Many VURers, Saamis are closer to many Turkics/Central Asians than to most Euros according to G25?

[Zanzibar]

Using G25, this seems to be the case:

Distance to: Mari

0.11547308 Bashkir
0.13857526 Tatar_Siberian
0.14622919 Tatar_Siberian_Zabolotniye
0.15879922 Mansi
0.16609517 Turkmen
0.17229907 Uzbek
0.17348576 Khanty
0.17705239 Finnish_East
0.17783813 Nogai
0.18422090 Iran_Turkmen
0.19255765 Finnish
0.19535284 Tajik_Shugnan
0.19586713 Hazara_Afghanistan
0.19923069 Uygur
0.19996889 Karakalpak
0.20260554 Tajik_Ishkashim
0.20344348 Hazara
0.21081083 Russian_Tver
0.21182997 Tubalar
0.21232139 Tajik_Yagnobi
0.21763448 Estonian
0.22557314 Russian_Smolensk
0.22981453 Polish
0.23081106 Hungarian
0.23128921 Latvian
0.23172467 Swedish
0.23796045 Icelandic
0.23996963 Bosnian
0.24026907 German
0.24118352 Irish
0.24241418 English
0.24252065 Romanian
0.26465765 Italian_Piedmont


Distance to: Udmurt

0.09797134 Bashkir
0.12750545 Finnish_East
0.13114207 Turkmen
0.13310796 Tatar_Siberian
0.14089777 Tajik_Shugnan
0.14179315 Finnish
0.14393915 Iran_Turkmen
0.15093452 Uzbek
0.15098617 Tajik_Ishkashim
0.15155844 Tatar_Siberian_Zabolotniye
0.15961422 Tajik_Yagnobi
0.15979505 Russian_Tver
0.17017327 Estonian
0.17152629 Mansi
0.17241783 Nogai
0.17796271 Russian_Smolensk
0.18020743 Swedish
0.18059071 Polish
0.18103482 Hungarian
0.18369906 Latvian
0.18382164 Hazara_Afghanistan
0.18579149 Khanty
0.18647838 Icelandic
0.18890984 Uygur
0.18894553 Irish
0.19010287 German
0.19029509 Bosnian
0.19164537 English
0.19445041 Hazara
0.19510247 Romanian
0.19868197 Karakalpak
0.21214030 Tubalar
0.22032703 Italian_Piedmont



Distance to: Saami

0.11182593 Bashkir
0.12036459 Finnish_East
0.13826217 Finnish
0.14216068 Tatar_Siberian
0.15607780 Tatar_Siberian_Zabolotniye
0.16075159 Russian_Tver
0.16336793 Turkmen
0.16632238 Estonian
0.17367742 Uzbek
0.17400811 Mansi
0.17827602 Tajik_Shugnan
0.17868672 Iran_Turkmen
0.17931411 Latvian
0.17952044 Russian_Smolensk
0.18157993 Nogai
0.18279075 Swedish
0.18381285 Polish
0.18837516 Tajik_Ishkashim
0.18848438 Khanty
0.18949914 Hungarian
0.19039592 Icelandic
0.19534091 Irish
0.19658845 Tajik_Yagnobi
0.19719818 German
0.19782542 English
0.20117721 Bosnian
0.20194140 Hazara_Afghanistan
0.20432707 Uygur
0.20636918 Karakalpak
0.20953171 Romanian
0.21102027 Hazara
0.21653079 Tubalar
0.23687648 Italian_Piedmont


The most Mongoloid-shifted Saami individual:

Distance to: Saami:GS000035025

0.10832232 Bashkir
0.13407839 Tatar_Siberian
0.14117080 Tatar_Siberian_Zabolotniye
0.14321710 Finnish_East
0.15780722 Mansi
0.16114704 Finnish
0.17090740 Khanty
0.17232113 Turkmen
0.17544998 Uzbek
0.17726949 Nogai
0.18446833 Russian_Tver
0.18893651 Estonian
0.19088560 Iran_Turkmen
0.19462396 Tajik_Shugnan
0.19982472 Karakalpak
0.19993139 Hazara_Afghanistan
0.20114102 Latvian
0.20143800 Russian_Smolensk
0.20256351 Uygur
0.20368092 Tajik_Ishkashim
0.20500438 Tubalar
0.20707970 Swedish
0.20715251 Polish
0.20743505 Hazara
0.21328762 Hungarian
0.21434038 Icelandic
0.21449101 Tajik_Yagnobi
0.21949449 Irish
0.22140021 German
0.22170772 English
0.22482493 Bosnian
0.23282629 Romanian
0.25936264 Italian_Piedmont


Most Mongoloid-shifted Udmurt individual:

Distance to: Udmurt:udmurd8

0.08187760 Bashkir
0.11499101 Tatar_Siberian
0.12768661 Turkmen
0.13030726 Tatar_Siberian_Zabolotniye
0.14008865 Uzbek
0.14503560 Iran_Turkmen
0.15002433 Finnish_East
0.15051991 Mansi
0.15082985 Tajik_Shugnan
0.15733351 Nogai
0.15932898 Tajik_Ishkashim
0.16412459 Finnish
0.16433979 Khanty
0.16977493 Hazara_Afghanistan
0.17150233 Tajik_Yagnobi
0.17470455 Uygur
0.17977632 Hazara
0.18225833 Karakalpak
0.18263746 Russian_Tver
0.19334510 Estonian
0.19378021 Tubalar
0.20046634 Russian_Smolensk
0.20108449 Swedish
0.20161450 Hungarian
0.20302204 Polish
0.20680134 Icelandic
0.20715504 Latvian
0.20848813 Irish
0.21031218 German
0.21038218 Bosnian
0.21127078 English
0.21365826 Romanian
0.23643305 Italian_Piedmont


