86,3.77, 0.17,0.00,12.40,0.00,52.84,0.00
Armenian:armenia80,15.15,0.32,0.03,0.06,12.61,5.38 ,0.00,0.00,17.06,0.00,49.37,0.00
Armenian:armenia86,17.69,0.00,0.00,0.00,9.53,1.58, 1.90,0.00,11.73,0.00,57.56,0.00
Armenian:armenia91,17.34,0.24,0.00,0.14,10.10,1.86 ,0.42,0.00,15.03,0.30,54.57,0.00
Balkar:bal102,19.43,3.33,0.00,2.33,3.72,19.70,0.00 ,0.00,0.00,1.97,49.53,0.00
Balkar:bal108,17.70,4.12,0.00,0.00,0.00,17.74,0.00 ,0.00,0.00,3.96,56.48,0.00
Balkar:bal115,15.24,4.20,0.00,1.17,0.00,20.47,0.01 ,0.00,0.00,1.94,56.97,0.00
Balkar:bal124,16.23,3.63,0.00,1.02,0.03,22.02,0.00 ,0.00,0.00,0.71,56.37,0.00
Balkar:bal136,16.07,2.68,0.00,0.00,2.65,19.81,0.84 ,0.00,0.00,4.11,53.83,0.00
Balkar:bal14,11.62,5.08,0.00,0.00,0.00,19.40,1.86, 0.00,0.94,3.75,57.36,0.00
Balkar:bal149,8.02,3.82,0.00,0.00,7.41,38.78,0.00, 0.00,0.79,2.68,38.50,0.00
Balkar:bal22,13.09,3.94,0.00,0.39,0.00,18.99,0.03, 0.00,0.00,4.62,58.93,0.00
Balkar:bal26,14.39,5.20,0.00,0.00,2.15,19.82,0.98, 0.00,2.87,2.98,51.61,0.00
Balkar:bal31,12.14,3.49,0.00,0.93,10.12,32.80,0.33 ,0.00,3.46,2.84,33.89,0.00
Balkar:bal32,15.89,2.64,0.00,1.21,1.56,16.42,0.91, 0.00,0.00,3.12,58.24,0.00
Balkar:bal42,15.50,5.64,0.00,0.00,3.11,17.42,0.00, 0.00,0.00,3.98,54.35,0.00
Balkar:bal45,18.13,3.49,0.00,0.46,0.99,17.46,0.50, 0.00,0.00,2.23,56.75,0.00
Balkar:bal50,17.87,3.96,0.00,0.41,7.15,19.92,0.00, 0.00,3.27,2.67,44.75,0.00
Balkar:bal64,17.74,5.31,0.00,0.51,3.80,17.27,0.00, 0.00,0.92,5.57,48.88,0.00
Balkar:bal7,13.52,4.67,0.00,0.00,0.00,19.69,0.00,0 .00,0.00,5.20,56.91,0.00
Balkar:bal80,18.34,3.45,0.00,0.00,0.00,20.97,0.02, 0.00,0.00,4.33,52.88,0.00
Balkar:bal88,12.61,3.77,0.00,0.00,0.00,20.08,2.40, 0.00,0.25,3.40,57.49,0.00
Balkar:bal97,19.20,5.50,0.00,2.09,2.01,16.00,0.00, 0.00,1.09,2.63,51.48,0.00
Bulgarian:Bulgaria1,1.65,1.85,0.48,0.19,24.47,32.1 4,0.08,0.00,5.58,0.21,33.35,0.00
Bulgarian:Bulgaria2,1.94,1.25,0.00,0.20,25.86,35.5 9,0.00,0.00,5.85,0.00,29.31,0.00
Bulgarian:Bulgaria25,0.33,0.13,1.25,0.13,25.07,40. 25,1.51,0.00,5.13,0.00,26.19,0.00
Bulgarian:Bulgaria26,1.71,1.04,0.81,0.30,22.28,34. 26,0.93,0.00,5.71,0.00,32.98,0.00
Bulgarian:Bulgaria3,4.33,0.69,1.97,0.00,24.59,31.2 9,0.00,0.14,6.53,0.00,30.45,0.00
Bulgarian:Bulgaria33,3.60,1.14,0.00,0.00,23.31,32. 84,1.42,0.00,6.20,0.00,31.49,0.00
Bulgarian:Bulgaria37,0.73,0.00,1.24,0.00,24.56,36. 45,1.36,0.01,4.71,1.02,29.76,0.18
Bulgarian:Bulgaria39,0.00,0.00,0.99,0.00,24.20,39. 84,1.08,0.00,4.65,1.14,28.10,0.00
Bulgarian:Bulgaria4,5.06,0.00,0.95,0.00,27.50,34.9 4,0.00,0.00,5.32,1.16,25.07,0.00
Bulgarian:Bulgaria5,5.04,0.22,0.84,0.00,26.05,34.9 9,0.00,0.00,6.64,0.31,25.91,0.00
Bulgarian:Bulgaria6,4.14,0.42,0.00,0.00,23.94,35.2 2,0.22,0.00,4.90,0.83,30.31,0.02
Bulgarian:Bulgaria7,2.63,0.00,0.00,0.00,25.02,29.8 9,0.00,0.00,8.86,1.15,32.46,0.00
Bulgarian:Bulgaria8,0.53,2.05,0.00,0.00,26.05,34.4 6,0.00,0.00,5.85,1.35,29.72,0.00
Chechen:ch101,15.08,1.91,0.00,1.09,3.02,35.24,0.87 ,0.00,0.00,0.07,42.71,0.00
Chechen:ch109,24.83,2.39,0.00,0.00,6.45,23.29,1.05 ,0.00,3.75,1.01,37.23,0.00
Chechen:ch11,21.09,1.60,0.00,1.44,7.24,20.56,0.14, 0.00,4.30,1.71,41.94,0.00
Chechen:ch113,17.80,1.98,0.31,0.75,0.00,24.81,0.76 ,0.00,0.00,1.09,52.50,0.00
Chechen:ch126,23.47,1.94,0.00,1.62,0.98,20.83,0.00 ,0.00,0.00,0.00,51.17,0.00
Chechen:ch131,23.38,1.37,0.00,0.00,0.00,22.99,0.00 ,0.00,0.00,2.29,49.97,0.00
Chechen:ch150,22.23,1.99,0.00,0.26,0.00,22.26,0.00 ,0.00,0.00,0.93,52.33,0.00
Chechen:ch16,21.66,2.40,0.00,0.00,0.00,22.31,0.75, 0.00,3.08,1.74,48.07,0.00
Chechen:ch170,20.99,1.50,0.00,0.00,0.00,20.02,0.00 ,0.00,2.25,1.90,53.35,0.00
Chechen:ch174,21.20,3.87,0.00,1.00,2.04,21.78,0.00 ,0.00,0.00,0.00,50.11,0.00
Chechen:ch179,23.31,2.27,0.00,0.72,0.00,22.61,0.20 ,0.00,0.64,0.00,50.25,0.00
Chechen:ch193,18.82,2.78,0.00,0.00,0.00,21.10,0.00 ,0.00,1.21,1.35,54.74,0.00
Chechen:ch21,23.68,1.75,0.00,1.26,4.49,23.21,0.00, 0.00,2.75,1.58,41.28,0.00
Chechen:ch3,20.10,2.67,0.00,0.60,0.54,24.95,0.00,0 .00,0.53,0.01,50.60,0.00
Chechen:ch31,22.62,1.78,0.00,0.00,6.79,21.52,0.43, 0.00,2.95,1.04,42.85,0.00
Chechen:ch34,24.44,0.00,0.00,1.32,0.00,22.10,0.00, 0.00,0.62,2.27,49.25,0.00
Chechen:ch55,21.02,3.88,0.00,0.56,5.80,26.58,0.85, 0.00,4.15,0.00,37.17,0.00
Chechen:ch60,18.27,2.30,0.00,0.93,10.36,26.26,0.82 ,0.28,2.72,0.00,38.06,0.00
Chechen:ch76,19.98,2.88,0.00,2.30,0.56,26.34,0.00, 0.00,0.00,0.00,47.93,0.00
Chechen:ch86,21.66,3.51,0.00,0.56,1.11,24.33,0.94, 0.00,0.00,0.06,47.83,0.00
Kumyk:Kumyk22,20.22,3.79,0.00,0.17,1.08,18.17,0.00 ,0.00,5.91,3.50,47.17,0.00
Kumyk:kumyks1,21.54,5.94,0.00,0.00,7.30,18.25,0.00 ,0.00,1.46,6.34,39.18,0.00
Kumyk:kumyks10,21.74,0.82,0.00,0.00,2.29,20.56,0.0 0,0.00,1.29,3.81,49.49,0.00
Kumyk:kumyks108,22.20,1.11,0.00,1.38,0.00,18.87,0. 00,0.00,2.55,4.89,49.00,0.00
Kumyk:kumyks11,17.54,4.21,0.00,0.25,3.48,18.94,1.3 5,0.00,1.33,6.63,46.27,0.00
Kumyk:kumyks110,22.20,2.68,0.00,0.00,0.88,22.14,0. 00,0.00,1.23,4.35,46.52,0.00
Kumyk:kumyks111,19.01,3.20,0.00,1.66,1.17,17.71,1. 41,0.00,5.65,0.66,49.55,0.00
Kumyk:kumyks13,20.02,2.24,0.00,0.53,4.87,14.20,0.5 9,0.37,7.08,4.83,44.96,0.31
Kumyk:kumyks15,23.25,2.51,0.00,0.31,6.70,14.78,1.2 7,0.00,4.46,3.53,43.19,0.00
Kumyk:kumyks4,14.88,3.88,0.00,1.21,1.05,24.22,0.21 ,0.00,3.30,2.97,48.28,0.00
Kumyk:kumyks5,18.95,4.12,0.00,0.49,7.18,20.55,0.00 ,0.00,4.21,5.02,39.48,0.00
Kumyk:kumyks6,20.62,4.25,0.00,0.00,4.81,19.46,0.92 ,0.00,1.69,3.69,44.56,0.00
Kumyk:kumyks7,18.41,4.22,0.00,1.73,0.00,19.43,0.37 ,0.00,6.47,2.13,47.23,0.00
Kumyk:kumyks8,21.74,5.63,0.00,0.45,3.45,18.44,0.00 ,0.00,3.44,2.25,44.60,0.00
Kurd:kurd1101,27.62,0.85,2.45,0.19,5.79,7.24,1.28, 0.25,11.91,0.26,42.09,0.07
Kurd:kurd1156,28.57,2.62,0.00,0.01,8.41,0.50,0.51, 0.00,14.39,0.26,44.75,0.00
Kurd:kurd1159,30.14,0.00,0.00,1.65,3.57,8.51,0.13, 0.40,14.40,0.00,41.21,0.00
Kurd:kurd1160,28.37,0.00,0.00,0.99,7.18,5.51,2.20, 0.07,12.68,0.00,43.00,0.00
Kurd:kurd1173,21.59,0.71,0.15,0.91,2.50,8.41,4.34, 0.17,14.11,0.00,47.11,0.00
Kurd:kurd1198,28.66,1.28,0.00,0.03,8.23,5.66,0.87, 0.00,14.30,0.50,40.47,0.00
Mordovian:mordovia1,6.38,7.87,0.41,0.00,15.90,56.4 9,1.99,0.00,0.78,0.65,9.52,0.00
Mordovian:mordovia10,0.00,7.50,0.00,0.00,7.39,66.4 7,1.84,0.00,1.94,0.85,14.00,0.00
Mordovian:mordovia11,3.19,9.04,0.00,0.00,10.86,62. 92,1.50,0.00,0.55,0.00,11.94,0.00
Mordovian:mordovia12,4.42,4.58,0.00,0.66,17.40,57. 73,1.31,0.00,0.99,1.53,11.39,0.00
Mordovian:mordovia13,4.81,6.61,0.00,0.35,11.08,65. 25,0.00,0.00,2.70,0.45,8.75,0.00
Mordovian:mordovia14,2.47,5.36,0.00,1.04,10.24,62. 91,0.83,0.00,3.12,1.02,13.01,0.00
Mordovian:mordovia15,4.16,5.97,0.00,3.25,14.41,62. 91,0.00,0.00,0.60,0.00,8.71,0.00
Mordovian:mordovia2,1.22,5.21,0.00,1.32,11.27,64.9 0,1.56,0.00,1.47,0.00,13.05,0.00
Mordovian:mordovia3,4.52,6.58,0.00,0.00,9.57,65.85 ,0.93,0.00,0.75,2.13,9.67,0.00
Mordovian:mordovia4,4.59,4.38,0.00,1.26,10.11,64.7 7,0.24,0.00,0.00,2.87,11.78,0.00
Mordovian:mordovia5,1.85,5.27,0.00,0.84,12.64,62.2 3,2.22,0.00,0.10,1.61,13.23,0.00
Mordovian:mordovia6,4.28,6.81,0.00,1.25,14.56,61.4 6,0.00,0.00,0.04,0.00,11.60,0.00
Mordovian:mordovia7,4.76,6.45,0.00,1.58,8.83,62.79 ,0.57,0.00,1.53,0.00,13.48,0.00
Mordovian:mordovia8,0.00,5.25,0.46,0.00,10.23,64.6 4,2.46,0.00,0.00,1.35,15.61,0.00
Mordovian:mordovia9,5.28,4.41,0.00,0.00,13.29,61.6 4,0.14,0.00,0.83,2.35,12.05,0.00
Nogai_Kuban:nogay1,12.80,8.64,0.30,1.35,0.29,24.17 ,0.98,0.00,0.83,9.56,41.10,0.00
Nogai_Kuban:nogay10,15.27,11.38,0.00,2.12,2.93,21. 10,0.00,0.00,0.00,14.86,32.34,0.00
Nogai_Kuban:nogay11,11.14,12.09,0.81,0.00,5.77,23. 16,1.04,0.00,2.00,13.56,30.43,0.00
Nogai_Kuban:nogay12,13.43,11.58,0.60,0.04,4.37,19. 22,0.25,0.00,0.04,8.51,41.96,0.00
Nogai_Kuban:nogay13,12.58,11.36,0.00,0.00,1.45,20. 95,0.76,0.00,0.93,15.35,36.63,0.00
Nogai_Kuban:nogay14,11.18,11.54,0.00,0.00,6.16,19. 24,0.40,0.00,0.06,16.30,35.13,0.00
Nogai_Kuban:nogay15,11.43,16.50,0.33,2.05,5.65,19. 47,1.33,0.00,0.03,15.73,27.48,0.00
Nogai_Kuban:nogay16,12.21,10.96,0.00,0.00,5.28,21. 12,0.54,0.00,0.00,13.21,36.67,0.00
Nogai_Kuban:nogay2,14.06,11.42,1.35,1.93,1.87,18.1 7,0.00,0.00,0.00,10.42,40.78,0.00
Nogai_Kuban:nogay3,15.05,10.03,0.00,0.00,9.01,22.5 9,0.00,0.00,3.02,11.86,28.44,0.00
Nogai_Kuban:nogay4,10.73,12.60,0.00,1.76,3.97,20.0 3,0.93,0.00,0.00,11.11,38.87,0.00
Nogai_Kuban:nogay5,15.91,9.40,0.30,0.68,7.97,19.58 ,2.09,0.00,1.85,11.35,30.86,0.00
Nogai_Kuban:nogay6,10.03,6.75,0.00,0.56,8.48,29.89 ,1.53,0.00,0.43,8.08,34.24,0.00
Nogai_Kuban:nogay7,13.23,8.51,0.00,0.00,5.89,27.94 ,0.00,0.00,0.76,8.66,35.01,0.00
Nogai_Kuban:nogay8,14.71,10.28,0.00,0.00,3.80,23.4 3,0.00,0.00,1.28,10.01,36.50,0.00
Nogai_Kuban:nogay9,14.31,7.15,0.00,1.36,3.09,19.17 ,0.63,0.00,0.00,10.89,43.39,0.00
North_Ossetian:NorthOssetia1,15.94,3.88,0.00,0.00, 0.00,20.34,0.00,0.00,0.00,3.72,56.12,0.00
North_Ossetian:NorthOssetia11,16.83,3.50,0.00,1.08 ,5.75,19.41,0.69,0.00,2.67,3.30,46.78,0.00
North_Ossetian:NorthOssetia12,22.13,3.57,0.00,0.00 ,4.02,17.38,0.00,0.17,2.62,3.81,46.30,0.00
North_Ossetian:NorthOssetia13,21.21,3.58,0.90,0.00 ,0.00,18.48,0.00,0.00,0.00,5.07,50.78,0.00
North_Ossetian:NorthOssetia14,14.44,4.65,0.00,1.03 ,0.00,21.25,0.00,0.00,0.00,3.12,55.51,0.00
North_Ossetian:NorthOssetia16,16.30,4.32,0.00,0.34 ,0.00,19.58,0.00,0.00,0.00,2.74,56.73,0.00
North_Ossetian:NorthOssetia17,19.74,3.76,1.05,0.00 ,0.00,16.74,0.00,0.06,0.31,3.02,55.33,0.00
North_Ossetian:NorthOssetia19,15.97,3.23,0.00,0.63 ,0.00,20.96,0.06,0.00,0.00,3.97,55.17,0.00
North_Ossetian:NorthOssetia2,20.74,3.30,0.01,0.08, 5.84,17.05,0.52,0.00,2.91,4.09,45.46,0.00
North_Ossetian:NorthOssetia20,14.81,5.88,0.00,0.05 ,0.00,16.39,0.60,0.00,0.00,2.65,59.62,0.00
North_Ossetian:NorthOssetia3,14.82,6.39,0.00,0.35, 1.47,20.39,0.00,0.00,0.00,2.65,53.92,0.00
North_Ossetian:NorthOssetia4,17.79,3.29,0.00,0.00, 0.00,18.80,0.00,0.24,0.00,5.01,54.87,0.00
North_Ossetian:NorthOssetia5,15.76,3.17,0.00,0.00, 0.36,18.48,0.00,0.00,0.00,4.33,57.90,0.00
North_Ossetian:NorthOssetia8,18.08,3.56,0.00,1.25, 1.21,19.01,0.04,0.00,0.00,3.20,53.64,0.00
North_Ossetian:NorthOssetia9,14.39,3.93,0.00,0.22, 0.00,18.36,0.55,0.00,0.00,5.40,57.15,0.00
Tajik:tad838,35.91,5.98,0.00,0.00,3.20,17.57,7.29, 0.00,3.85,4.91,21.29,0.00
Tajik:tadjik10,33.64,5.62,0.00,1.57,5.73,20.43,7.3 9,0.00,1.99,5.38,18.24,0.00
Tajik:tadjik11,31.49,7.60,0.00,2.02,3.51,17.37,9.3 2,0.21,2.14,5.79,20.55,0.00
Tajik:tadjik12,33.81,9.70,1.31,0.00,5.39,11.07,7.0 5,0.00,2.58,11.76,17.34,0.00
Tajik:tadjik13,31.01,6.67,2.14,1.17,4.15,18.03,7.2 7,0.00,1.36,12.81,15.37,0.00
Tajik:tadjik14,34.55,4.49,0.00,2.10,4.56,17.44,8.1 7,0.00,3.25,4.70,20.74,0.00
Tajik:tadjik15,30.40,9.53,0.15,0.00,3.88,15.84,9.5 9,0.06,2.40,7.59,20.57,0.00
Tajik:tadjik2,36.06,8.90,0.53,0.73,4.93,19.42,4.68 ,0.00,2.05,4.81,17.89,0.00
Tajik:tadjik3,34.75,6.11,0.00,0.00,4.07,19.76,7.35 ,0.03,3.10,6.41,18.43,0.00
Tajik:tadjik4,36.61,4.69,0.00,0.13,5.00,20.20,5.20 ,0.00,3.27,7.57,17.33,0.00
Tajik:tadjik5,27.67,6.87,0.00,1.06,2.17,19.48,8.43 ,0.00,3.71,8.92,21.69,0.00
Tajik:tadjik6,31.47,7.23,0.00,4.27,3.28,18.02,5.92 ,0.00,3.67,8.84,17.29,0.00
Tajik:tadjik7,30.83,5.52,0.00,3.60,2.04,19.59,5.54 ,0.00,3.10,12.63,17.15,0.00
Tajik:tadjik8,35.44,6.41,0.28,1.06,6.24,20.18,5.12 ,0.00,3.20,8.22,13.86,0.00
Tajik:tadjik9,34.71,5.57,0.43,0.59,4.58,18.45,8.34 ,0.00,4.15,7.75,15.44,0.00
Turkmen:turkm1820,29.91,4.90,0.00,1.40,4.47,10.44, 6.65,0.28,8.17,4.64,28.72,0.43
Turkmen:turkm3661,22.32,7.54,0.70,2.10,3.75,13.36, 6.14,0.00,7.85,6.87,29.02,0.34
Turkmen:turkm537,18.13,13.73,0.00,1.09,6.79,13.35, 4.45,0.00,6.09,12.13,24.25,0.00
Turkmen:turkm7529,26.18,10.32,0.00,1.57,6.04,11.55 ,5.87,0.00,5.70,9.02,23.45,0.31
Turkmen:turkmBe24,33.23,2.98,2.41,2.29,3.21,7.26,4 .36,0.00,6.32,7.62,30.32,0.00
Turkmen:turkmE31,28.34,4.76,0.00,1.06,1.47,9.45,6. 34,0.00,7.64,6.84,34.10,0.00
Turkmen:turkmE42,26.62,3.47,0.00,0.92,1.26,13.01,6 .84,0.00,7.81,7.10,32.98,0.00
Turkmen:turkmG31,26.94,6.16,0.23,2.98,5.98,10.70,6 .07,0.15,7.45,5.16,28.18,0.00
Turkmen:turkmG33,26.54,5.11,0.00,4.33,4.29,10.79,5 .47,0.00,7.89,3.92,31.65,0.00
Turkmen:turkmH6,28.34,5.64,1.07,3.15,5.88,7.63,5.7 2,0.00,7.08,5.70,29.79,0.00
Turkmen:turkmV32,34.76,6.85,0.00,0.00,4.37,7.16,4. 54,0.00,6.58,8.50,27.25,0.00
Turkmen:turkmen1,22.34,13.96,1.39,0.92,7.27,13.72, 5.25,0.50,4.59,13.32,16.67,0.06
Turkmen:turkmen2,24.57,9.95,1.89,3.72,4.09,16.10,5 .37,0.50,4.05,13.12,16.61,0.03
Turkmen:turkmu26,28.51,6.54,0.00,1.36,8.58,7.09,3. 91,0.29,7.63,6.80,29.29,0.00
Turkmen:turkmu33,27.40,5.98,2.01,2.30,5.57,9.85,6. 54,0.00,6.97,6.48,26.91,0.00
Ukranian:UkrBel614,0.01,0.04,0.00,0.00,12.71,65.09 ,0.63,0.00,1.32,1.82,18.37,0.00
Ukranian:UkrBel618,1.98,1.06,0.00,0.00,13.69,67.65 ,1.06,0.00,0.62,0.27,13.68,0.00
Ukranian:UkrBel620,1.33,1.02,0.00,0.00,18.98,59.94 ,0.05,0.00,3.78,0.30,14.59,0.00
Ukranian:UkrBel622,0.00,1.07,0.00,0.72,13.34,62.74 ,0.00,0.00,2.70,0.00,19.43,0.00
Ukranian:UkrBel733,0.00,0.49,0.70,0.00,12.22,65.48 ,0.00,0.00,3.64,0.80,16.68,0.00
Ukranian:UkrBel736,0.28,1.85,0.00,0.20,13.05,63.47 ,1.98,0.00,2.65,0.00,16.53,0.00
Ukranian:UkrLv215,3.93,1.33,0.00,0.07,24.11,56.48, 0.23,0.00,2.48,0.00,11.28,0.08
Ukranian:UkrLv223,5.47,1.21,1.66,0.41,14.80,60.20, 0.46,0.00,3.74,0.29,11.77,0.00
Ukranian:UkrLv226,4.44,1.48,0.00,0.00,23.65,49.67, 1.59,0.00,3.67,0.00,15.51,0.00
Ukranian:UkrLv228,3.21,2.17,0.00,0.17,20.42,57.36, 0.22,0.00,3.64,0.61,12.21,0.00
Ukranian:UkrLv237,0.00,0.00,0.00,0.00,16.20,59.43, 1.93,0.00,2.65,0.00,19.79,0.00
Ukranian:UkrLv240,0.25,0.00,1.50,0.00,19.72,56.36, 0.85,0.00,3.65,0.00,17.67,0.00
Ukranian:Ukraine130,0.00,2.42,0.00,0.00,15.62,65.9 2,0.99,0.00,1.50,0.00,13.55,0.00
Ukranian:Ukraine133,1.62,0.00,0.00,0.22,18.01,60.7 9,2.43,0.00,0.81,1.13,15.00,0.00
Ukranian:Ukraine136,3.34,0.35,0.00,2.75,15.74,58.6 8,0.00,0.00,1.03,0.33,17.78,0.00
Ukranian:Ukraine141,0.06,1.38,0.00,0.08,18.81,59.8 7,0.28,0.00,1.39,1.11,17.02,0.00
Ukranian:Ukraine94,0.56,1.86,0.00,0.09,17.68,60.94 ,0.80,0.00,3.53,0.00,14.55,0.00
Ukranian:Ukraine97,0.00,0.00,0.00,0.01,13.33,64.97 ,0.00,0.00,6.18,1.74,13.76,0.00
Ukranian:UkrainePol19,0.00,0.86,0.00,0.00,14.36,66 .81,1.87,0.00,1.37,0.00,14.73,0.00
Ukranian:UkrainePol25,0.00,0.00,0.00,0.00,18.04,55 .98,0.83,0.23,5.30,0.81,18.81,0.00