Most Mongoloid-shifted Mari individual:
Distance to: Mari:mari1

0.11040352 Bashkir
0.13218886 Tatar_Siberian
0.13714602 Tatar_Siberian_Zabolotniye
0.14953210 Mansi
0.16383451 Khanty
0.16693582 Turkmen
0.16971483 Uzbek
0.17234959 Nogai
0.18345203 Finnish_East
0.18677072 Iran_Turkmen
0.19206068 Hazara_Afghanistan
0.19396984 Karakalpak
0.19471678 Uygur
0.19885824 Hazara
0.19894694 Finnish
0.20018331 Tajik_Shugnan
0.20393972 Tubalar
0.20717671 Tajik_Ishkashim
0.21750578 Tajik_Yagnobi
0.21774718 Russian_Tver
0.22484249 Estonian
0.23248012 Russian_Smolensk
0.23707678 Polish
0.23795651 Hungarian
0.23845057 Latvian
0.23846213 Swedish
0.24458502 Icelandic
0.24725899 Bosnian
0.24734527 German
0.24755833 Irish
0.24910385 English
0.24978596 Romanian
0.27156481 Italian_Piedmont


What do you think? I didn't post the ones for Saami_Kola, Komi, Mordvins as they seem to be closer to Euros than Central Asians are unlike Saami, Udmurt, Mari, etc probably due to much lower Mongoloid ancestry and more closer geographic proximity to Europe.

Will also include Chuvash here as they seem to be genetically Finno-Ugric but linguistically Turkicized:

Distance to: Chuvash

0.11489170 Bashkir
0.12697437 Finnish_East
0.14117864 Finnish
0.14159654 Turkmen
0.14825872 Tatar_Siberian
0.15316901 Iran_Turkmen
0.15669270 Tajik_Shugnan
0.15719659 Russian_Tver
0.16395802 Uzbek
0.16630835 Estonian
0.16691995 Tajik_Ishkashim
0.16950335 Tajik_Yagnobi
0.16963873 Tatar_Siberian_Zabolotniye
0.17250406 Russian_Smolensk
0.17616421 Polish
0.17715033 Hungarian
0.17969626 Swedish
0.18028483 Latvian
0.18169810 Nogai
0.18614863 Bosnian
0.18677826 Icelandic
0.18773898 German
0.18943428 Mansi
0.18993492 Romanian
0.19002238 Irish
0.19112287 English
0.19689561 Hazara_Afghanistan
0.20067179 Uygur
0.20461346 Khanty
0.20627424 Hazara
0.20868481 Karakalpak
0.21509629 Italian_Piedmont
0.22868145 Tubalar


Thoughts? As you can see, a lot of them are genetically closer to Siberian Tatars, Turkmens, Uzbeks, Nogais, Karakalpaks and even Hazaras than to most Euros. Are you shocked?

I wonder if the results will different using the gedmatch calculators.

[Zanzibar]

bump

[travv]

I think it’s pretty clear that all Mongoloids are closer to each other than to Caucasoids.

So, no I am not shocked.

[Komintasavalta]

I used ADMIXTOOLS 2 to calculate FST distances between populations in the 1240K+HO dataset:

https://i.ibb.co/3Fb1dKF/a.png

Saami are closer to Uzbeks than to Hungarians. And they are closer to Stavropol Nogais than to Romanians. The population labeled Saami.DG consists of two individuals from a region of Finland that is part of the Northern Saami area.

Arkhangelsk Russians from Leshukonsky are also closer to Tajiks than to North Italians.

On surprising thing is that Chuvashes are closer to Tajiks than to Udmurts, but Udmurts are a drifted population that is far from everyone.

Estonians are closer to Kazan Tatars than to Icelandics, but maybe it's because Tatars are a mixed population that also has a low number of shared IBD segments with other populations: "Together, the low number of shared IBDs within the same population and the high values for relative relatedness from multiple DHGR components (Supplementary Table S4) indicate the populations with the strongest admixtures where millions of people from remote populations mixed with each other for hundreds of years. In Europe, such admixed populations include the Moldavians, Greeks, Italians, Hungarians, and Tatars, among others." (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7696950/)


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

pop=unlist(strsplit("Bashkir
Chuvash
English
Estonian
Finnish
Hungarian
Icelandic
Italian_North
Karakalpak
Karelian
Kyrgyz_Tajikistan
Mansi
Nogai_Astrakhan
Nogai_Karachay_Cherkessia
Nogai_Stavropol
Norwegian
Romanian
Russian
Russian_Archangelsk_Krasnoborsky
Russian_Archangelsk_Leshukonsky
Russian_Archangelsk_Pinezhsky
Saami.DG
Tajik
Tatar_Kazan
Tatar_Mishar
Tatar_Siberian
Tatar_Siberian_Zabolotniye
Turkmen
Udmurt
Uyghur
Uzbek","\n"))

f=fst("path/to/v44.3_HO_public",pop)

df=as.data.frame(f[,-4])
df2=rbind(df,setNames(df[,c(2,1,3)],names(df)))
t=xtabs(df2[,3]~df2[,1]+df2[,2])

pheatmap::pheatmap(
1000*t,
filename="a.png",
clustering_callback=function(...)reorder(hclust(as .dist(t)),t["Italian_North",]),
# clustering_callback=function(...)hclust(dist(t)),
legend=F,
border_color=NA,
cellwidth=18,
cellheight=18,
treeheight_row=80,
treeheight_col=80,
display_numbers=T,
number_format="%.0f",
number_color="black",
colorRampPalette(hex(HSV(c(210,210,130,60,40,20,0) ,c(0,.5,.5,.5,.5,.5,.5),1)))(256)
)

Based on the first two dimensions in a SmartPCA run, Chuvashes would seem to be much closer to Udmurts than to Tajiks:

https://i.ibb.co/Zz4jzv3/1.png

[Arūnas]

^^ smart people, not so close to Balkaners

[Komintasavalta]

Here's ADMIXTURE runs at different K values from 2 to 8 combined to a single CSV table:


,K2:1,K2:2,K3:1,K3:2,K3:3,K4:1,K4:2,K4:3,K4:4,K5:1 ,K5:2,K5:3,K5:4,K5:5,K6:1,K6:2,K6:3,K6:4,K6:5,K6:6 ,K7:1,K7:2,K7:3,K7:4,K7:5,K7:6,K7:7,K8:1,K8:2,K8:3 ,K8:4,K8:5,K8:6,K8:7,K8:8
Bashkir,.6401,.3599,.0488,.4390,.5122,.5841,.0734, .1472,.1954,.1943,.0283,.0354,.2346,.5074,.0100,.1 517,.4935,.0002,.2841,.0606,.0438,.1353,.0131,.499 5,.0000,.2430,.0653,.4913,.1408,.0045,.0025,.0000, .0690,.0137,.2782
Chuvash,.3790,.6210,.0300,.6876,.2824,.1878,.1544, .5677,.0901,.4542,.0805,.0000,.4653,.0000,.0095,.2 575,.0027,.0000,.6655,.0648,.0416,.3317,.0261,.000 0,.0000,.5622,.0384,.0000,.3581,.0000,.0039,.0000, .0232,.0152,.5995
English,.0000,1.0000,.6649,.3351,.0000,.0000,.0000 ,.1518,.8482,.0003,.0000,.0000,.9997,.0000,.0000,. 0000,.0000,.0000,.1824,.8175,.7617,.0000,.0000,.00 00,.0000,.2383,.0000,.0000,.0000,.7611,.0000,.0000 ,.0000,.1489,.0900
Estonian,.0006,.9994,.1837,.8163,.0000,.0000,.0000 ,.7518,.2481,.0016,.6336,.0000,.3648,.0000,.0000,. 0000,.0000,.0552,.6706,.2742,.0772,.0000,.0000,.00 00,.0040,.9188,.0000,.0000,.0000,.0000,.0000,.0000 ,.0000,.3044,.6955
Finnish,.0557,.9443,.1032,.8905,.0063,.0000,.0037, .8857,.1106,.0347,.8051,.0000,.1602,.0000,.0037,.0 000,.0000,.0000,.8741,.1221,.0353,.0090,.0076,.000 0,.0000,.9466,.0015,.0000,.0000,.0796,.0000,.0000, .0000,.9004,.0200
Hungarian,.0031,.9969,.6018,.3970,.0013,.0000,.002 8,.2661,.7311,.0154,.0810,.0020,.9008,.0007,.0010, .0026,.0026,.0132,.2536,.7269,.6468,.0013,.0012,.0 000,.0074,.3403,.0030,.0000,.0023,.5007,.0005,.003 1,.0025,.0142,.4768
Icelandic,.0000,1.0000,.5764,.4236,.0000,.0000,.00 00,.2471,.7529,.0034,.0210,.0000,.9756,.0000,.0000 ,.0000,.0004,.0000,.2712,.7284,.6502,.0000,.0000,. 0000,.0000,.3497,.0000,.0000,.0000,.6929,.0000,.00 00,.0000,.2890,.0181
Italian_North,.0000,1.0000,.9836,.0164,.0000,.0000 ,.0000,.0000,1.0000,.0000,.0000,.0013,.9987,.0000, .0000,.0000,.0005,.0000,.0000,.9994,.9999,.0000,.0 000,.0000,.0000,.0000,.0000,.0000,.0000,.9999,.000 0,.0000,.0000,.0000,.0000
Karakalpak,.9853,.0147,.1451,.0028,.8521,.4000,.57 74,.0068,.0158,.0247,.0000,.4593,.0084,.5075,.0526 ,.4272,.5055,.0000,.0000,.0147,.0046,.0016,.0000,. 4531,.0000,.0098,.5310,.4519,.0021,.0028,.0000,.00 00,.5308,.0000,.0124
Karelian,.0717,.9283,.0231,.9706,.0062,.0000,.0008 ,.9731,.0261,.0258,.9406,.0000,.0336,.0000,.0000,. 0000,.0000,.0000,.9685,.0315,.0070,.0143,.0000,.00 00,.0286,.9496,.0004,.0000,.0000,.0026,.0000,.0000 ,.0001,.9419,.0554
Kyrgyz_Tajikistan,1.0000,.0000,.0372,.0010,.9618,. 0000,1.0000,.0000,.0000,.2700,.0000,.7300,.0000,.0 000,.0360,.9305,.0000,.0000,.0000,.0334,.0000,.000 8,.0000,.0000,.0000,.0000,.9991,.0000,.0077,.0000, .0000,.0000,.9923,.0000,.0000
Mansi,.9476,.0524,.0000,.2618,.7382,.9821,.0000,.0 179,.0000,.9894,.0000,.0000,.0105,.0000,.0000,.736 6,.0000,.0000,.2634,.0000,.0000,.9852,.0000,.0000, .0000,.0147,.0000,.0000,.9836,.0000,.0000,.0000,.0 000,.0164,.0000
Nogai_Astrakhan,.9246,.0754,.1843,.0420,.7736,.000 0,.8696,.1304,.0000,.2872,.0380,.6281,.0467,.0000, .0285,.7613,.0000,.0000,.0062,.2041,.0018,.0239,.0 000,.0000,.0000,.1446,.8297,.0000,.0276,.0009,.000 0,.0000,.8185,.1035,.0496
Nogai_Karachay_Cherkessia,.5136,.4864,.5782,.0082, .4137,.0000,.5076,.0095,.4829,.0368,.0000,.4642,.4 989,.0000,.5220,.2227,.0000,.0000,.0134,.2419,.196 5,.0038,.4772,.0000,.0000,.0514,.2711,.0030,.0020, .1673,.4484,.0000,.2784,.0006,.1003
Nogai_Stavropol,.8467,.1533,.2496,.0407,.7097,.003 2,.8054,.1029,.0885,.2441,.0191,.5930,.1438,.0000, .0658,.6837,.0000,.0000,.0124,.2380,.0908,.0286,.0 000,.0000,.0000,.1197,.7609,.0000,.0232,.0433,.000 0,.0000,.7561,.0316,.1457