#K13
Abhkasian:abh100,3.86,6.19,9.31,51.59,20.68,2.04,3 .56,2.22,0.45,0.00,0.00,0.00,0.10
Abhkasian:abh107,0.00,1.57,10.91,71.63,12.78,0.00, 0.00,2.25,0.79,0.05,0.03,0.00,0.00
Abhkasian:abh119,2.65,3.90,9.86,55.73,20.74,0.71,2 .37,1.77,1.59,0.38,0.30,0.00,0.00
Abhkasian:abh122,0.00,7.66,10.66,51.78,23.58,1.72, 1.04,1.30,1.56,0.00,0.70,0.00,0.00
Abhkasian:abh133,0.00,0.00,12.12,76.80,8.87,0.00,0 .00,1.14,0.00,0.08,0.81,0.00,0.19
Abhkasian:abh135,0.00,0.52,15.39,66.52,13.86,0.00, 1.69,1.63,0.00,0.38,0.00,0.00,0.00
Abhkasian:abh137,0.00,0.00,12.87,66.24,16.91,0.00, 0.00,1.94,0.00,0.30,0.97,0.76,0.00
Abhkasian:abh147,0.00,3.24,9.45,70.52,14.83,0.00,0 .00,1.48,0.00,0.00,0.50,0.00,0.00
Abhkasian:abh154,1.44,2.79,9.09,55.54,24.16,3.02,2 .33,1.49,0.05,0.10,0.00,0.00,0.00
Abhkasian:abh165,15.34,27.01,6.45,30.08,14.05,1.28 ,2.05,0.20,1.69,1.42,0.00,0.43,0.00
Abhkasian:abh24,0.00,0.00,17.17,69.42,5.55,3.20,0. 00,1.87,0.00,0.18,0.90,0.39,1.33
Abhkasian:abh27,1.94,2.24,15.65,70.50,6.33,1.12,0. 00,1.41,0.81,0.00,0.00,0.00,0.00
Abhkasian:abh41,0.00,2.73,14.84,74.16,5.40,0.00,0. 00,2.22,0.65,0.00,0.00,0.00,0.00
Abhkasian:abh45,0.00,3.41,15.28,68.64,7.90,2.10,0. 00,0.89,0.40,0.00,1.21,0.00,0.17
Abhkasian:abh53,0.00,3.86,11.27,67.22,13.22,0.00,0 .66,1.82,1.95,0.00,0.00,0.00,0.00
Abhkasian:abh60,0.00,5.18,9.72,70.65,11.89,0.00,0. 00,1.99,0.20,0.00,0.38,0.00,0.00
Abhkasian:abh71,0.00,2.78,10.75,71.53,9.94,0.00,0. 00,1.34,0.59,0.00,1.26,1.81,0.00
Abhkasian:abh74,0.00,4.47,13.15,69.01,4.87,4.21,0. 00,2.19,0.13,0.00,1.56,0.40,0.00
Abhkasian:abh85,0.00,1.35,8.70,66.32,20.02,0.00,0. 00,3.01,0.10,0.00,0.49,0.00,0.00
Abhkasian:abh9,0.00,0.00,14.64,73.93,8.39,0.00,0.0 0,1.85,0.00,0.00,1.11,0.08,0.00
Armenian:armenia102,0.00,3.97,8.14,43.96,39.42,2.2 8,0.46,1.24,0.00,0.03,0.50,0.00,0.00
Armenian:armenia106,4.35,0.00,7.25,39.19,45.15,0.0 0,3.20,0.66,0.00,0.00,0.20,0.00,0.00
Armenian:armenia139,0.00,0.03,8.85,35.87,48.66,4.7 1,0.65,0.29,0.00,0.36,0.58,0.00,0.00
Armenian:armenia162,0.67,0.00,11.99,43.19,36.89,5. 54,1.22,0.00,0.00,0.00,0.40,0.00,0.10
Armenian:armenia176,1.22,0.36,14.73,38.36,34.62,6. 26,3.99,0.10,0.00,0.00,0.25,0.00,0.12
Armenian:armenia191,2.68,1.69,10.40,45.61,36.74,1. 69,0.32,0.05,0.00,0.00,0.81,0.00,0.00
Armenian:armenia279,0.00,0.00,8.37,36.18,47.38,5.8 6,0.56,0.49,0.00,0.28,0.88,0.00,0.00
Armenian:armenia293,0.00,0.25,8.71,41.56,46.83,0.0 0,1.56,0.93,0.00,0.02,0.13,0.00,0.00
Armenian:armenia3,3.94,4.10,12.05,39.07,33.93,4.28 ,1.64,0.00,0.38,0.37,0.00,0.00,0.24
Armenian:armenia36,0.00,0.00,13.03,39.51,43.67,1.8 0,1.34,0.05,0.00,0.00,0.61,0.00,0.00
Armenian:armenia7,4.34,0.62,12.89,35.11,37.34,6.64 ,2.59,0.00,0.00,0.13,0.04,0.29,0.00
Armenian:armenia71,5.61,0.00,6.28,42.26,36.08,5.63 ,3.26,0.44,0.00,0.28,0.00,0.00,0.16
Armenian:armenia73,0.00,3.93,8.31,41.14,42.49,0.97 ,1.49,0.00,0.49,0.23,0.58,0.16,0.23
Armenian:armenia80,3.33,2.20,12.46,35.05,35.94,8.2 6,2.36,0.28,0.00,0.11,0.00,0.00,0.00
Armenian:armenia86,0.96,1.42,11.68,41.75,39.25,2.1 1,2.55,0.00,0.00,0.00,0.28,0.00,0.00
Armenian:armenia91,0.00,0.00,12.60,42.19,38.03,5.2 2,0.70,0.00,0.10,0.47,0.69,0.00,0.00
Balkar:bal102,13.38,3.61,9.89,59.14,4.92,0.00,0.00 ,4.34,3.60,0.41,0.41,0.00,0.30
Balkar:bal108,0.00,10.95,10.11,63.81,6.10,0.00,0.0 0,3.13,3.80,0.19,0.38,0.97,0.55
Balkar:bal115,0.00,15.52,8.13,57.10,10.29,0.00,0.0 0,3.55,2.42,0.64,0.72,1.64,0.00
Balkar:bal124,0.00,16.37,12.13,60.93,3.79,0.00,0.0 0,2.87,2.38,0.95,0.52,0.00,0.06
Balkar:bal136,6.71,11.75,9.66,45.26,13.67,1.77,2.2 1,3.11,3.72,1.08,0.90,0.14,0.00
Balkar:bal14,0.19,13.42,7.21,53.83,14.06,0.56,0.00 ,3.91,5.33,0.54,0.84,0.12,0.00
Balkar:bal149,17.27,25.32,7.84,28.83,12.36,0.09,0. 00,2.58,3.93,1.24,0.53,0.00,0.00
Balkar:bal22,0.00,10.39,15.36,59.62,4.36,0.12,0.00 ,4.52,4.78,0.00,0.51,0.10,0.26
Balkar:bal26,7.60,6.61,8.19,51.22,15.06,0.00,1.26, 1.53,6.96,0.41,0.00,0.00,1.16
Balkar:bal31,16.00,23.81,6.02,28.56,14.34,1.28,1.5 5,2.53,3.88,1.12,0.69,0.00,0.23
Balkar:bal32,0.00,10.98,11.72,58.56,9.74,0.00,0.46 ,3.74,2.25,0.66,1.08,0.81,0.00
Balkar:bal42,12.88,3.41,11.17,56.55,4.40,0.00,1.50 ,2.48,6.92,0.67,0.00,0.00,0.00
Balkar:bal45,9.25,3.24,10.65,63.17,4.05,0.00,0.98, 4.38,2.19,1.08,1.01,0.00,0.00
Balkar:bal50,0.00,14.26,14.56,62.24,0.00,2.11,0.00 ,1.96,3.91,0.20,0.00,0.77,0.00
Balkar:bal64,8.05,9.41,7.85,44.18,16.49,0.00,1.91, 3.94,6.23,1.39,0.00,0.00,0.55
Balkar:bal7,4.86,11.61,10.55,46.71,14.19,0.00,1.85 ,3.03,6.64,0.00,0.58,0.00,0.00
Balkar:bal80,3.03,11.63,11.65,60.90,2.37,0.30,0.94 ,3.20,3.67,1.24,0.00,1.08,0.00
Balkar:bal88,0.00,12.32,7.69,55.75,15.34,0.00,1.55 ,2.93,4.23,0.01,0.18,0.00,0.00
Balkar:bal97,7.20,6.12,4.81,59.54,9.23,1.00,0.56,3 .79,5.89,0.00,1.56,0.00,0.30
Bulgarian:Bulgaria1,3.02,35.93,27.15,10.67,20.56,0 .00,0.00,1.05,0.14,0.77,0.04,0.67,0.00
Bulgarian:Bulgaria2,12.03,33.50,21.26,12.80,18.05, 0.90,0.00,0.00,0.70,0.00,0.74,0.00,0.00
Bulgarian:Bulgaria25,13.06,41.31,14.81,0.00,29.17, 0.00,0.40,0.33,0.00,0.12,0.81,0.00,0.00
Bulgarian:Bulgaria26,1.12,38.64,23.84,11.42,21.90, 0.00,1.03,0.24,1.28,0.00,0.00,0.00,0.53
Bulgarian:Bulgaria3,19.85,22.06,18.43,11.26,23.73, 2.77,0.00,0.00,0.56,0.17,1.17,0.00,0.00
Bulgarian:Bulgaria33,11.99,28.24,20.34,14.56,21.60 ,0.00,1.39,0.00,0.42,0.71,0.74,0.00,0.00
Bulgarian:Bulgaria37,18.91,31.56,19.10,3.46,23.89, 0.00,0.91,0.74,0.00,0.28,0.50,0.65,0.00
Bulgarian:Bulgaria39,16.06,35.91,17.73,5.18,21.37, 1.79,0.00,0.70,0.56,0.00,0.69,0.00,0.00
Bulgarian:Bulgaria4,23.89,25.60,18.15,9.78,19.08,1 .26,0.00,0.28,0.86,0.94,0.00,0.00,0.15
Bulgarian:Bulgaria5,8.64,40.27,18.39,6.81,25.13,0. 00,0.00,0.55,0.00,0.23,0.00,0.00,0.00
Bulgarian:Bulgaria6,21.54,24.53,17.15,14.78,17.77, 1.70,0.00,1.42,0.00,0.54,0.00,0.00,0.57
Bulgarian:Bulgaria7,0.00,33.03,27.53,11.40,26.90,0 .56,0.00,0.39,0.00,0.00,0.20,0.00,0.00
Bulgarian:Bulgaria8,12.45,33.66,21.83,11.30,15.26, 2.36,0.00,1.77,0.95,0.00,0.42,0.00,0.00
Chechen:ch101,12.81,24.77,5.50,36.18,13.35,0.25,3. 61,1.14,1.76,0.32,0.31,0.00,0.00
Chechen:ch109,20.09,7.75,0.00,59.83,1.75,2.60,3.31 ,0.41,2.72,1.29,0.26,0.00,0.00
Chechen:ch11,7.23,9.92,11.41,61.48,0.83,2.67,0.00, 2.97,1.45,1.44,0.58,0.00,0.00
Chechen:ch113,8.42,14.87,5.64,45.99,14.33,1.64,3.3 9,1.52,1.06,2.16,0.99,0.00,0.00
Chechen:ch126,10.16,9.82,4.72,65.93,1.74,1.58,1.42 ,2.61,0.90,0.68,0.43,0.00,0.00
Chechen:ch131,7.87,12.41,2.22,63.20,7.81,1.30,0.00 ,2.06,0.83,1.63,0.66,0.00,0.00
Chechen:ch150,0.00,16.07,8.46,68.28,0.66,1.69,0.00 ,1.22,0.83,1.73,0.50,0.56,0.00
Chechen:ch16,15.96,6.89,0.00,59.30,8.11,2.75,1.84, 0.00,2.53,1.79,0.44,0.00,0.39
Chechen:ch170,5.07,8.00,7.20,65.88,3.93,4.03,0.00, 0.92,2.07,1.01,1.36,0.34,0.19
Chechen:ch174,17.06,9.52,0.00,61.06,6.70,0.52,0.00 ,0.86,2.69,0.49,1.11,0.00,0.00
Chechen:ch179,1.20,17.38,7.58,64.46,2.08,1.60,2.51 ,0.53,1.64,0.26,0.00,0.76,0.00
Chechen:ch193,4.44,14.01,0.00,61.52,11.47,3.37,0.0 6,1.69,2.51,0.94,0.00,0.00,0.00
Chechen:ch21,11.18,13.07,1.55,65.68,0.00,2.04,0.00 ,2.98,0.64,1.63,1.23,0.00,0.00
Chechen:ch3,3.63,17.08,7.53,62.95,1.08,2.72,0.00,0 .65,2.98,0.79,0.19,0.41,0.00
Chechen:ch31,14.37,9.74,3.53,63.03,3.87,1.12,0.92, 1.04,1.50,0.29,0.00,0.51,0.09
Chechen:ch34,14.31,7.45,0.00,68.37,0.00,3.84,1.01, 2.82,0.00,0.26,1.45,0.00,0.50
Chechen:ch55,8.51,21.71,2.58,54.60,2.68,3.68,1.35, 0.92,1.73,2.04,0.21,0.00,0.00
Chechen:ch60,10.12,19.28,6.30,53.30,4.09,1.15,2.24 ,1.14,1.66,0.24,0.24,0.19,0.04
Chechen:ch76,9.07,17.26,3.63,47.17,12.79,1.02,2.34 ,1.75,2.08,1.15,1.30,0.00,0.44
Chechen:ch86,12.89,13.64,4.20,46.19,12.47,1.18,4.6 8,0.82,2.02,0.64,0.89,0.38,0.00
Kumyk:Kumyk22,8.54,10.90,0.00,47.85,23.97,0.00,0.2 4,3.24,5.25,0.00,0.01,0.00,0.00
Kumyk:kumyks1,6.46,11.49,11.43,53.23,1.61,0.82,1.4 4,3.90,7.89,0.33,0.75,0.65,0.00
Kumyk:kumyks10,7.46,12.31,7.98,45.59,16.48,1.66,3. 40,1.84,1.71,1.57,0.00,0.00,0.00
Kumyk:kumyks108,1.23,12.71,4.21,63.92,4.12,3.62,0. 17,4.67,2.21,0.19,1.21,1.75,0.00
Kumyk:kumyks11,13.24,7.40,5.41,49.92,8.88,1.00,1.5 9,3.67,5.44,0.75,1.89,0.81,0.00
Kumyk:kumyks110,0.00,15.22,11.92,59.60,0.00,2.58,1 .47,1.42,4.52,1.96,0.08,1.23,0.00
Kumyk:kumyks111,1.76,10.55,11.89,53.23,9.80,2.82,2 .97,2.15,2.81,1.18,0.23,0.24,0.36
Kumyk:kumyks13,5.79,11.06,7.58,38.75,20.64,2.64,4. 72,2.64,3.20,1.63,0.48,0.02,0.86
Kumyk:kumyks15,4.96,9.85,5.76,47.31,20.88,0.00,4.7 1,2.61,1.79,1.33,0.53,0.00,0.27
Kumyk:kumyks4,8.77,14.02,4.85,40.49,17.81,2.24,3.5 0,2.23,4.31,0.96,0.83,0.00,0.00
Kumyk:kumyks5,9.67,11.89,4.27,48.15,14.68,0.00,1.4 6,3.15,6.62,0.11,0.00,0.00,0.00
Kumyk:kumyks6,13.16,9.01,5.85,51.18,7.93,1.26,2.95 ,2.44,5.04,0.77,0.00,0.00,0.42
Kumyk:kumyks7,2.79,11.27,5.37,51.31,12.48,4.46,3.2 0,3.06,3.56,1.18,0.51,0.81,0.00
Kumyk:kumyks8,9.44,10.43,5.66,42.05,17.19,2.94,4.1 3,1.58,5.13,1.31,0.00,0.14,0.00
Kurd:kurd1101,3.48,2.94,5.70,45.52,27.50,5.74,5.86 ,1.26,0.14,0.69,0.51,0.05,0.58
Kurd:kurd1156,2.01,0.00,3.52,43.14,38.10,4.91,6.09 ,0.17,1.66,0.04,0.35,0.00,0.00
Kurd:kurd1159,4.20,4.82,0.36,47.11,32.97,3.33,4.17 ,1.15,0.30,0.30,0.74,0.00,0.55
Kurd:kurd1160,0.00,4.87,8.46,49.54,26.15,2.98,5.86 ,0.18,0.41,0.86,0.00,0.00,0.69
Kurd:kurd1173,2.95,3.81,0.87,40.72,36.94,4.42,8.19 ,0.00,0.10,1.13,0.75,0.00,0.13
Kurd:kurd1198,5.33,1.36,6.69,41.47,30.82,6.12,5.93 ,0.00,1.36,0.47,0.46,0.00,0.00
Mordovian:mordovia1,12.16,65.16,1.35,3.82,4.96,1.8 8,1.65,0.00,6.87,1.05,0.26,0.00,0.84
Mordovian:mordovia10,17.41,52.21,7.74,7.58,3.15,0. 00,2.49,0.00,7.36,1.74,0.00,0.00,0.33
Mordovian:mordovia11,0.00,73.22,6.27,5.43,1.53,1.9 0,2.99,0.00,7.14,0.76,0.37,0.38,0.00
Mordovian:mordovia12,0.00,73.13,8.92,3.35,4.33,1.1 6,1.60,1.10,4.81,0.79,0.16,0.00,0.65
Mordovian:mordovia13,24.55,49.18,4.69,7.70,3.70,0. 18,0.89,0.00,7.05,1.29,0.00,0.00,0.78
Mordovian:mordovia14,7.51,66.00,6.72,4.28,6.80,0.0 0,0.15,1.25,3.99,1.48,0.99,0.84,0.00
Mordovian:mordovia15,4.07,69.46,5.59,5.84,4.34,0.0 0,1.85,1.83,6.10,0.20,0.28,0.00,0.45
Mordovian:mordovia2,22.44,50.88,5.69,6.58,3.43,0.6 5,2.62,0.00,5.45,0.79,0.80,0.00,0.67
Mordovian:mordovia3,21.35,50.08,7.06,7.82,0.94,0.1 5,1.98,1.23,7.08,1.51,0.00,0.80,0.00
Mordovian:mordovia4,2.99,73.16,4.01,6.76,3.20,0.00 ,1.24,3.32,4.96,0.24,0.13,0.00,0.00
Mordovian:mordovia5,2.16,69.05,7.87,3.96,5.91,0.00 ,2.22,0.99,6.99,0.84,0.00,0.00,0.00
Mordovian:mordovia6,8.93,67.22,5.59,5.17,2.91,0.31 ,0.16,1.13,5.94,0.90,0.53,1.20,0.00
Mordovian:mordovia7,9.41,64.45,2.83,10.37,1.58,1.9 0,0.00,1.06,6.75,0.62,0.62,0.00,0.40
Mordovian:mordovia8,7.04,67.32,6.76,6.39,3.26,0.11 ,0.44,0.28,4.70,2.24,0.59,0.00,0.89
Mordovian:mordovia9,0.00,68.78,10.94,10.27,0.00,1. 46,1.65,0.49,4.21,1.76,0.00,0.21,0.23
Nogai_Kuban:nogay1,3.48,18.28,7.09,44.49,0.31,4.48 ,1.80,7.51,10.54,0.89,0.14,1.00,0.00
Nogai_Kuban:nogay10,9.65,13.36,4.90,31.26,6.67,0.8 4,4.03,10.46,16.27,0.84,0.91,0.53,0.28
Nogai_Kuban:nogay11,0.40,21.60,12.40,34.86,0.00,3. 34,1.33,8.40,16.98,0.63,0.06,0.00,0.00
Nogai_Kuban:nogay12,9.78,9.22,7.38,41.83,8.02,0.59 ,2.36,5.44,13.57,0.77,0.16,0.67,0.21
Nogai_Kuban:nogay13,3.87,16.65,5.54,33.66,8.93,1.7 2,3.48,9.87,15.67,0.47,0.13,0.00,0.00
Nogai_Kuban:nogay14,5.73,13.38,9.47,38.21,3.43,0.5 9,0.00,9.84,16.63,1.46,0.42,0.80,0.05
Nogai_Kuban:nogay15,5.14,15.92,6.62,33.06,0.00,2.4 9,0.91,11.51,21.74,0.90,1.73,0.00,0.00
Nogai_Kuban:nogay16,8.72,14.36,7.41,32.29,10.35,0. 00,1.50,7.88,15.02,1.47,0.42,0.57,0.00
Nogai_Kuban:nogay2,0.00,13.06,12.28,46.18,1.45,1.9 7,0.33,8.84,14.81,0.00,0.23,0.85,0.00
Nogai_Kuban:nogay3,0.00,26.02,8.02,33.63,8.99,0.00 ,0.00,6.16,13.78,1.51,1.63,0.23,0.04
Nogai_Kuban:nogay4,9.34,11.97,7.11,30.48,13.45,0.0 0,2.69,9.16,13.81,1.40,0.20,0.00,0.38
Nogai_Kuban:nogay5,9.16,13.92,4.38,37.41,9.73,0.00 ,3.16,6.93,13.62,1.24,0.44,0.00,0.00
Nogai_Kuban:nogay6,8.24,24.23,5.94,30.21,14.21,0.0 0,1.41,5.19,10.57,0.00,0.00,0.00,0.00
Nogai_Kuban:nogay7,13.13,17.02,7.99,31.01,8.83,1.9 4,2.92,4.85,10.26,1.94,0.00,0.13,0.00
Nogai_Kuban:nogay8,6.36,16.41,8.10,42.54,1.96,1.87 ,1.99,6.96,13.42,0.31,0.00,0.00,0.08
Nogai_Kuban:nogay9,0.02,16.77,10.55,46.74,4.85,0.1 8,0.58,8.10,9.42,1.67,0.96,0.00,0.17
North_Ossetian:NorthOssetia1,4.82,12.75,7.67,49.46 ,14.09,1.57,1.86,1.13,4.68,0.99,0.79,0.18,0.00
North_Ossetian:NorthOssetia11,0.00,15.84,10.74,56. 90,6.55,0.00,0.00,3.76,4.22,0.00,0.66,1.32,0.00
North_Ossetian:NorthOssetia12,5.58,10.35,8.32,51.7 3,13.35,0.00,1.91,3.18,4.95,0.00,0.00,0.51,0.13
North_Ossetian:NorthOssetia13,0.00,11.55,10.92,66. 36,0.00,1.66,0.00,2.67,4.66,1.06,0.47,0.00,0.65
North_Ossetian:NorthOssetia14,0.00,15.34,12.93,55. 56,6.28,0.00,0.00,3.09,5.02,0.81,0.96,0.00,0.00
North_Ossetian:NorthOssetia16,9.39,10.83,5.41,48.2 9,16.39,0.59,0.93,2.82,4.84,0.42,0.08,0.00,0.00
North_Ossetian:NorthOssetia17,5.46,8.94,7.40,49.47 ,14.02,2.46,4.14,2.02,4.25,0.15,0.00,0.80,0.88
North_Ossetian:NorthOssetia19,4.76,12.31,8.80,48.6 5,13.57,1.80,2.39,2.91,4.29,0.39,0.00,0.00,0.12
North_Ossetian:NorthOssetia2,0.00,10.92,12.01,62.4 9,4.25,0.56,0.00,3.46,4.82,0.00,0.53,0.96,0.00
North_Ossetian:NorthOssetia20,0.00,10.37,11.70,59. 25,8.66,0.00,1.31,2.58,4.78,0.64,0.59,0.00,0.14
North_Ossetian:NorthOssetia3,5.88,9.65,13.39,59.11 ,0.00,1.08,0.00,2.12,7.42,0.00,1.10,0.27,0.00
North_Ossetian:NorthOssetia4,6.80,6.25,5.59,61.36, 9.72,0.00,0.00,3.55,3.86,1.26,0.17,1.44,0.00
North_Ossetian:NorthOssetia5,0.00,11.60,12.81,61.3 5,5.45,0.00,0.00,1.60,5.31,0.29,0.63,0.95,0.00
North_Ossetian:NorthOssetia8,4.92,7.70,11.12,63.74 ,0.00,2.16,0.00,4.03,3.03,1.45,1.24,0.61,0.00
North_Ossetian:NorthOssetia9,0.00,12.07,11.11,57.2 1,9.00,0.00,0.58,3.66,5.00,0.00,0.70,0.00,0.67
Tajik:tad838,3.52,14.74,0.00,46.22,8.28,0.11,15.04 ,2.33,5.40,3.53,0.83,0.00,0.00
Tajik:tadjik10,12.96,14.43,0.00,41.74,2.43,0.87,15 .41,2.63,6.69,2.16,0.55,0.00,0.12
Tajik:tadjik11,8.56,10.18,0.00,46.46,0.00,2.34,15. 61,4.83,7.89,1.35,1.92,0.12,0.75
Tajik:tadjik12,8.54,9.41,2.63,34.17,5.85,1.32,16.9 7,5.82,13.38,0.93,0.00,0.51,0.46
Tajik:tadjik13,8.84,13.26,0.00,37.13,3.71,0.64,14. 28,9.32,9.03,2.80,0.00,0.99,0.00
Tajik:tadjik14,14.22,9.71,0.32,36.60,6.72,2.69,18. 12,3.37,6.01,1.65,0.04,0.00,0.56
Tajik:tadjik15,6.87,10.98,0.00,39.37,8.93,0.00,15. 45,3.50,11.63,1.80,0.61,0.86,0.00
Tajik:tadjik2,10.49,14.96,0.00,42.24,3.31,0.00,13. 45,3.18,9.14,1.84,0.00,0.38,1.01
Tajik:tadjik3,10.85,12.21,0.00,45.59,2.31,0.00,16. 71,3.20,7.28,1.11,0.00,0.75,0.00
Tajik:tadjik4,14.17,9.07,0.00,47.29,2.63,0.00,14.1 4,4.62,5.69,2.27,0.00,0.00,0.12
Tajik:tadjik5,6.12,12.12,3.62,43.09,0.06,3.31,13.5 5,5.86,9.43,1.53,0.80,0.52,0.00
Tajik:tadjik6,9.54,12.44,0.00,34.45,7.49,1.43,14.4 7,7.94,8.33,2.52,0.81,0.28,0.29
Tajik:tadjik7,12.46,10.72,0.00,37.93,3.85,0.00,13. 86,10.60,8.54,1.62,0.15,0.25,0.00
Tajik:tadjik8,18.44,6.83,0.00,43.17,1.48,0.00,12.6 8,4.90,8.45,2.60,0.00,0.00,1.43
Tajik:tadjik9,10.43,12.30,0.00,34.95,9.50,0.00,18. 44,4.73,7.76,1.80,0.00,0.00,0.09
Turkmen:turkm1820,0.00,8.01,5.57,46.15,11.86,3.08, 13.08,3.33,6.77,0.84,0.00,1.11,0.18
Turkmen:turkm3661,2.23,11.35,4.23,37.22,13.41,3.24 ,11.26,5.44,9.94,0.74,0.00,0.95,0.00
Turkmen:turkm537,9.13,7.83,0.48,28.01,18.52,0.54,7 .67,7.29,17.29,1.70,0.60,0.00,0.95
Turkmen:turkm7529,7.10,7.59,2.17,40.35,8.85,1.25,9 .28,5.49,13.69,1.55,1.39,0.00,1.30
Turkmen:turkmBe24,0.00,6.69,6.87,43.44,17.61,0.26, 10.82,6.70,5.28,1.30,0.00,0.00,1.03
Turkmen:turkmE31,5.40,4.52,2.22,36.07,23.68,2.94,1 2.17,5.29,6.60,0.39,0.61,0.03,0.10
Turkmen:turkmE42,5.06,7.88,1.68,36.56,21.56,3.70,1 1.68,5.37,5.62,0.87,0.00,0.03,0.00
Turkmen:turkmG31,6.56,6.32,5.29,34.44,17.72,3.00,1 1.59,4.66,8.12,0.45,0.42,0.00,1.42
Turkmen:turkmG33,5.50,7.23,5.55,32.89,19.59,3.23,1 1.33,5.25,6.01,1.05,1.17,0.00,1.21
Turkmen:turkmH6,4.94,5.80,5.64,32.71,21.16,2.27,13 .03,5.24,7.27,1.46,0.00,0.00,0.48
Turkmen:turkmV32,0.00,4.74,5.61,46.68,13.84,0.45,1 3.39,5.41,9.30,0.00,0.00,0.14,0.44
Turkmen:turkmen1,9.86,9.22,0.00,27.48,13.55,1.62,9 .56,10.30,16.62,1.79,0.00,0.00,0.00
Turkmen:turkmen2,3.01,16.90,0.00,27.95,10.10,2.14, 11.23,11.73,13.06,1.95,0.73,0.74,0.45
Turkmen:turkmu26,6.90,2.75,1.66,37.98,24.85,0.00,1 1.04,5.11,6.39,2.40,0.93,0.00,0.00
Turkmen:turkmu33,6.66,4.77,3.90,34.75,19.54,1.86,1 2.62,6.56,7.05,1.33,0.00,0.95,0.00
Ukranian:UkrBel614,27.60,47.65,5.28,9.25,6.19,0.21 ,0.34,1.21,0.97,0.34,0.00,0.15,0.79
Ukranian:UkrBel618,27.26,48.15,8.74,9.81,1.09,0.45 ,2.28,0.00,0.91,0.65,0.11,0.00,0.54
Ukranian:UkrBel620,13.56,61.48,11.02,2.69,4.93,3.8 9,0.08,0.00,1.71,0.00,0.56,0.00,0.07
Ukranian:UkrBel622,22.55,46.08,9.69,7.55,9.48,0.63 ,0.33,1.12,1.20,0.74,0.63,0.00,0.00
Ukranian:UkrBel733,6.71,67.27,10.91,7.40,0.00,5.67 ,0.09,0.27,0.56,0.33,0.56,0.00,0.23
Ukranian:UkrBel736,0.00,71.85,8.82,0.00,14.53,0.00 ,2.19,0.00,1.18,0.23,1.20,0.00,0.00
Ukranian:UkrLv215,28.24,45.90,11.43,5.32,2.52,2.42 ,1.54,0.18,1.36,0.02,1.07,0.00,0.00
Ukranian:UkrLv223,16.41,61.96,0.96,3.64,9.58,4.26, 1.27,0.63,0.54,0.17,0.08,0.49,0.00
Ukranian:UkrLv226,28.18,38.30,12.95,8.52,6.03,1.97 ,0.91,0.42,0.82,1.11,0.79,0.00,0.00
Ukranian:UkrLv228,25.64,41.34,11.57,7.62,7.32,0.81 ,1.06,0.36,2.19,1.24,0.43,0.00,0.43
Ukranian:UkrLv237,4.05,65.77,15.61,1.75,9.95,0.00, 2.08,0.00,0.00,0.58,0.00,0.00,0.21
Ukranian:UkrLv240,11.81,60.07,9.62,0.00,16.79,0.00 ,0.00,0.00,0.00,0.01,1.04,0.00,0.67
Ukranian:Ukraine130,3.73,72.57,9.57,0.00,9.67,1.26 ,0.62,0.00,1.64,0.52,0.41,0.00,0.00
Ukranian:Ukraine133,10.75,62.96,9.83,4.33,6.79,0.0 0,3.37,1.06,0.03,0.38,0.00,0.00,0.50
Ukranian:Ukraine136,10.01,61.72,6.91,4.93,12.20,0. 00,0.00,3.31,0.34,0.04,0.36,0.00,0.16
Ukranian:Ukraine141,5.87,69.07,10.92,0.00,10.98,0. 00,0.00,1.64,0.35,0.20,0.58,0.00,0.39
Ukranian:Ukraine94,7.52,64.55,12.42,0.00,10.45,0.8 9,1.84,0.00,1.04,0.57,0.00,0.01,0.70
Ukranian:Ukraine97,9.99,68.21,6.16,0.00,8.42,3.62, 0.00,1.58,0.13,0.63,0.15,1.10,0.00
Ukranian:UkrainePol19,0.00,76.69,8.98,0.00,10.86,0 .54,1.14,0.00,0.00,1.05,0.27,0.00,0.46
Ukranian:UkrainePol25,8.33,60.62,15.64,3.80,3.41,5 .89,0.47,0.00,0.63,0.00,0.00,0.00,1.23