Norwegian,.0000,1.0000,.6145,.3855,.0000,.0000,.00 00,.2178,.7822,.0028,.0137,.0000,.9834,.0000,.0000 ,.0000,.0000,.0000,.2407,.7593,.6911,.0000,.0000,. 0000,.0000,.3089,.0000,.0000,.0000,.7261,.0000,.00 00,.0000,.2671,.0068
Romanian,.0035,.9965,.8009,.1971,.0020,.0000,.0073 ,.0436,.9490,.0000,.0000,.0081,.9919,.0000,.0121,. 0024,.0024,.0000,.0455,.9376,.8993,.0000,.0124,.00 00,.0000,.0879,.0004,.0000,.0000,.7630,.0141,.0000 ,.0005,.0000,.2224
Russian,.0376,.9624,.2437,.7409,.0154,.0027,.0148, .6963,.2863,.0407,.5611,.0006,.3947,.0030,.0006,.0 137,.0002,.3383,.4043,.2430,.1554,.0206,.0032,.000 8,.2606,.5553,.0042,.0002,.0219,.0200,.0000,.2325, .0028,.0877,.6349
Russian_Archangelsk_Krasnoborsky,.0940,.9060,.1059 ,.8612,.0328,.0027,.0256,.8458,.1259,.1015,.6275,. 0003,.2706,.0000,.0158,.0140,.0000,.0000,.8237,.14 66,.0047,.0570,.0188,.0000,.0000,.9195,.0000,.0000 ,.0563,.0041,.0051,.0000,.0000,.4566,.4779
Russian_Archangelsk_Leshukonsky,.1824,.8176,.0000, .9036,.0964,.0818,.0150,.9032,.0000,.1648,.8351,.0 000,.0000,.0000,.0000,.0775,.0019,.1607,.7599,.000 0,.0000,.1657,.0000,.0018,.2348,.5977,.0000,.0000, .1316,.0000,.0000,.1284,.0000,.7399,.0000
Russian_Archangelsk_Pinezhsky,.1285,.8715,.0000,.9 514,.0486,.0373,.0082,.9546,.0000,.0700,.9147,.000 0,.0000,.0153,.0000,.0334,.0000,.4395,.5271,.0000, .0000,.0794,.0000,.0000,.5062,.4144,.0000,.0000,.0 517,.0000,.0000,.3697,.0000,.5785,.0000
Saami.DG,.3487,.6513,.0000,.7651,.2349,.2281,.0495 ,.7223,.0000,.3649,.6102,.0000,.0248,.0000,.0000,. 2068,.0000,.0000,.7931,.0000,.0000,.3078,.0000,.00 00,.0000,.6845,.0076,.0000,.2705,.0000,.0000,.0000 ,.0000,.7295,.0000
Tajik,.4302,.5698,.6671,.0000,.3329,.0000,.4241,.0 000,.5759,.0014,.0000,.4279,.5707,.0000,.9190,.013 0,.0000,.0000,.0502,.0178,.0066,.0083,.9612,.0000, .0000,.0152,.0086,.0000,.0071,.0079,.9509,.0000,.0 108,.0092,.0141
Tatar_Kazan,.3590,.6410,.2100,.5129,.2771,.1291,.2 032,.4178,.2498,.3386,.0752,.0709,.5153,.0000,.019 0,.2623,.0007,.0000,.4676,.2504,.1762,.2153,.0396, .0000,.0000,.4448,.1242,.0000,.1962,.0088,.0083,.0 000,.1457,.0154,.6256
Tatar_Mishar,.2480,.7520,.2902,.5211,.1887,.0189,. 2074,.4961,.2776,.2280,.2002,.0544,.5099,.0075,.00 71,.1613,.0392,.0205,.4520,.3198,.1651,.0658,.0000 ,.0000,.0802,.5356,.1533,.0000,.0794,.0322,.0000,. 0804,.1416,.0114,.6549
Tatar_Siberian,.8382,.1618,.0367,.2760,.6873,.3484 ,.4726,.1487,.0303,.5442,.0106,.3222,.1230,.0000,. 0048,.6785,.0000,.0000,.2422,.0744,.0367,.3834,.00 08,.0000,.0000,.1421,.4371,.0000,.3839,.0271,.0009 ,.0000,.4300,.0281,.1300
Tatar_Siberian_Zabolotniye,.9497,.0503,.0000,.2500 ,.7500,1.0000,.0000,.0000,.0000,1.0000,.0000,.0000 ,.0000,.0000,.0000,.7493,.0000,.0000,.2506,.0000,. 0000,.9999,.0000,.0000,.0000,.0000,.0000,.0000,.99 99,.0000,.0000,.0000,.0000,.0000,.0000
Turkmen,.6721,.3279,.4581,.0000,.5419,.0000,.6500, .0085,.3415,.0706,.0000,.5798,.3496,.0000,.5483,.3 441,.0000,.0000,.0047,.1029,.0948,.0106,.4354,.000 0,.0000,.0218,.4374,.0000,.0095,.0812,.4334,.0000, .4306,.0042,.0411
Udmurt,.4808,.5192,.0000,.6447,.3553,.4946,.0000,. 4197,.0857,.6007,.0000,.0000,.3993,.0000,.0000,.32 39,.0000,.0000,.6761,.0000,.0088,.5270,.0056,.0000 ,.0000,.4586,.0000,.0000,.5298,.0000,.0000,.0000,. 0000,.0000,.4701
Uyghur,.9340,.0660,.2192,.0000,.7808,.0000,.9088,. 0082,.0830,.1677,.0007,.7443,.0873,.0000,.3276,.64 83,.0000,.0000,.0005,.0236,.0273,.0012,.1425,.0000 ,.0000,.0163,.8127,.0000,.0024,.0318,.1306,.0000,. 8097,.0103,.0152
Uzbek,.7304,.2696,.3950,.0034,.6016,.0000,.7125,.0 235,.2640,.0902,.0215,.6004,.2635,.0245,.5339,.383 0,.0000,.0000,.0160,.0670,.0491,.0066,.3681,.0145, .0000,.0627,.4989,.0135,.0067,.0210,.3495,.0122,.4 920,.0190,.0862