Here's the new averages compared to old averages in K12b updated:

https://i.ibb.co/PTDbk5c/yunusbayev-2011-caucasus-k12b.png

The old Nogai average is almost identical to the new Nogai_Kuban average, so I think it can be replaced with the new Nogai_Kuban average. Kuban Nogais are fairly distinct from other Nogai (https://www.eki.ee/books/redbook/nogays.shtml):

According to N. Baskakov, the Nogay language divides into three dialects: a) the Kara-Nogay (Turkic kara -- 'black') dialect, spoken in the Nogay District in Dagestan, on the lower reaches of the River Kuma and in the area between the Lower Kuma and Lower Terek in North Dagestan, b) the Nogay Proper spoken in the Achikulak and Neftekumsk Districts of the Stavropol Area, (the speakers of these two dialects together make up the so-called Steppe Nogay Group), c) the Aknogay dialect (Turkic ak -- 'white': Turkic peoples have commonly divided their tribes into black and white, 'black' meaning 'northern' and 'white' 'western') by the River Kuban and its tributaries in Karachayevo-Cherkess and in the Kangly village of the Mineralnye Vody District (13,200 speakers). The Kara-Nogay and Nogay Proper dialects are comparatively close linguistically while the Aknogay dialect stands somewhat apart. [...]

The Kara-Nogays continued as nomads until the establishment of Soviet power. The Kuban Nogays became settled much earlier, in the late 18th century, along the Greater and Smaller Zelenchuk Rivers and the Lower Uruk and Laba. The nomadic way of life has left a conspicuous mark on Nogay economies and culture. The methods of livestock husbandry are similar to that of the Kazakh and other Central Asian peoples. Throughout the centuries horsebreeding has been of great importance -- horses were used for transport in the vast steppes, battles were fought by cavalry, horse-milk was drunk and horsemeat was served as food. Horses were sold annually to Moscow. After settling, agriculture rose to prime importance among the Kuban Nogays.

https://academic.oup.com/mbe/article/29/1/359/1750206:

The Kuban Nogays and the Kara Nogays (fig. 1A) have a special status among the Caucasian populations due to their recent, late 18th to early 19th century arrival from the Pontocaspian steppes (Kolga et al. 2001). It has been shown earlier that the Nogays possess 40% of East Eurasian mtDNA lineages (Bermisheva et al. 2004). Although the Kara Nogays have more (∼35%) typical eastern Y chromosome lineages than the Kuban Nogays (17%) (supplementary table S3, Supplementary Material online), it is perhaps more interesting that both the Kuban Nogays and the Kara Nogays preserve a certain combination of STR haplotypes in the Y chromosome haplogroup C, the so-called Genghis Khan modal haplotype (Zerjal et al. 2003). Because the historic Nogay Khan, a powerful late 13th century general of the Golden Horde, was indeed a great-grandson of Genghis Khan, such a coincidence is intriguing.

Leto

11-02-2021, 05:31 PM

Here's all samples from Yunusbayev et al. 2011, "The Caucasus as an Asymmetric Semipermeable Barrier to Ancient Human Migrations": https://evolbio.ut.ee/caucasus/, https://academic.oup.com/mbe/article/29/1/359/1750206.
...
Thank you, although nearly all of them were used as original references, so for Gedmatch that data isn't very useful. On the other hand, I do need it for G25 but all the fucks keep ignoring me :angry:

vbnetkhio

11-02-2021, 06:12 PM

Thank you, although nearly all of them were used as original references, so for Gedmatch that data isn't very useful. On the other hand, I do need it for G25 but all the fucks keep ignoring me :angry:

they were probably used as g25 references too, so you can't get their g25 results for the same reason.

Leto

11-02-2021, 06:22 PM

they were probably used as g25 references too, so you can't get their g25 results for the same reason.
No, the samples that I'm asking for are not in the G25 spreadsheet.

vbnetkhio

11-02-2021, 06:44 PM

No, the samples that I'm asking for are not in the G25 spreadsheet.

well yes, they were probably used to construct g25, so they can't be added to the spreadsheet, because they would have nonsensical results becaues of the calculator effect.

Leto

11-02-2021, 06:48 PM

well yes, they were probably used to construct g25, so they can't be added to the spreadsheet, because they would have nonsensical results becaues of the calculator effect.
What do you mean by used to construct? G25 is not based on any specific dataset, you can use anything as long as you have the coordinates for that. Only Gedmatch was made up of artificial components based on modern samples (North Atlantic, Baltic, etc.).

vbnetkhio

11-02-2021, 06:57 PM

Leto

11-02-2021, 07:02 PM

It's the same with G25, the "components" of G25 are also constructed from certain modern samples, which then cannot be used in G25 afterwards.
Does G25 have components? There are no fixed calculators on G25 unlike on Gedmatch. When I go to Vahaduo G25, I see a lot of shit made up by TA users and other folks plus David's standard model.

Komintasavalta

11-02-2021, 07:04 PM

What do you mean by used to construct? G25 is not based on any specific dataset, you can use anything as long as you have the coordinates for that. Only Gedmatch was made up of artificial components based on modern samples (North Atlantic, Baltic, etc.).

I think the G25 datasheets consist of only projected samples, because projected samples plot differently from reference samples.

For example in the plot below, I took 8 random samples from different populations, I used half of samples from each population as references, which are indicated by a triangle, and I projected the other half of samples, which are indicated by a circle (https://anthrogenica.com/showthread.php?23708-Shell-and-R-scripts-for-SmartPCA-and-ADMIXTURE&p=806356&viewfull=1#post806356). The reference samples plot further away from the center, in the same way that in ADMIXTURE, reference samples get higher percentages of their main components than projected samples:

https://i.ibb.co/m6nKLG2/a.png

Davidski refers to this phenomenon as "projection bias" (https://eurogenes.blogspot.com/2017/03/baltic-corded-ware-rich-in-r1a-z645.html):

Speaking of projection bias, I'm quite certain that their Principal Component Analysis (PCA) suffers from it. The ancient samples look like they're being pulled into the middle of the plot, so much so that one of the foragers basically clusters with modern-day Lithuanians, while the CWC individuals appear too western. They need to fix this.

https://4.bp.blogspot.com/-PeuXkrFay5k/WLj4ZEtV-RI/AAAAAAAAFX0/lqE81yLv5joeuD0-hCMVt4kMYLrNr3-awCLcB/s380/Saag_Fig_2.png

In SMARTPCA, you can use the `poplistname` option to do projection, and in PLINK 2, you can use `--score`:

https://compvar-workshop.readthedocs.io/en/latest/contents/02_pca/pca.html#population-lists-vs-projection
https://www.cog-genomics.org/plink/2.0/score#pca_project
https://groups.google.com/g/plink2-users/c/W6DL5-hs_Q4/m/b_o3JMrxAwAJ

Leto

11-02-2021, 07:04 PM

Anyway, if there is a third study out there with Tajik samples in it (other than Yunus and Jeong), please let me know. I need them for my Steppe-centric Central Asian model.

Leto

11-02-2021, 07:08 PM

Sorry, that stuff is kind of hard for me to understand.

vbnetkhio

11-02-2021, 07:15 PM

Does G25 have components? There are no fixed calculators on G25 unlike on Gedmatch. When I go to Vahaduo G25, I see a lot of shit made up by TA users and other folks plus David's standard model.

there are the 25 principal components (coordinates), the difference is that they don't range from 0% to 100% like the gedmatch components, for example the first one peaks in Lithuanians 0.14 and is lowest in Mbuti at -0.65.

Komintasavalta

11-02-2021, 07:59 PM

Anyway, if there is a third study out there with Tajik samples in it (other than Yunus and Jeong), please let me know. I need them for my Steppe-centric Central Asian model.

There's G25 coordinates for some Tajik samples in Cardona et al. 2014, "Genome-Wide Analysis of Cold Adaptation in Indigenous Siberian Populations": https://anthrogenica.com/showthread.php?22733-651-New-Sample-for-G25, https://pastebin.com/raw/MhkaSSgD.

In the stock G25, the average of the Tajik samples from Cardona is actually closer to Turkmens and Uzbeks than to Tajiks:

$ dist()(awk -F, 'NR==FNR{for(i=2;i<=NF;i++)a[i]=$i;next}$1{s=0;for(i=2;i<=NF;i++)s+=($i-a[i])^2;printf"%f %s\n",s^.5,$1}' "$2" "$1"|sort -n|awk '{printf"%."x"f %s\n",$1,$2}' "x=${3-3}"|sed s,^0,,)
$ tav()(awk '{n[$1]++;for(i=2;i<=NF;i++){a[$1][i]+=$i}}END{for(i in a){o=i;for(j=2;j<=NF;j++)o=o FS sprintf("%f",a[i][j]/n[i]);print o}}' "FS=${1-$'\t'}")
$ curl -Ls https://pastebin.com/raw/MhkaSSgD|grep Tajik|sed 's/:[^,]*//'|tav ,|dist <(curl -Ls 'https://drive.google.com/uc?export=download&id=1wZr-UOve0KUKo_Qbgeo27m-CQncZWb8y') -|head -n8
.028 Turkmen_Uzbekistan
.029 Turkmen
.061 Uzbek
.067 Tatar_Crimean_steppe
.071 Tajik
.076 Sarikoli_China
.088 Tatar_Lipka
.092 Tajik_Badakshan

Leto

11-02-2021, 09:00 PM

There's G25 coordinates for some Tajik samples in Cardona et al. 2014, "Genome-Wide Analysis of Cold Adaptation in Indigenous Siberian Populations": https://anthrogenica.com/showthread.php?22733-651-New-Sample-for-G25, https://pastebin.com/raw/MhkaSSgD.

In the stock G25, the average of the Tajik samples from Cardona is actually closer to Turkmens and Uzbeks than to Tajiks:

$ dist()(awk -F, 'NR==FNR{for(i=2;i<=NF;i++)a[i]=$i;next}$1{s=0;for(i=2;i<=NF;i++)s+=($i-a[i])^2;printf"%f %s\n",s^.5,$1}' "$2" "$1"|sort -n|awk '{printf"%."x"f %s\n",$1,$2}' "x=${3-3}"|sed s,^0,,)
$ tav()(awk '{n[$1]++;for(i=2;i<=NF;i++){a[$1][i]+=$i}}END{for(i in a){o=i;for(j=2;j<=NF;j++)o=o FS sprintf("%f",a[i][j]/n[i]);print o}}' "FS=${1-$'\t'}")
$ curl -Ls https://pastebin.com/raw/MhkaSSgD|grep Tajik|sed 's/:[^,]*//'|tav ,|dist <(curl -Ls 'https://drive.google.com/uc?export=download&id=1wZr-UOve0KUKo_Qbgeo27m-CQncZWb8y') -|head -n8
.028 Turkmen_Uzbekistan
.029 Turkmen
.061 Uzbek
.067 Tatar_Crimean_steppe
.071 Tajik
.076 Sarikoli_China
.088 Tatar_Lipka
.092 Tajik_Badakshan
Wow, thank you so much! They do seem to be more Mongoloid than the ones I previously had. Probably from Northern/Northwestern TJK (Sughd region). Some are well over 25% East Eurasian.

Their BA Steppe average is 30.9 percent (three samples are below 30%, the highest value is 34.9%). Don't know what they would score on Gedmatch though.

Komintasavalta

11-03-2021, 03:22 AM

I now finished running K13 for all 14,313 samples in the 1240K+HO version of the Reich dataset: https://drive.google.com/file/d/15Mvba7Bw07VtixiBO_EctOhPPECGzZC9. There's many samples that suffer from the calculator effect, because I didn't bother removing samples that were used as references in K13.

The code below selects populations that include at least one sample whose latitude is over 50, and it adds up the percentage of the Siberian, East Asian, and American components:

$ curl 'https://drive.google.com/uc?export=download&id=15Mvba7Bw07VtixiBO_EctOhPPECGzZC9' -Lso reich.k13
$ curl https://reichdata.hms.harvard.edu/pub/datasets/amh_repo/curated_releases/V50/V50.0/SHARE/public.dir/v50.0_HO_public.anno|iconv -f macintosh -t utf-8 >ho.anno
$ igno()(grep -Ev '\.REF|rel\.|fail\.|\.contam|Ignore_|_dup|_contam| _lc|_father|_mother|_son|_daughter|_brother|_siste r|_relative|_sibling|_twin|Neanderthal|Denisova|Vi ndija_light|Gorilla|Macaque|Marmoset|Orangutan|Pri mate_Chimp|hg19ref')
$ tav()(awk '{n[$1]++;for(i=2;i<=NF;i++){a[$1,i]+=$i}}END{for(i in n){o=i;for(j=2;j<=NF;j++)o=o FS sprintf("%f",a[i,j]/n[i]);print o}}' "FS=${1-$'\t'}")
$ sed 1d reich.k13|igno|sed 's/:[^,]*//'|tav ,|sort>reich.k13.ave
$ awk -F\\t '$10>=50{print$7}' ho.anno|igno|awk -F, 'NR==FNR{a[$0];next}$1 in a' - reich.k13.ave|awk -F, '{print$9+$10+$11,$1}'|sort -n|awk '{$1=sprintf("%.0f",$1)}1'
0 Czech_Baalberge
0 Czech_Bohemia_Baden_N
0 Czech_Bohemia_CordedWare_o1
0 Czech_Bohemia_Jordanow_N
0 Czech_Bohemia_Rivnac_N_oAnatolia
0 Czech_Bohemia_Rivnac_N_oWHG
0 Czech_C_Baalberge_o1
0 Czech_C_Baalberge_o2
0 Czech_EarlySlav.SG
0 Czech_Eneolithic
0 Czech_MN
0 Czech_N
0 England_IA_ERoman.SG
0 England_IA_Roman_oMiddleEast.SG
0 England_Mesolithic.SG
0 England_Mesolithic_o1
0 England_Mesolithic_o1.SG
0 England_N_published
0 England_Trumpington_N.SG
0 Faroes_EarlyModern_o2.SG
0 France_HautsDeFrance_MN.SG
0 Germany_Blatterhohle_MN_oWHG
0 Germany_CordedWare_o
0 Germany_LN_oWHG
0 Germany_MN_Esperstedt
0 Germany_MN_Salzmuende
0 Germany_N
0 Germany_Tollense_BA_o1.SG
0 Iceland_Early_Christian_o.SG
0 Ireland_EN.SG
0 Ireland_Mesolithic.SG
0 Ireland_N.SG
0 Poland_BKG.SG
0 Poland_BKG_o2.SG
0 Poland_GAC.SG
0 Poland_Globular_Amphora_published
0 Poland_Medieval_1.SG
0 Poland_Mierzanowice_GAC.SG
0 Poland_TRB_o.SG
0 Poland_Wilczyce_GAC.SG
0 Russia_EasternScythian_SouthernUrals_o.SG
0 Scotland_MBA_published
0 Scotland_Megalithic.SG
0 Scotland_N_lowEEF_all.SG
0 Scotland_N_mediumlowEEF
0 Scotland_N_published
0 Sweden_BA.SG
0 Sweden_FBC.SG
0 Sweden_Gotland_Vasterbjers_PittedWare_BattleAxe_o. SG
0 Sweden_TRB_MN
0 Wales_Mesolithic
0 Wales_Mesolithic.SG
0 Wales_N_all.SG
0 England_Mesolithic
0 Czech_C_Baalberge
0 Czech_Bohemia_Rivnac_N
0 Germany_Tollense_BA_o2.SG
0 Poland_TRB.SG
0 Germany_EN_LBK_published
0 Ireland_MN.SG
0 Poland_BKG_o1.SG
0 Denmark_MN_B.SG
0 Ireland_EN_MN.SG
0 Poland_Globular_Amphora
0 English.DG
0 England_N.SG
0 Germany_Blatterhohle_MN
0 Scotland_N
0 Poland_Koszyce_GAC.SG
0 Czech_Bohemia_CordedWare_o3
0 England_N_all.SG
0 Ireland_LN.SG
0 Scotland_N_lowEEF.SG
0 England_N
0 Czech_Bohemia_GlobularAmphorae_N
0 Germany_MN_Baalberge
0 Sweden_EarlyViking.SG
0 Scotland_N.SG
0 Germany_LBA_Halberstadt_published
0 Ukraine_Medieval.SG
0 England_Mesolithic_all.SG
0 Scotland_N_lowEEF
0 England_MBA_highEEF
0 Germany_EN_LBK
0 Sweden_Ansarve_Megalithic.SG
1 English
1 Poland_Sandomierz_GAC.SG
1 Faroes_EarlyModern_o1.SG
1 Sweden_LNBA
1 Czech.DG
1 Wales_MBA_published
1 England_BellBeaker_highWHG_published
1 Russia_MLBA_Sintashta_published
1 Polish.DG
1 Wales_N
1 Czech_Bohemia_BellBeaker_oAnatolia1
1 Sweden_IA_2.SG
1 Czech_Bohemia_FunnelBeaker_N
1 Ireland_Megalithic.SG
1 Norway_IA.SG
1 Czech_MN.SG
1 Denmark_Viking_o1.SG
1 Czech_Bohemia_CordedWare_o2
1 Czech_EBA_Starounetice
1 England_EarlyMedieval_Saxon.SG
1 Lithuanian
1 England_BellBeaker_mediumEEF
1 Wales_N.SG
1 Germany_LN_Alberstedt
1 French
1 Orcadian.SDG
1 Kazakhstan_Chanchar_MBA_published
1 England_MBA_lowEEF
1 Germany_BellBeaker_published
1 Orcadian
1 Denmark_Viking_o2.SG
1 Poland_Ksiaznice_GAC.SG
1 Orcadian.DG
1 Ireland_Viking.SG
1 Icelandic.DG
1 Latvia_BA
1 Icelandic
1 Scotland_Viking.SG
1 Russia_IA_Ingria.SG
1 Poland_CWC_1.SG
1 Denmark_Viking.SG
1 Norway_Viking_o2.SG
1 Poland_Medieval_2.SG
1 Czech
1 England_IA.SG
1 Poland_ChopiceVeseleCulture
1 Lithuania_EMN_Narva
1 Iceland_Pre_Christian.SG
1 Sweden_BattleAxe.SG
1 Poland_BellBeaker_published
2 Faroes_EarlyModern.SG
2 England_IA_o.SG
2 Norwegian
2 Greenland_EarlyNorse.SG
2 Iceland_Early_Christian.SG
2 Russia_MLBA_Sintashta.SG
2 Russia_Ivanovo_Fatyanovo_BA.SG
2 Scotland_C_EBA_mediumhighEEF
2 Sweden_Gotland_Vasterbjers_PittedWare_BattleAxe_o_ minus.SG
2 Scotland_C_EBA_mediumhighEEF_published
2 Germany_Tollense_BA.SG
2 Russia_MBA_Poltavka_oEEF
2 Russia_Moscow_Fatyanovo_BA.SG
2 Ukraine_Viking_o.SG
2 Germany_EBA_Unetice_published
2 England_IA_Roman.SG
2 Sweden_Viking_o2.SG
2 Scotland_Viking_o.SG
2 Russia_Tver_Fatyanovo_BA.SG
2 Estonia_EarlyViking.SG
2 Scotland_LBA
2 Norway_Medieval.SG
2 Sweden_Late_N.SG
2 Czech_Bohemia_BellBeaker
2 Latvia_MN_o1.SG
2 Netherlands_BellBeaker
2 Denmark_EarlyViking.SG
2 Denmark_IA.SG
2 Russia_Yaroslavl_Fatyanovo_BA.SG
2 Lithuania_LN_o
2 Sweden_LN.SG
2 Germany_EBA_Unetice
2 Sweden_IA.SG
2 Czech_BellBeaker
2 Czech_Bohemia_Unetice_EBA
2 Estonia_CordedWare
2 England_MBA
2 Kazakhstan_Maitan_MLBA_Alakul
2 England_C_EBA
2 Belarusian
2 Sweden_Viking.SG
2 Ireland_EBA.SG
2 England_Viking_o.SG
2 Wales_C_EBA
2 Jew_Ashkenazi
2 Estonia_IdaViru_CordedWare_Neolithic.SG
2 Scotland_MBA
2 Ukrainian
2 England_BellBeaker_highEEF
2 Czech_EBA
2 Ukrainian_North
2 Greenland_EarlyNorse_o1.SG
2 Estonia_BA.SG
2 Scottish
2 Scotland_Mesolithic_all.SG
2 Estonian.DG
2 England_LBA
2 Czech_Bohemia_BellBeaker_oAnatolia2
2 Germany_BellBeaker
2 Latvia_HG.SG
2 Lithuania_BA
2 Netherlands_BA
2 Germany_BenzigerodeHeimburg_LN
2 Sweden_PWC.SG
2 Russia_Viking.SG
2 Germany_Mesolithic
2 Poland_Southeast_BellBeaker.SG
2 England_Viking.SG
2 England_BellBeaker
2 Estonia_CordedWare.SG
3 Estonia_CordedWare.SG_o1
3 Faroes_Viking.SG
3 Poland_Viking.SG
3 Sweden_IA_1.SG
3 Sweden_Motala_HG.SG
3 Scotland_C_EBA
3 England_C_EBA_lowEEF
3 Lithuania_Mesolithic
3 Russia_MLBA_Sintashta
3 Czech_BA_Veterov_1
3 England_C_EBA_highEEF
3 Finland_Levanluhta_B
3 Lithuania_EMN_Narva_o
3 Denmark_LN_BA.SG
3 Kazakhstan_MLBA_Alakul_Lisakovskiy
3 Latvia_HG
3 Czech_IA_Hallstatt.SG
3 Estonia_CordedWare.SG_o2
3 Poland_BellBeaker
3 Sweden_Gotland_Hemmor_PittedWare_BattleAxe_minus.S G
3 Poland_EBA
3 Iceland_Viking.SG
3 Czech_Bohemia_CordedWare
3 Germany_LN_Karsdorf
3 Denmark_Djursland_SingleGraveCulture.SG
3 Greenland_LateNorse.SG
3 Sweden_TRB_MN.SG
3 Sweden_Gotland_Ajvide_PittedWare_BattleAxe.SG
3 Poland_EBA.SG
3 Poland_EBA_Unetice.SG
3 Estonia_IA.SG
3 Sweden_Gotland_Vasterbjers_PittedWare_BattleAxe.SG
3 Russia_Andronovo.SG
3 England_LBA_lowEEF
3 Sweden_BAC.SG
3 Russia_SaltovoMayaki.SG
3 England_BellBeaker_lowEEF
3 Germany_CordedWare.SG
3 Russia_Srubnaya
3 Estonian
3 Norway_Medieval_o.SG
3 Sweden_Gotland_Hemmor_PittedWare_BattleAxe.SG
3 Norway_Viking.SG
4 Sweden_Gotland_Vasterbjers_PittedWare_BattleAxe_mi nus.SG
4 Denmark_BA.SG
4 Sweden_Viking_o1.SG
4 Latvia_MN
4 Poland_CWC_3.SG
4 Germany_CordedWare
4 Ukraine_IA_WesternScythian_o1.SG
4 Scotland_BellBeaker
4 Czech_CordedWare
4 IsleOfMan_Viking.SG
4 Russia_Srubnaya_Alakul.SG
4 Germany_CordedWare_published_o1
4 Russia_Viking_o.SG
4 Estonia_CWC.SG
4 Poland_Southeast_CordedWare.SG
4 Sweden_Mesolithic.SG
4 Kazakhstan_LBA_Guruldek_published
4 Russia_Potapovka_o2
4 Estonia_EMN_Narva
4 Russia_Sunghir_Medieval.SG
5 Sweden_Motala_HG
5 Kazakhstan_Georgievsky_MBA_published
5 Sweden_Mesolithic_o.SG
5 Lithuania_LN
5 Sweden_HG.SG
5 Poland_CWC.SG
5 Russian
5 Kazakhstan_Andronovo.SG
5 Russia_Afanasievo
5 Russia_MBA_Poltavka
5 Russia_Samara_EBA_Yamnaya
5 Russia_Petrovka
5 Czech_Bohemia_Jordanow_Michelsberg_N
5 Ukraine_Viking.SG
5 Russia_Samara_EBA_Yamnaya_published
5 England_C_EBA_published
5 Latvia_LN_CordedWare.SG
6 Russia_MLBA_Krasnoyarsk
6 Estonia_Medieval.SG
6 Russia_Afanasievo.SG
6 Czech_Bohemia_BellBeaker_oSteppe
6 Russia_MBA_Poltavka_published
6 Russia_MLBA_Sintashta_o2
6 Finnish.DG
6 Russia_Samara_EBA_Yamnaya_published2
6 Latvia_LN_CordedWare
6 Kazakhstan_MLBA_Sintashta_o.SG
6 Russia_MBA_Poltavka_o2
6 Poland_CordedWare_ProtoUnetice.SG
7 Belgium_UP_Magdalenian_udg
7 Kazakhstan_Maitan_MLBA_Alakul_o1
7 Kazakhstan_Shoendykol_MLBA_Fedorovo
7 Norway_N_HG.SG
7 Denmark_LN.SG
7 Kazakhstan_Mereke_MBA_o2
7 Sweden_PWC_o.SG
7 Russia_MLBA_Potapovka
7 FIN_o
7 Estonia_BA_o.SG
8 Kazakhstan_Zevakinskiy_BA
8 Russian.DG
8 Lithuania_Late_Antiquity.SG
8 Latvia_MN_o2
8 Russia_IA_EarlySarmatian
8 Kazakhstan_CentralSaka_o2.SG
8 Mordovian
8 Finnish
8 Norway_Mesolithic.SG
8 Russian.SDG
8 Russia_Yaroslavl_VolosovoLyalovo_N.SG
9 Kazakhstan_Sarmatian.SG
9 Russia_Popovo_HG
9 Karelian
9 Estonia_N_CombCeramic.SG
9 Russia_Kostenki14.SG
9 Belgium_UP_GoyetQ116_1_published
9 Denmark_LBA.SG
9 Russian_Archangelsk_Krasnoborsky
10 Russia_Sunghir3.SG
10 Russia_Sunghir4.SG
10 Belgium_UP_Magdalenian
10 Russia_Kostenki14
10 Belgium_UP_GoyetQ116_1_published_all
10 Norway_LN_BA.SG
10 Estonia_MN_CCC_1
10 Lithuania_LBA.SG
11 Netherlands_BellBeaker_published
11 Russia_MiddleSarmatian_SouthernUrals.SG
11 Russia_Sunghir2.SG
11 Veps
11 Kazakhstan_Sarmatian_IA
11 Russia_Potapovka
11 Estonia_MN_CCC_2
11 Ukraine_IA_WesternScythian.SG
11 Russia_Khvalynsk_Eneolithic
11 Russian_Archangelsk_Pinezhsky
12 Russia_Sunghir1.SG
12 Russia_HG_Karelia
12 Kazakhstan_Birlik_EIA.SG
12 Russia_LateSarmatian.SG
12 Russia_EarlySarmatian.SG
12 Russia_Arkhangelsk_Veretye_Mesolithic.SG
13 Kazakhstan_IA_Chanchar_published
13 Kazakhstan_LIA_Georgievsky_published
13 Russia_EarlySarmatian_SouthernUrals.SG
13 Russia_IA_Scythian_questionable
13 Russia_HG_Samara
13 Russia_Srubnaya_o1
14 Latvia_MN_o3
14 Russia_Vologda_Veretye_Mesolithic.SG
14 Russia_Sidelkino_HG.SG
14 Latvia_MN_Comb_Ware.SG
14 Russia_AfontovaGora2.SG
14 Russia_Kostenki12
15 Kazakhstan_Nomad_IA_o.SG
15 Scotland_C_EBA_published
15 Russian_Archangelsk_Leshukonsky
15 Kazakhstan_Maitan_MLBA_Alakul_o2
15 Russia_MLBA_Sintashta_o1
16 Russia_Potapovka_o1
16 Russia_EHG
16 Kazakhstan_Zevakinskiy_LBA_o
16 Russia_Mezhovskaya.SG
16 Tatar_Mishar
18 Russia_HG_Karelia.SG
18 Belgium_UP_GoyetQ376-19_published
18 Russia_LBA_Priobrazhenka
18 Kazakhstan_Mereke_MBA
19 Kazakhstan_MLBA_Zevakinskiy
19 Russia_Ust_Ishim.DG
19 Russia_Ust_Ishim_HG_published.DG
19 Russia_Andronovo_o.SG
20 Russia_Tagar.SG
20 Russia_MLBA_Sintashta_o3
20 Russia_Yana_UP.SG
21 Tatar_Kazan
21 Russia_MA1_HG.SG
21 Kazakhstan_Zevakinskiy_LBA
21 Russia_LBA_1.SG
23 Chuvash
23 Besermyan
24 Russia_Karasuk_oRISE.SG
25 Saami.WGA
25 Saami.DG
25 Russia_Chalmny_Varre
26 Russia_AfontovaGora3
26 Udmurt
27 Kazakstan_Sargat_IA
28 Russia_Gorokhov_IA_2
29 Russia_HG_Sosnoviy
30 Kazakhstan_Nomad_IA.SG
31 Finland_Levanluhta
32 Russia_Sargat_IA
33 Bashkir
33 Finland_Saami_IA.SG
34 Russia_HG_Tyumen
34 Russia_MLBA_Krasnoyarsk_o
34 Aleut_o1
34 Aleut_o1.DG
35 Kazakhstan_Botai_Eneolithic.SG
35 Norway_Viking_o1.SG
35 Russia_EasternScythian_SouthernUrals.SG
35 Kazakhstan_Botai_Eneolithic
36 Russia_Gorokhov_IA_3
37 Aleut
39 Russia_Tuva_IA_AldyBel
39 Russia_IA_3.SG
41 Kazakhstan_Tasmola_EIA
41 Kazakhstan_Central_Saka.SG
43 Russia_Siberia_Lena_EBA_o
43 Russia_KusnarenkovoKarajakupovo_Medieval.SG
46 Tatar_Siberian
47 Russia_BA_Okunevo.SG
47 Yukagir_Forest
47 Russia_Bolshoy
49 Kazakhstan_Central_Steppe_EMBA.SG
49 Tatar_Siberian_Zabolotniye
49 Kazakhstan_Kimak.SG
51 Mansi
51 Mansi.DG
52 Chukchi.DG
52 USA_AK_Prehistoric.SG
52 Aleut_o
52 Aleut_o.DG
55 Altaian_Chelkan
55 Kazakhstan_ZevakinoChilikta_IA_2.SG
55 Russia_Gorokhov_IA_1
56 Tlingit
58 Khakass_outlier
59 Tubalar
60 Canada_MDorset.SG
60 Kazakhstan_Kipchak2.SG
60 Shor_Khakassia
60 Russia_IA_2.SG
60 Shor_Mountain
61 Aleut.DG
61 Tubalar.DG
61 Kazakh
64 Selkup
64 Cree1.DG
66 Khakass
66 Ket
66 Even
67 Russia_Siberia_Tenisei_EBA
68 Russia_LBA_2.SG
68 Russia_LenaRiver_LUP.SG
72 Cree2.DG
72 Khakass_Kachin
72 Altaian
74 Altaian.DG
75 Kazakhstan_Hun_Elite_LIA
75 Enets
76 Russia_AngaraRiver_Medieval.SG
76 USA_Alaska_TrailCreek_9000BP.SG
80 Mongolia_LBA_CenterWest_4
80 Russia_UstIda_LN.SG
82 Russia_Kurma_EBA_o.SG
82 Russia_UstBelaya_Angara_Medieval
82 Tuvinian
82 Russia_Karasuk_o1.SG
83 Even_o.DG
83 Even_o
83 USA_Ancient_Beringian.SG
83 Evenk_FarEast
83 Russia_Kolyma_M.SG
84 Russia_UstBelaya_Angara_published
84 Tofalar
84 Kazakhstan_Birlik_Tasmola_EIA
84 Russia_UstBelaya_Angara_o_published
84 Russia_LenaRiver_N.SG
85 Russia_AngaraRiver_N.SG
85 Russia_UstIda_EBA.SG
85 Russia_UstBelaya_MED.SG
85 Russia_LakeBaikal_N.SG
85 Canada_LateDorset.SG
86 Todzin
86 Russia_UstBelaya_Angara
86 Russia_AngaraRiver_BA.SG
86 Buryat
86 Russia_Shamanka_EBA.SG
86 Russia_Kurma_EBA.SG
87 Russia_Siberia_Lena_EBA
87 Dolgan
87 Russia_Siberia_UP
87 Russia_Buryatia_M.SG
87 Kazakhstan_Nomad_HP.SG
87 Russia_UstBelaya_Angara.SG
87 Russia_LenaRiver_BA.SG
88 Russia_Buryatia_EIA
88 Khamnegan
88 Russia_Yana_Medieval.SG
89 Russia_LenaRiver_MiddleN.SG
89 Greenland_Saqqaq.SG
89 USA_AK_PaleoAleut_published
89 Mongolia_Khuvsgul_LateMedieval
89 Russia_LakeBaikal_BA.SG
89 Kazakhstan_Korgantas_IA
89 Russia_UstBelaya_EBA.SG
90 Yakut
90 Yakut.SDG
90 Russia_Uelen_IA.SG
90 Kazakhstan_Nomad_Hun_Sarmatian.SG
90 Russia_Siberia_Lena_EN
91 Russia_LenaRiver_EN.SG
91 Russia_Siberia_Angara_EN
91 Russia_Buryatia_Xiongnu
91 Russia_KuengaRiver_N_1.SG
91 Mongolia_EIA_3
91 Canada_MDorset_published
92 Yakut.DG
92 Itelmen.DG
92 Russia_Siberia_Irkutsk_EBA
92 Russia_Ekven_IA.SG
92 Itelmen
93 Canada_6500BP.SG
93 Russia_Uelen_OldBeringSea
93 Russia_Ekven_OldBeringSea.SG
93 Russia_Buryatia_PreBronze
93 Koryak
93 Chukchi1
93 Canada_BigBar_5700BP.SG
93 Russia_Uelen_OldBeringSea_published
93 USA_AK_PaleoAleut.SG
94 Russia_Ekven_OldBeringSea
94 Chipewyan.DG
94 USA_AK_Ancient_Athabaskan_1100BP.DG
94 Eskimo_Naukan.DG
94 USA_AK_Ancient_Athabaskan_1100BP.SG
94 USA_AK_NeoAleut
94 Eskimo_Naukan
94 USA_AK_PaleoAleut
94 Mongolia_EIA_SlabGrave_1
94 Chukchi
94 Canada_Thule.SG
94 Eskimo_ChaplinSireniki
94 Russia_Lokomotiv_Eneolithic.SG
95 Evenk_Transbaikal
95 USA_AK_Ancient_Athabaskan_1100BP
95 Yukagir_Tundra
95 Russia_Shamanka_Eneolithic.SG
95 Russia_CentralYakutia_LN.SG
95 Russia_AginBuryat_N.SG
95 Russia_AngaraRiver_EN.SG
95 USA_AK_NeoAleut_published
95 Eskimo_Sireniki.DG
96 USA_AK_Athabskan.SG
96 Russia_UstBelaya_Angara_o.SG
96 Eskimo_Chaplin.DG
96 Nganasan
96 Even.DG
96 Eskimo_Sireniki
97 Russia_KolymaRiver_LN.SG
97 Russia_Krasnoyarsk_BA.SG
97 Russia_Chita_BA.SG
98 Russia_KuengaRiver_N_2.SG
98 Oroqen
98 Russia_KadalinkaRiver_N.SG
98 Oroqen.SDG
99 Russia_CentralYakutia_IA.SG
99 Russia_ArgunRiver_M.SG
99 Nivh
99 Ulchi.DG
99 Oroqen.DG
99 Ulchi
100 Negidal