If you use the CSV table to calculate Euclidean distances between populations, Udmurts are still closer to many Central Asians than to the English:

.000 Udmurt
.556 Chuvash
.895 Tatar_Kazan
1.209 Tatar_Mishar
1.323 Saami.DG
1.401 Tatar_Siberian
1.411 Bashkir
1.598 Russian_Archangelsk_Krasnoborsky
1.616 Russian
1.616 Mansi
1.657 Tatar_Siberian_Zabolotniye
1.701 Estonian
1.736 Russian_Archangelsk_Leshukonsky
1.974 Russian_Archangelsk_Pinezhsky
2.002 Finnish
2.080 Hungarian
2.095 Nogai_Karachay_Cherkessia
2.122 Karelian
2.158 Uzbek
2.166 Turkmen
2.207 Nogai_Stavropol
2.220 Icelandic
2.288 Norwegian
2.308 Karakalpak
2.347 Nogai_Astrakhan
2.384 English
2.473 Uyghur
2.525 Tajik
2.604 Romanian
2.710 Kyrgyz_Tajikistan
2.909 Italian_North

In a K=2 ADMIXTURE run, Udmurts have a balanced mix of the two admixture components:

0 100 English
0 100 Estonian
0 100 Hungarian
0 100 Icelandic
0 100 Italian_North
0 100 Norwegian
0 100 Romanian
4 96 Russian
6 94 Finnish
7 93 Karelian
9 91 Russian_Archangelsk_Krasnoborsky
13 87 Russian_Archangelsk_Pinezhsky
18 82 Russian_Archangelsk_Leshukonsky
25 75 Tatar_Mishar
35 65 Saami.DG
36 64 Tatar_Kazan
38 62 Chuvash
43 57 Tajik
48 52 Udmurt
51 49 Nogai_Karachay_Cherkessia
64 36 Bashkir
67 33 Turkmen
73 27 Uzbek
84 16 Tatar_Siberian
85 15 Nogai_Stavropol
92 8 Nogai_Astrakhan
93 7 Uyghur
95 5 Mansi
95 5 Tatar_Siberian_Zabolotniye
99 1 Karakalpak
100 0 Kyrgyz_Tajikistan

In the K=3 run, it's interesting how some Bashkirs only have the Karelian and Kyrgyz components, but Tatars have a fairly high proportion of the Italian component:

https://i.ibb.co/ryFPw6Y/3.png

In the K=4 run, Karakalpaks have a fairly large proportion of the Mansi component, which brings them closer to Udmurts. The proportion of the Mansi component is over 50% both in some Udmurt samples and some Karakalpak samples.

https://i.ibb.co/KyfK9Rq/4.png

[Zanzibar]

I used ADMIXTOOLS 2 to calculate FST distances between populations in the 1240K+HO dataset:

https://i.ibb.co/3Fb1dKF/a.png

Saami are closer to Uzbeks than to Hungarians. And they are closer to Stavropol Nogais than to Romanians. The population labeled Saami.DG consists of two individuals from a region of Finland that is part of the Northern Saami area.

Arkhangelsk Russians from Leshukonsky are also closer to Tajiks than to North Italians.

On surprising thing is that Chuvashes are closer to Tajiks than to Udmurts, but Udmurts are a drifted population that is far from everyone.

Estonians are closer to Kazan Tatars than to Icelandics, but maybe it's because Tatars are a mixed population that also has a low number of shared IBD segments with other populations: "Together, the low number of shared IBDs within the same population and the high values for relative relatedness from multiple DHGR components (Supplementary Table S4) indicate the populations with the strongest admixtures where millions of people from remote populations mixed with each other for hundreds of years. In Europe, such admixed populations include the Moldavians, Greeks, Italians, Hungarians, and Tatars, among others." (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7696950/)


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

pop=unlist(strsplit("Bashkir
Chuvash
English
Estonian
Finnish
Hungarian
Icelandic
Italian_North
Karakalpak
Karelian
Kyrgyz_Tajikistan
Mansi
Nogai_Astrakhan
Nogai_Karachay_Cherkessia
Nogai_Stavropol
Norwegian
Romanian
Russian
Russian_Archangelsk_Krasnoborsky
Russian_Archangelsk_Leshukonsky
Russian_Archangelsk_Pinezhsky
Saami.DG
Tajik
Tatar_Kazan
Tatar_Mishar
Tatar_Siberian
Tatar_Siberian_Zabolotniye
Turkmen
Udmurt
Uyghur
Uzbek","\n"))

f=fst("path/to/v44.3_HO_public",pop)

df=as.data.frame(f[,-4])
df2=rbind(df,setNames(df[,c(2,1,3)],names(df)))
t=xtabs(df2[,3]~df2[,1]+df2[,2])

pheatmap::pheatmap(
1000*t,
filename="a.png",
clustering_callback=function(...)reorder(hclust(as .dist(t)),t["Italian_North",]),
# clustering_callback=function(...)hclust(dist(t)),
legend=F,
border_color=NA,
cellwidth=18,
cellheight=18,
treeheight_row=80,
treeheight_col=80,
display_numbers=T,
number_format="%.0f",
number_color="black",
colorRampPalette(hex(HSV(c(210,210,130,60,40,20,0) ,c(0,.5,.5,.5,.5,.5,.5),1)))(256)
)

Based on the first two dimensions in a SmartPCA run, Chuvashes would seem to be much closer to Udmurts than to Tajiks:

https://i.ibb.co/Zz4jzv3/1.png

Very interesting. It seems that the Udmurts and Chuvashes are closer to Siberian Tatars, Uzbeks, Turkmens, most Nogais, Tajiks than to Euros. Meanwhile Saamis are closer to Siberian Tatars, Nogai_Karachay_Cherkessia, Uzbeks than to English, Norwegians and Hungarians.

Where are the Russian samples from? They seem to have some East Asian ancestry based on how closer they are to the Finno-Ugrics than other Euros.

Also can you run the same distance models for the Mari, the most Mongoloid Saami samples which are Saami:GS000035025 and Saami:saami2, and the most Mongoloid-shifted Udmurts which are Udmurt:udmurd8 and Udmurt:153_R02C01? I want to see whether they will be even more distant from Euros than other members of their ethnic group.

[Komintasavalta]

Where are the Russian samples from? They seem to have some East Asian ancestry based on how closer they are to the Finno-Ugrics than other Euros.

Out of the Russian samples that don't include Archangelsk in the population name, 24 samples have the locality field in the anno file set as Vologda Oblast (which is a North Russian region south of Arkhangelsk Oblast with a Finno-Permic substrate):

$ wget https://reichdata.hms.harvard.edu/pub/datasets/amh_repo/curated_releases/V44/V44.3/SHARE/public.dir/v44.3_HO_public.anno
$ cut -f 2,8,9,11,12 v44.3_HO_public.anno|grep Russian|grep -v Ignore|grep -v SDG|tr \\t \;
Rakr-203;Russian_Archangelsk_Krasnoborsky;Arkhangelsk region, Krasnoborsky district;61.56;45.94
Rakr-205;Russian_Archangelsk_Krasnoborsky;Arkhangelsk region, Krasnoborsky district;61.56;45.94
Rakr-237;Russian_Archangelsk_Krasnoborsky;Arkhangelsk region, Krasnoborsky district;61.56;45.94
Rakr-248;Russian_Archangelsk_Krasnoborsky;Arkhangelsk region, Krasnoborsky district;61.56;45.94
Rakr-341;Russian_Archangelsk_Krasnoborsky;Arkhangelsk region, Krasnoborsky district;61.56;45.94
Rakr-345;Russian_Archangelsk_Krasnoborsky;Arkhangelsk region, Krasnoborsky district;61.56;45.94
Rakrlsh-002;Russian_Archangelsk_Leshukonsky;Arkhangelsk region, Leshukonsky district;64.9;45.74
Rakrlsh-140;Russian_Archangelsk_Leshukonsky;Arkhangelsk region, Leshukonsky district;64.9;45.74
Rakrlsh-143;Russian_Archangelsk_Leshukonsky;Arkhangelsk region, Leshukonsky district;64.9;45.74
Rakrlsh-144;Russian_Archangelsk_Leshukonsky;Arkhangelsk region, Leshukonsky district;64.9;45.74
Rakrlsh-149;Russian_Archangelsk_Leshukonsky;Arkhangelsk region, Leshukonsky district;64.9;45.74
Rbgp-200;Russian;Belgorod region, Krasnensky, Prohorovsky, Yakovlevsky districts;50.78;36.48
Rbgp-201;Russian;Belgorod region, Krasnensky, Prohorovsky, Yakovlevsky districts;50.78;36.48
Rbgp-203;Russian;Belgorod region, Krasnensky, Prohorovsky, Yakovlevsky districts;50.78;36.48
Rbgp-205;Russian;Belgorod region, Krasnensky, Prohorovsky, Yakovlevsky districts;50.78;36.48
Rkbo-12;Russian;Kaluga region, Baryatinsky, Borovsky districts;54.31;34.53
Rkbo-16;Russian;Kaluga region, Baryatinsky, Borovsky districts;54.31;34.53
Rkbo-44;Russian;Kaluga region, Baryatinsky, Borovsky districts;54.31;34.53
Rkbo-58;Russian;Kaluga region, Baryatinsky, Borovsky districts;54.31;34.53
Rksh-402;Russian;Tver region, Kashin district;57.36;37.61
Rksh-405;Russian;Tver region, Kashin district;57.36;37.61
Rksh-407;Russian;Tver region, Kashin district;57.36;37.61
Rksh-412;Russian;Tver region, Kashin district;57.36;37.61
Rkuch-03;Russian;Kursk region, Pristensky and Cheremisinovsky districts;51.89;37.25
Rkuch-05;Russian;Kursk region, Pristensky and Cheremisinovsky districts;51.89;37.25
Rkuch-53;Russian;Kursk region, Pristensky and Cheremisinovsky districts;51.89;37.25
Rkuch-58;Russian;Kursk region, Pristensky and Cheremisinovsky districts;51.89;37.25
Rorl-102;Russian;Orel region, Livnensky and Bolhovsky districts;53.45;36
Rorl-110;Russian;Orel region, Livnensky and Bolhovsky districts;53.45;36
Rorl-114;Russian;Orel region, Livnensky and Bolhovsky districts;53.45;36