This finds populations that are closest to the Mari average when multiplied by MDS of FST:

$ printf %s\\n ,,,,,,,,,,,, 19,,,,,,,,,,,, 28,36,,,,,,,,,,, 26,32,36,,,,,,,,,, 26,35,28,21,,,,,,,,, 52,62,50,48,39,,,,,,,, 64,65,76,57,60,82,,,,,,, 114,114,122,110,111,127,76,,,,,, 111,111,123,109,112,130,83,56,,,,, 138,137,154,138,144,161,120,113,105,,,, 179,181,187,177,176,191,146,166,177,217,,, 122,127,124,116,108,121,113,145,151,185,203,, 146,150,150,140,135,141,133,164,170,204,220,41,>k13fst
$ Rscript -e 't=read.csv("reich.k13.ave",h=F,r=1);fst=as.matrix(as.dist(read.csv("k13fst",h=F)));fst=fst/mean(fst);t2=as.matrix(t)%*%cmdscale(fst,ncol(fst)-1);write.table(round(t2,6),"reich.k13.ave.mds",sep=",",quote=F,col.names=F)'
$ grep Mari.SG reich.k13.ave.mds|awk -F, 'NR==FNR{for(i=2;i<=NF;i++)a[i]=$i;next}$1{s=0;for(i=2;i<=NF;i++)s+=($i-a[i])^2;print s^.5,$1}' - reich.k13.ave.mds|sort -n|awk '{$1=sprintf("%.2f",$1)}1'|head -n16
0.00 Mari.SG
2.70 Udmurt
3.64 Bashkir.SG
4.05 Kazakstan_Sargat_IA
4.70 Finland_Levanluhta
5.28 Bashkir
5.35 Russia_Sargat_IA
5.65 Russia_Chalmny_Varre
5.88 Besermyan
6.03 Russia_Karasuk_oRISE.SG
6.41 Kazakhstan_Tasmola_Saka_IA
6.73 Kyrgyzstan_AlaiNura_IA
7.01 Saami.DG
7.23 Saami.WGA
7.25 Kyrgyzstan_Saka_IA
7.40 Kyrgyzstan_TianShan_Saka_o1.SG

Here's PCAs of samples where the combined percentage of the last four components is less than 20%:

https://i.ibb.co/x8wVLJg/1.png
https://i.ibb.co/crX5FbM/a.png

awk -F\\t '$5==0{print$7}' ho.anno|igno|grep -Fv .|grep -v _o|awk -F: 'NR==FNR{a[$0];next}$1 in a' - reich.k13 >modern
awk -F\\t '$5>0{print$7}' ho.anno|igno|grep -v _o|awk -F: 'NR==FNR{a[$0];next}$1 in a' - reich.k13 >ancient

library(tidyverse)
library(ggforce)

t=read.csv("modern",header=F,row.names=1)

t=t[rowSums(t[,10:13])<=20,]

fst=as.matrix(as.dist(read.csv("k13fst",header=F)))
t2=as.matrix(t)%*%cmdscale(fst,ncol(fst)-1)

p0=prcomp(t2)
pct=paste0(colnames(p0$x)," (",sprintf("%.1f",100*p0$sdev/sum(p0$sdev)),"%)")
p=as.data.frame(p0$x)

p[,1]=-p[,1]
p=p/sd(p[,1])

pop=sub(":.*","",rownames(t))
pop=sub("\\.(SG|DG|SDG|WGA)","",pop)

set.seed(1)
color=as.factor(sample(seq(1,length(unique(pop)))) )
col=rbind(c(60,80),c(25,95),c(100,70),c(30,70),c(7 0,50),c(60,100),c(20,50),c(15,40))
hues=max(ceiling(length(color)/nrow(col)),7)
pal1=as.vector(apply(col,1,function(x)hcl(seq(15,3 75,length=hues+1)[1:hues],x[1],x[2])))
pal2=as.vector(apply(col,1,function(x)hcl(seq(15,3 75,length=hues+1)[1:hues],ifelse(x[2]>50,.8*x[1],.2*x[1]),ifelse(x[2]>50,.3*x[2],100))))

i=1
xpc=sym(paste0("PC",i))
ypc=sym(paste0("PC",i+1))

p[,i]=p[,i]*diff(range(p[,i+1]))/diff(range(p[,i]))

centers=data.frame(aggregate(p,list(pop),mean),row .names=1)

ranges=apply(p,2,function(x)abs(max(x)-min(x)))
maxrange=max(ranges[c(i,i+1)])

ggplot(p,aes(!!xpc,!!ypc,group=0))+
ggforce::geom_voronoi_tile(aes(x=!!xpc,y=!!ypc,fil l=color[as.factor(!!pop)],color=color[as.factor(!!pop)]),size=.07,max.radius=maxrange/35)+
geom_label(data=centers,aes(x=!!xpc,y=!!ypc,label= rownames(centers)),color=pal2[color],fill=pal1[color],alpha=.7,size=2,label.r=unit(.1,"lines"),label.padding=unit(.1,"lines"),label.size=.1)+
labs(x=pct[i],y=pct[i+1])+
coord_fixed()+
scale_x_continuous(expand=expansion(.03))+
scale_y_continuous(expand=expansion(.03))+
scale_fill_manual(values=pal1)+
scale_color_manual(values=pal2)+
theme(
axis.text=element_blank(),
axis.ticks=element_blank(),
axis.ticks.length=unit(0,"pt"),
axis.title=element_text(color="black",size=8),
legend.position="none",
panel.background=element_rect(fill="white"),
panel.border=element_rect(color="gray90",fill=NA,size=.4),
panel.grid=element_blank(),
plot.background=element_rect(fill="white",color=NA)
)

ggsave(paste0(i,".png"),width=8,height=8)

Finally below is a heatmap of modern populations with no suffix like .SG or .DG. There are many samples that suffer from the calculator effect, so for example the Scottish average gets 85% North_Atlantic. In order to rearrange the branches of the clustering tree, I used MDS on the FST matrix of K13 in order to plot the 13 components of K13 in 12-dimensional space, and I then plotted the populations in 12-dimensional space by multiplying their component percentages with the matrix produced by MDS, and I used the value of the first dimension as a weight for the function `reorder.hclust`.

https://i.ibb.co/wcgGkmW/h.png

library(pheatmap)
library(vegan) # for reorder.hclust
library(colorspace) # for hex

t=read.csv("modern",row.names=1,header=F)
colnames(t)=c("North_Atlantic","Baltic","West_Med","West_Asian","East_Med","Red_Sea","South_Asian","East_Asian","Siberian","Amerindian","Oceanian","Northeast_African","Sub-Saharan")

ave=data.frame(aggregate(t,list(sub(":.*","",rownames(t))),mean),row.names=1)
ave=ave[rownames(ave)%in%readLines("pop"),]

fst=as.matrix(as.dist(read.csv("k13fst",header=F,check.names=F)))
ave2=as.matrix(ave)%*%cmdscale(fst,ncol(fst)-1)
hc=hclust(dist(ave2))
hc=reorder(hc,prcomp(ave2)$x[,1])

pheatmap::pheatmap(
ave,
filename="1.png",
cluster_cols=F,
clustering_callback=function(...)hc,
legend=F,
cellwidth=16,
cellheight=16,
treeheight_row=150,
treeheight_col=80,
fontsize=8,
border_color=NA,
display_numbers=T,
number_format="%.0f",
fontsize_number=7,
number_color="black",
colorRampPalette(hex(HSV(c(210,210,130,60,40,20,0) ,c(0,rep(.5,6)),1)))(256)
)

vbnetkhio

11-03-2021, 08:10 AM

I'm looking for a study on modern DNA, whose G25 results were also published. It included a few hundred modern samples, including a dozen Slovenians. Does anybody know what it is?

I thought it was this one, but I can't find those Slovenians in the list anymore?
https://anthrogenica.com/showthread.php?22733-651-New-Sample-for-G25

JamesBond007

11-03-2021, 08:23 AM

Leto

11-03-2021, 11:13 AM

Can you run some of those Cardona samples? Dodecad K12b would suffice.

EDIT
That post on Anthrogenica by David Bush links to a different study
https://onlinelibrary.wiley.com/doi/abs/10.1002/ajhb.23194

Siberian genetic diversity reveals complex origins of the Samoyedic-speaking populations
Tatiana M. Karafet, Ludmila P. Osipova, Olga V. Savina, Brian Hallmark, Michael F. Hammer

Komintasavalta

11-03-2021, 05:22 PM

Can you run some of those Cardona samples? Dodecad K12b would suffice.

K12b: https://pastebin.com/raw/PMTtnzZn
K13: https://pastebin.com/raw/Pe0wM1ea

EDIT
That post on Anthrogenica by David Bush links to a different study
https://onlinelibrary.wiley.com/doi/abs/10.1002/ajhb.23194

Yeah sorry, that was the right study. The files at Anthrogenica contain all 651 samples from this dataset: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE73996. Its title is "The genetic basis of adaptation to climatic stress in Siberian indigenous populations", so I confused it with Cardona et al. 2014, "Genome-Wide Analysis of Cold Adaptation in Indigenous Siberian Populations". But I think the dataset is from an unpublished paper whose samples were later used in the paper you linked to.

Leto

11-03-2021, 06:41 PM

Thank you for running them, I see a few valuable populations in that spreadsheet! :thumb001: I'm processing them for Dodecad and maybe a couple for K13 too.

Komintasavalta

11-04-2021, 03:13 AM

Here's how you can use my K13 datasheet for the Reich dataset to make a polygonal diagram where each corner of the polygon represents one component:

library(tidyverse)
library(ggforce)
library(colorspace)

t=read.csv("https://drive.google.com/uc?export=download&id=15Mvba7Bw07VtixiBO_EctOhPPECGzZC9",row.names=1,check.names=F)
t=t/100

fst=as.matrix(as.dist(read.csv(header=F,text=",,,,,,,,,,,,
19,,,,,,,,,,,,
28,36,,,,,,,,,,,
26,32,36,,,,,,,,,,
26,35,28,21,,,,,,,,,
52,62,50,48,39,,,,,,,,
64,65,76,57,60,82,,,,,,,
114,114,122,110,111,127,76,,,,,,
111,111,123,109,112,130,83,56,,,,,
138,137,154,138,144,161,120,113,105,,,,
179,181,187,177,176,191,146,166,177,217,,,
122,127,124,116,108,121,113,145,151,185,203,,
146,150,150,140,135,141,133,164,170,204,220,41,")))

t=t[!grepl("\\.REF|rel\\.|fail\\.|\\.contam|Ignore_|_dup|_cont am|_lc|_father|_mother|_son|_daughter|_brother|_si ster|_relative|_sibling|_twin|Neanderthal|Denisova |Vindija_light|Gorilla|Macaque|Marmoset|Orangutan| Primate_Chimp|hg19ref|_o",rownames(t)),]

rownames(t)=%sub("\\.(SG|DG|SDG|WGA|WGC)|_published","",rownames(t))
t=data.frame(aggregate(t,list(sub(":.*","",rownames(t))),mean),row.names=1,check.names=F)

mds=as.matrix(t)%*%cmdscale(fst,ncol(fst)-1)

t=as.data.frame(cbind(t[,2],t[,9],t[,8],rowSums(t[,c(1,3:7,10:13)])))
names(t)=c("Baltic","Siberian","East_Asian","Other")

start=ifelse(ncol(t)==4,.25,0)
corners=sapply(c(sin,cos),function(x)x(head((start +seq(0,2,length.out=ncol(t)+1))*pi,-1)))
corners=corners*min(2/diff(apply(corners,2,range)))
corners[,2]=corners[,2]-mean(range(corners[,2]))

xy=as.data.frame(as.matrix(t)%*%corners)
grid=as.data.frame(rbind(cbind(corners,rbind(corne rs[-1,],corners[1,])),cbind(corners,matrix(apply(corners,2,mean),ncol =2,nrow=ncol(t),byrow=T))))

seg=lapply(1:3,function(i)as.matrix(dist(mds))%>%apply(1,function(x)unlist(xy[names(sort(x)[i]),],use.names=F))%>%t%>%cbind(xy))%>%do.call(rbind,.)%>%setNames(paste0("V",1:4))

k=as.factor(cutree(hclust(dist(mds)),32))

set.seed(1)
hue=seq(0,360,length.out=nlevels(k)+1)%>%head(-1)%>%sample()
pal1=hex(colorspace::HSV(hue,.5,1))
pal2=hex(colorspace::HSV(hue,.3,1))

angle=head(seq(360,0,length.out=ncol(t)+1),-1)
angle=ifelse(angle>90&angle<=270,angle+180,angle)

ggplot(xy,aes(x=V1,y=V2))+
geom_polygon(data=as.data.frame(corners),fill="gray25")+
# geom_text(data=as.data.frame(corners),aes(x=1.04*V 1,y=1.04*V2),label=colnames(t),size=3.2,angle=angl e,color="gray85")+
geom_text(data=as.data.frame(corners),aes(x=V1,y=V 2+sign(V2)*.02),vjust=(1-corners[,2])/2,hjust=(1+corners[,1])/2,label=colnames(t),size=3.2,color="gray85")+
geom_segment(data=grid,aes(x=V1,y=V2,xend=V3,yend= V4),color="gray30",size=.4)+
ggforce::geom_mark_hull(aes(group=!!k,color=!!k,fi ll=!!k),concavity=1000,radius=unit(.15,"cm"),expand=unit(.15,"cm"),alpha=.15,size=.1)+
geom_segment(data=seg,aes(x=V1,y=V2,xend=V3,yend=V 4),color="gray10",size=.25)+
geom_point(aes(color=k),size=.5)+
geom_text(aes(label=rownames(xy),color=!!k),size=2 .2,vjust=-.6)+
coord_fixed(xlim=c(-1,1),ylim=c(-1,1))+
scale_fill_manual(values=pal1)+
scale_color_manual(values=pal2)+
theme(
axis.text=element_blank(),
axis.ticks=element_blank(),
axis.title=element_blank(),
legend.position="none",
panel.background=element_rect(fill="gray20"),
panel.grid=element_blank(),
plot.background=element_rect(fill="gray20",color=NA,size=0),
plot.margin=margin(0,0,0,0)
)

ggsave("1.png",width=11,height=11)

Here you can see that CentralYakutia_IA (yak030) has even higher Siberian than the Nganasan average. The yak030 sample is missing from G25, but in the Reich dataset, it's the closest ancient sample to Nganasans:

https://i.ibb.co/mFqvXJ8/1.png

Here some populations like Scottish and BedouinB are outliers, because their samples suffer from the calculator effect:

https://i.ibb.co/KWHTxmV/eurogenes-k13-reich-polygon-modern.png

This shows all ancient and modern populations:

https://i.ibb.co/GQCpCKM/eurogenes-k13-reich-polygon.jpg

Leto

11-04-2021, 09:35 PM

Here's how you can use my K13 datasheet for the Reich dataset to make a polygonal diagram where each corner of the polygon represents one component:

I appreciate your interest in those graphs, I just find it hard to read some of them.

Komintasavalta

11-08-2021, 07:20 PM

@Lucas and @michal3141: Where can I get the FST matrix for your K47 and K25 calculators? I'm using Mantel's test to check if high-K calculators produce higher correlation with f2 distance than low-K calculators.

I also want to test some very low-K calculators like Gedrosia K3, but I need its .alleles and .F files and its FST matrix.

Or can some Windows user just post the .F and .alleles files for all calculators from Admixture Studio? I also need MDLP World 22.