Rorl-155;Russian;Orel region, Livnensky and Bolhovsky districts;53.45;36
RPin-114;Russian_Archangelsk_Pinezhsky;Arkhangelsk region, Pinezhsky district;64;44.26
RPin-123;Russian_Archangelsk_Pinezhsky;Arkhangelsk region, Pinezhsky district;64;44.26
RPin-143;Russian_Archangelsk_Pinezhsky;Arkhangelsk region, Pinezhsky district;64;44.26
RPin-145;Russian_Archangelsk_Pinezhsky;Arkhangelsk region, Pinezhsky district;64;44.26
RPin-151;Russian_Archangelsk_Pinezhsky;Arkhangelsk region, Pinezhsky district;64;44.26
Rps-002;Russian;Pskov region, Ostrov district;57.35;28.32
Rps-004;Russian;Pskov region, Ostrov district;57.35;28.32
Rps-006;Russian;Pskov region, Ostrov district;57.35;28.32
Rps-012;Russian;Pskov region, Ostrov district;57.35;28.32
Rps-090;Russian;Pskov region, Porkhov district;57.77;29.56
Rps-091;Russian;Pskov region, Porkhov district;57.77;29.56
Rps-098;Russian;Pskov region, Porkhov district;57.77;29.56
Rrzm-08;Russian;Ryazan region, Mihailovsky district;54.23;39.03
Rrzm-10;Russian;Ryazan region, Mihailovsky district;54.23;39.03
Rrzm-13;Russian;Ryazan region, Mihailovsky district;54.23;39.03
Rrzm-16;Russian;Ryazan region, Mihailovsky district;54.23;39.03
Rrzm-83;Russian;Ryazan region, Mihailovsky district;54.23;39.03
Rrzs-3;Russian;Ryazan region, Spassky district;54.4;40.53
Rrzs-7;Russian;Ryazan region, Spassky district;54.4;40.53
Rrzs-11;Russian;Ryazan region, Spassky district;54.4;40.53
Rrzs-32;Russian;Ryazan region, Spassky district;54.4;40.53
Rrzs-58;Russian;Ryazan region, Spassky district;54.4;40.53
Rrzs-66;Russian;Ryazan region, Spassky district;54.4;40.53
Rrzs-88;Russian;Ryazan region, Spassky district;54.4;40.53
Rsm-103;Russian;Smolensk region, Roslavl and Ershichi districts;53.95;32.87
Rsm-109;Russian;Smolensk region, Roslavl and Ershichi districts;53.95;32.87
Rsm-166;Russian;Smolensk region, Roslavl and Ershichi districts;53.95;32.87
Rsm-171;Russian;Smolensk region, Roslavl and Ershichi districts;53.95;32.87
Rsm-176;Russian;Smolensk region, Roslavl and Ershichi districts;53.95;32.87
Rsm-179;Russian;Smolensk region, Roslavl and Ershichi districts;53.95;32.87
Rsm-181;Russian;Smolensk region, Roslavl and Ershichi districts;53.95;32.87
RYAR-173;Russian;Yaroslavl region;58.03;38.5
RYAR-223;Russian;Yaroslavl region;58.03;38.5
RYAR-232;Russian;Yaroslavl region;58.03;38.5
HGDP00879;Russian;Vologda Administrative Region;61;40
HGDP00880;Russian;Vologda Administrative Region;61;40
HGDP00882;Russian;Vologda Administrative Region;61;40
HGDP00883;Russian;Vologda Administrative Region;61;40
HGDP00884;Russian;Vologda Administrative Region;61;40
HGDP00887;Russian;Vologda Administrative Region;61;40
HGDP00888;Russian;Vologda Administrative Region;61;40
HGDP00889;Russian;Vologda Administrative Region;61;40
HGDP00890;Russian;Vologda Administrative Region;61;40
HGDP00891;Russian;Vologda Administrative Region;61;40
HGDP00892;Russian;Vologda Administrative Region;61;40
HGDP00893;Russian;Vologda Administrative Region;61;40
HGDP00894;Russian;Vologda Administrative Region;61;40
HGDP00895;Russian;Vologda Administrative Region;61;40
HGDP00896;Russian;Vologda Administrative Region;61;40
HGDP00897;Russian;Vologda Administrative Region;61;40
HGDP00898;Russian;Vologda Administrative Region;61;40
HGDP00899;Russian;Vologda Administrative Region;61;40
HGDP00900;Russian;Vologda Administrative Region;61;40
HGDP00901;Russian;Vologda Administrative Region;61;40
HGDP00902;Russian;Vologda Administrative Region;61;40
HGDP00903;Russian;Vologda Administrative Region;61;40
S_Russian-2.DG;Russian.DG;Vologda Administrative Region;61;40
S_Russian-1.DG;Russian.DG;Vologda Administrative Region;61;40