Komintasavalta

11-13-2021, 03:18 AM

I now finished running K13 for all 14,313 samples in the 1240K+HO version of the Reich dataset: https://drive.google.com/file/d/15Mvba7Bw07VtixiBO_EctOhPPECGzZC9.

I now also ran Eurogenes K13 for all samples in the 1240K version of the Reich dataset: https://drive.google.com/file/d/15Mvba7Bw07VtixiBO_EctOhPPECGzZC9.

It should produce more accurate results particularly for ancient samples with low SNP count, because the 1240K version has about two times as many SNPs as the 1240K+HO version, but it has over 3 times as many SNPs that overlap with Eurogenes K13:

$ wget https://reichdata.hms.harvard.edu/pub/datasets/amh_repo/curated_releases/V50/V50.0/SHARE/public.dir/v50.0_{HO,1240K}_public.snp
$ for x in 1240K HO;do cut -d\ -f1 /usr/local/lib/python3.9/site-packages/admix/data/K13.alleles|LC_ALL=C sort|comm -12 <(awk '{print$1}' v50.0_${x}_public.snp|LC_ALL=C sort) -|wc -l|echo "$(cat) out of $(wc -l< v50.0_${x}_public.snp) SNPs overlap with $x";done
177354 out of 1233013 SNPs overlap with 1240K
52770 out of 597573 SNPs overlap with HO

For samples that were included in both versions, the average in admixture percentages was 1.0 percentage points. But for samples with less than 200,000 SNPs, it was common for the difference to be over 2 percentage points:

https://i.imgur.com/ud4lw0A.png

Here's a PCA of samples that are at least 8000 years old and that have at least 100,000 SNPs:

https://i.imgur.com/s8fBF5s.png

This makes population averages where samples with less than 100,000 SNPs are excluded:

curl -LsO https://reichdata.hms.harvard.edu/pub/datasets/amh_repo/curated_releases/V50/V50.0/SHARE/public.dir/v50.0_1240K_public.anno
curl -Lso reich.1240k.k13 'https://drive.google.com/uc?export=download&id=15Mvba7Bw07VtixiBO_EctOhPPECGzZC9'
tav()(awk '{n[$1]++;for(i=2;i<=NF;i++){a[$1,i]+=$i}}END{for(i in n){o=i;for(j=2;j<=NF;j++)o=o FS sprintf("%f",a[i,j]/n[i]);print o}}' "FS=${1-$'\t'}")
awk -F\\t '$21>=1e5{print$2}' v50.0_1240K_public.anno|awk -F'[:,]' 'NR==FNR{a[$0];next}$2 in a' - reich.1240k.k13|sed 's/:[^,]*//'|tav ,|sort>reich.1240k.k13.ave

I think these calculators would give more accurate results with low-SNP ancient samples if they just included all SNPs from the 1240K dataset with no LD pruning. But out of the calculators that come with the Python admix script, even the calculators with the highest SNP count only include about 200,000 SNPs:

$ cd /usr/local/lib/python3.9/site-packages/admix/data/
$ wc -l *.alleles|sort -n
27187 Africa9.alleles
35648 AncientNearEast13.alleles
38496 puntDNAL.alleles
76261 MichalK25.alleles
76267 K47.alleles
92632 KurdishK10.alleles
101647 K7AMI.alleles
101647 K8AMI.alleles
112117 TurkicK11.alleles
118536 MDLPK27.alleles
159620 EUtest13.alleles
159620 Jtest14.alleles
164990 Eurasia7.alleles
165688 K13M2.alleles
165688 K14M1.alleles
165688 K18M4.alleles
165688 K25R1.alleles
165688 K36.alleles
165688 K7M1.alleles
166255 globe10.alleles
166255 globe13.alleles
166770 K12b.alleles
166770 K7b.alleles
169131 weac2.alleles
170288 E11.alleles
170822 world9.alleles
182705 K13.alleles
184719 K15.alleles
188173 HarappaWorld.alleles

Coastal Elite

11-13-2021, 03:26 AM

You can post mumbo gumbo graphs all day but you'll never have the out of the box thinking to create a calculator like this: https://www.theapricity.com/forum/showthread.php?318290-Euro-Stereotype-Calculator-(Scaled)

The east shifted mind can't comprehend my level of humor. Feel free to build off my western ideas.

Coastal Elite

11-13-2021, 03:54 AM

It's up to you to take this whole game to the next level. Don't get lost in the minutiae. You need more WOG-like big picture thinking.

vbnetkhio

11-17-2021, 09:55 AM

Komintasavalta

11-17-2021, 11:59 AM

could you run this trough k36?

https://easyupload.io/i17wjl

EG600001,0,0,0,0,0,8.29,0,0,6.46,0,12.16,1.37,13.1 6,8.97,3.07,10.33,0,8.52,0,2.51,0,6.92,0,10.34,.91 ,0,0,0,0,0,0,0,3.15,0,3.82,0
EG600002,0,0,0,.71,0,3.64,0,0,10.4,0,19.84,.63,12. 07,7.0,4.96,3.47,0,9.02,0,4.06,0,3.62,6.65,9.05,0, 0,.03,0,0,0,0,0,2.68,0,0,2.18
EG600003,0,0,1.06,5.43,0,6.28,0,0,5.6,0,22.26,0,14 .45,9.11,.38,2.49,0,9.73,0,0,0,3.05,8.77,8.26,0,.0 5,0,0,0,0,0,0,2.86,0,.22,0
EG600004,0,1.5,.56,1.62,0,4.55,0,0,9.56,0,18.25,6. 78,6.77,12.39,.86,9.7,0,5.5,0,0,0,5.9,3.78,6.42,0, .06,0,0,0,0,0,0,2.1,0,0,3.69
EG600005,0,0,0,.34,0,7.82,0,0,8.96,0,14.55,0,17.11 ,9.36,3.83,5.69,0,13.86,0,1.67,0,3.46,3.14,10.2,0, 0,0,0,0,0,0,0,0,0,0,0
EG600006,0,0,.49,1.25,0,8.49,0,0,3.91,0,22.96,.98, 16.9,10.69,6.73,5.06,0,5.15,0,0,0,6.08,0,8.97,0,0, 0,0,0,0,0,0,.12,0,1.16,1.07
EG600007,0,0,1.85,3.48,0,10.37,0,0,9.23,0,16.16,1. 92,13.73,6.82,4.78,5.59,0,5.51,0,3.03,0,3.57,5.14, 6.0,0,0,0,0,0,0,0,0,.54,0,.56,1.73
EG600008,0,0,.6,3.1,0,6.59,0,0,4.07,0,17.74,6.13,8 .88,13.1,0,9.98,0,10.45,0,0,.75,3.7,4.28,4.82,0,0, 0,0,0,.18,.95,0,2.48,0,0,2.18
EG600009,.02,.7,.41,4.02,0,6.38,0,0,5.17,0,19.08,1 .29,14.11,6.67,3.47,11.09,0,6.95,0,0,0,6.26,.74,8. 25,0,0,0,0,0,0,0,0,1.53,0,3.08,.8
EG600010,0,0,2.92,.26,0,7.38,0,0,8.49,0,19.72,4.7, 11.26,9.62,3.8,4.25,0,11.69,0,1.05,.22,4.54,2.46,5 .72,0,0,0,0,0,0,0,0,1.21,0,0,.72
EG600011,0,0,0,0,0,8.4,0,.01,7.35,0,19.67,0,9.93,8 .62,2.11,7.89,0,14.29,0,0,0,5.66,3.53,3.4,0,0,0,0, .2,0,0,0,0,0,5.29,3.65
EG600012,0,0,1.29,3.78,0,4.48,0,0,6.21,0,21.14,0,1 3.77,8.39,.84,10.33,0,7.13,0,.94,0,3.78,2.01,11.73 ,0,0,0,0,0,0,0,0,2.27,0,1.91,0
EG600013,0,0,2.94,.5,0,8.8,0,0,12.44,0,22.06,0,10. 45,13.01,4.09,3.87,0,3.37,0,0,0,12.04,.87,3.35,0,0 ,0,0,0,0,0,0,1.71,0,.51,0
EG600014,0,0,.91,.18,0,6.11,0,0,7.41,0,26.3,0,10.0 5,7.8,5.19,8.02,0,2.7,0,.21,0,8.22,4.14,9.38,0,0,0 ,0,0,0,0,0,0,0,2.34,1.05
EG600015,.59,0,1.4,1.81,0,7.42,0,0,6.49,0,26.37,0, 16.12,10.71,2.18,4.85,0,2.55,.04,0,0,7.61,1.53,7.8 2,0,.22,0,0,0,0,0,0,1.89,.01,0,.38
EG600016,0,0,0,4.1,0,8.61,0,0,4.45,0,22.21,0,14.25 ,14.32,2.1,6.3,0,3.59,0,0,0,2.89,5.02,8.03,0,0,0,0 ,0,.49,0,0,.05,0,2.93,.65
EG600017,0,0,0,1.32,0,5.34,0,0,5.37,0,25.8,0,17.02 ,12.76,1.51,2.75,0,8.14,0,0,0,.83,3.56,11.23,0,0,0 ,0,0,0,0,0,4.36,0,0,0
EG600018,0,0,.33,1.66,0,8.83,0,0,8.26,0,20.28,0,12 .11,5.89,3.98,4.53,0,12.44,0,.88,0,5.35,3.85,5.33, 0,0,0,0,0,0,1.08,0,2.64,0,0,2.56
EG600019,0,0,6.44,1.26,0,7.77,0,2.74,3.14,1.62,16. 69,0,10.57,13.85,7.59,1.37,0,0,0,0,0,3.13,4.79,5.2 8,0,0,0,.11,4.53,0,2.04,0,3.62,0,3.45,0
EG600020,0,.44,1.4,1.98,0,3.03,0,0,13.16,0,20.95,0 ,12.25,14.97,.65,9.09,0,8.48,0,0,0,2.58,5.02,4.33, 0,0,0,0,0,0,0,0,1.67,0,0,0
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There were some indel alleles like rs3831308 (https://www.ncbi.nlm.nih.gov/snp/rs3831308) (TCCTGCCCTACCCA), so I got this error: "Error: --recode 23 cannot be used with multi-character allele names." Therefore I excluded all alleles with multi-character names:

plink --bfile ukr_filtered --exclude <(awk 'length($5)>1||length($6)>1' ukr_filtered.bim|cut -f2) --make-bed --out ukr

JQP4545

02-28-2024, 02:47 AM

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EG600079,.17,0,0,1.76,0,8.69,0,0,10.3,0,26.45,0,14 .26,13.39,3.44,0,0,6.09,0,.49,0,7.76,1.37,5.84,0,0 ,0,0,0,0,0,0,0,0,0,0
EG600080,0,0,1.62,1.01,0,8.31,0,0,9.2,0,27.47,0,15 .54,14.92,.9,5.0,0,3.61,0,0,0,3.38,.23,6.9,0,0,0,0 ,0,0,0,0,.85,0,1.07,0
EG600081,0,0,0,4.3,0,8.59,.3,0,8.45,0,22.38,1.78,1 8.6,10.5,5.26,0,0,2.52,0,0,.05,9.9,.68,4.18,0,0,0, 0,0,.16,.9,0,1.1,.36,0,0
EG600082,.64,0,0,2.11,0,6.46,0,0,4.08,0,24.5,1.21, 16.49,11.86,.53,5.62,0,9.56,0,0,0,3.67,0,11.34,0,0 ,0,0,0,0,0,0,1.63,.31,0,0
EG600083,0,0,0,1.88,0,8.43,0,0,10.54,0,19.66,0,20. 56,13.31,3.45,6.51,0,5.29,0,.29,0,4.57,0,4.27,0,0, 0,0,0,0,.01,0,.24,0,1.0,0
EG600084,0,0,0,.2,0,8.47,0,0,6.55,0,22.98,0,18.35, 14.68,1.95,4.11,0,4.47,0,0,0,7.31,1.42,6.88,0,.08, 0,0,0,0,.58,0,1.82,.14,0,0
EG600085,0,0,0,.85,0,7.88,0,0,6.71,0,22.67,0,20.58 ,12.52,1.71,.14,0,.67,0,0,0,7.61,1.59,10.93,0,0,0, 0,0,0,0,0,4.66,0,.69,.8
EG600086,0,0,.02,2.06,0,10.95,0,0,2.56,0,28.89,0,1 6.57,7.27,0,0,0,5.87,0,0,0,5.63,3.12,10.96,0,0,0,0 ,0,0,.19,0,2.64,.14,2.25,.88
EG600087,0,0,0,0,0,6.17,0,0,8.06,0,24.85,.04,14.29 ,14.98,3.16,5.3,0,5.07,0,0,.84,4.24,2.14,7.49,0,0, 0,0,0,0,0,0,3.15,0,.23,0
EG600088,0,0,0,0,0,7.48,0,0,6.53,0,25.78,0,18.02,1 2.28,6.36,2.03,0,5.98,0,0,0,7.63,0,6.06,0,0,0,0,0, 0,0,0,1.76,0,0,.1
EG600089,0,0,1.8,.21,0,9.46,0,0,8.37,0,15.68,0,16. 8,6.57,4.43,5.39,0,8.83,0,0,0,4.02,3.41,11.82,0,0, 0,0,0,0,.46,.22,1.8,0,.43,.32
EG600090,0,0,0,.85,0,11.71,0,0,7.65,0,14.48,5.46,1 7.68,10.08,2.7,9.48,0,3.03,0,0,0,5.47,5.13,4.34,0, 0,0,0,0,0,1.25,0,.69,0,0,0
EG600091,0,0,0,1.38,0,7.28,0,0,7.49,0,24.02,0,18.5 2,15.21,.59,6.2,0,3.64,0,0,0,2.79,2.86,6.66,0,.1,. 01,0,0,0,.38,.09,1.89,.88,0,0
EG600092,0,0,0,2.98,0,7.07,0,0,10.5,0,20.31,0,14.2 ,10.42,2.99,4.49,0,1.0,0,0,0,7.0,3.84,9.6,0,0,0,0, 0,1.37,.3,0,2.53,0,1.41,0
EG600093,0,0,1.72,2.2,0,8.47,0,0,7.65,0,11.88,2.47 ,9.48,10.79,1.36,9.53,0,6.38,0,10.3,0,0,3.2,3.62,0 ,0,0,0,0,0,5.03,0,3.09,0,2.43,.39
EG600094,0,0,0,0,0,9.17,0,0,8.81,0,22.8,0,16.46,13 .47,6.22,6.21,0,1.46,0,0,0,1.66,0,8.45,0,0,0,0,0,0 ,.68,0,4.6,0,0,0
EG600095,0,0,0,0,0,9.27,0,0,7.66,0,21.58,.07,14.11 ,9.26,4.74,4.31,0,5.19,0,2.21,.16,5.04,.99,10.06,0 ,0,0,0,0,0,0,0,2.39,0,0,2.95
EG600096,.34,0,2.66,1.31,0,7.88,0,0,7.6,0,17.11,.4 8,13.87,9.96,2.66,1.35,0,5.67,0,2.5,0,10.18,2.32,7 .71,0,.19,0,0,0,0,.03,0,2.55,0,.77,2.85
EG600097,0,2.05,0,0,0,4.31,0,0,9.38,0,18.69,0,9.33 ,11.61,3.08,2.86,0,10.71,0,1.82,0,5.92,0,9.51,0,0, 0,0,0,0,6.14,0,2.53,0,.38,1.69
EG600098,0,0,0,.13,0,10.75,0,0,5.45,0,24.95,0,17.8 6,12.38,3.49,2.51,0,0,0,0,0,6.09,3.56,9.06,0,0,0,0 ,0,0,0,0,.36,0,3.41,0

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