Also can you run the same distance models for the Mari, the most Mongoloid Saami samples which are Saami:GS000035025 and Saami:saami2, and the most Mongoloid-shifted Udmurts which are Udmurt:udmurd8 and Udmurt:153_R02C01? I want to see whether they will be even more distant from Euros than other members of their ethnic group.

Identifiers like "udmurd8" are made up by Davidski and I don't know what genetic samples they refer to. "Udmurd" is Polish for Udmurt.

The sample GS0000350 is part of the 2016 EGDP release. Its files are split into one bed+bim+fam file for each chromosome, and I don't know how to merge the files. (It wouldn't take long to figure it out, but I already decided that I'm going to stop learning about genetics software.)

[Zanzibar]

Out of the Russian samples that don't include Archangelsk in the population name, 24 samples have the locality field in the anno file set as Vologda Oblast (which is a North Russian region south of Arkhangelsk Oblast with a Finno-Permic substrate):

$ wget https://reichdata.hms.harvard.edu/pub/datasets/amh_repo/curated_releases/V44/V44.3/SHARE/public.dir/v44.3_HO_public.anno
$ cut -f 2,8,9,11,12 v44.3_HO_public.anno|grep Russian|grep -v Ignore|grep -v SDG|tr \\t \;
Rakr-203;Russian_Archangelsk_Krasnoborsky;Arkhangelsk region, Krasnoborsky district;61.56;45.94
Rakr-205;Russian_Archangelsk_Krasnoborsky;Arkhangelsk region, Krasnoborsky district;61.56;45.94
Rakr-237;Russian_Archangelsk_Krasnoborsky;Arkhangelsk region, Krasnoborsky district;61.56;45.94
Rakr-248;Russian_Archangelsk_Krasnoborsky;Arkhangelsk region, Krasnoborsky district;61.56;45.94
Rakr-341;Russian_Archangelsk_Krasnoborsky;Arkhangelsk region, Krasnoborsky district;61.56;45.94
Rakr-345;Russian_Archangelsk_Krasnoborsky;Arkhangelsk region, Krasnoborsky district;61.56;45.94
Rakrlsh-002;Russian_Archangelsk_Leshukonsky;Arkhangelsk region, Leshukonsky district;64.9;45.74
Rakrlsh-140;Russian_Archangelsk_Leshukonsky;Arkhangelsk region, Leshukonsky district;64.9;45.74
Rakrlsh-143;Russian_Archangelsk_Leshukonsky;Arkhangelsk region, Leshukonsky district;64.9;45.74
Rakrlsh-144;Russian_Archangelsk_Leshukonsky;Arkhangelsk region, Leshukonsky district;64.9;45.74
Rakrlsh-149;Russian_Archangelsk_Leshukonsky;Arkhangelsk region, Leshukonsky district;64.9;45.74
Rbgp-200;Russian;Belgorod region, Krasnensky, Prohorovsky, Yakovlevsky districts;50.78;36.48
Rbgp-201;Russian;Belgorod region, Krasnensky, Prohorovsky, Yakovlevsky districts;50.78;36.48
Rbgp-203;Russian;Belgorod region, Krasnensky, Prohorovsky, Yakovlevsky districts;50.78;36.48
Rbgp-205;Russian;Belgorod region, Krasnensky, Prohorovsky, Yakovlevsky districts;50.78;36.48
Rkbo-12;Russian;Kaluga region, Baryatinsky, Borovsky districts;54.31;34.53
Rkbo-16;Russian;Kaluga region, Baryatinsky, Borovsky districts;54.31;34.53
Rkbo-44;Russian;Kaluga region, Baryatinsky, Borovsky districts;54.31;34.53
Rkbo-58;Russian;Kaluga region, Baryatinsky, Borovsky districts;54.31;34.53
Rksh-402;Russian;Tver region, Kashin district;57.36;37.61
Rksh-405;Russian;Tver region, Kashin district;57.36;37.61
Rksh-407;Russian;Tver region, Kashin district;57.36;37.61
Rksh-412;Russian;Tver region, Kashin district;57.36;37.61
Rkuch-03;Russian;Kursk region, Pristensky and Cheremisinovsky districts;51.89;37.25
Rkuch-05;Russian;Kursk region, Pristensky and Cheremisinovsky districts;51.89;37.25
Rkuch-53;Russian;Kursk region, Pristensky and Cheremisinovsky districts;51.89;37.25
Rkuch-58;Russian;Kursk region, Pristensky and Cheremisinovsky districts;51.89;37.25
Rorl-102;Russian;Orel region, Livnensky and Bolhovsky districts;53.45;36
Rorl-110;Russian;Orel region, Livnensky and Bolhovsky districts;53.45;36
Rorl-114;Russian;Orel region, Livnensky and Bolhovsky districts;53.45;36
Rorl-155;Russian;Orel region, Livnensky and Bolhovsky districts;53.45;36
RPin-114;Russian_Archangelsk_Pinezhsky;Arkhangelsk region, Pinezhsky district;64;44.26
RPin-123;Russian_Archangelsk_Pinezhsky;Arkhangelsk region, Pinezhsky district;64;44.26
RPin-143;Russian_Archangelsk_Pinezhsky;Arkhangelsk region, Pinezhsky district;64;44.26
RPin-145;Russian_Archangelsk_Pinezhsky;Arkhangelsk region, Pinezhsky district;64;44.26
RPin-151;Russian_Archangelsk_Pinezhsky;Arkhangelsk region, Pinezhsky district;64;44.26
Rps-002;Russian;Pskov region, Ostrov district;57.35;28.32
Rps-004;Russian;Pskov region, Ostrov district;57.35;28.32
Rps-006;Russian;Pskov region, Ostrov district;57.35;28.32
Rps-012;Russian;Pskov region, Ostrov district;57.35;28.32
Rps-090;Russian;Pskov region, Porkhov district;57.77;29.56
Rps-091;Russian;Pskov region, Porkhov district;57.77;29.56
Rps-098;Russian;Pskov region, Porkhov district;57.77;29.56
Rrzm-08;Russian;Ryazan region, Mihailovsky district;54.23;39.03
Rrzm-10;Russian;Ryazan region, Mihailovsky district;54.23;39.03
Rrzm-13;Russian;Ryazan region, Mihailovsky district;54.23;39.03
Rrzm-16;Russian;Ryazan region, Mihailovsky district;54.23;39.03
Rrzm-83;Russian;Ryazan region, Mihailovsky district;54.23;39.03
Rrzs-3;Russian;Ryazan region, Spassky district;54.4;40.53
Rrzs-7;Russian;Ryazan region, Spassky district;54.4;40.53
Rrzs-11;Russian;Ryazan region, Spassky district;54.4;40.53
Rrzs-32;Russian;Ryazan region, Spassky district;54.4;40.53
Rrzs-58;Russian;Ryazan region, Spassky district;54.4;40.53
Rrzs-66;Russian;Ryazan region, Spassky district;54.4;40.53
Rrzs-88;Russian;Ryazan region, Spassky district;54.4;40.53
Rsm-103;Russian;Smolensk region, Roslavl and Ershichi districts;53.95;32.87
Rsm-109;Russian;Smolensk region, Roslavl and Ershichi districts;53.95;32.87
Rsm-166;Russian;Smolensk region, Roslavl and Ershichi districts;53.95;32.87
Rsm-171;Russian;Smolensk region, Roslavl and Ershichi districts;53.95;32.87
Rsm-176;Russian;Smolensk region, Roslavl and Ershichi districts;53.95;32.87
Rsm-179;Russian;Smolensk region, Roslavl and Ershichi districts;53.95;32.87
Rsm-181;Russian;Smolensk region, Roslavl and Ershichi districts;53.95;32.87
RYAR-173;Russian;Yaroslavl region;58.03;38.5
RYAR-223;Russian;Yaroslavl region;58.03;38.5
RYAR-232;Russian;Yaroslavl region;58.03;38.5
HGDP00879;Russian;Vologda Administrative Region;61;40
HGDP00880;Russian;Vologda Administrative Region;61;40
HGDP00882;Russian;Vologda Administrative Region;61;40
HGDP00883;Russian;Vologda Administrative Region;61;40
HGDP00884;Russian;Vologda Administrative Region;61;40
HGDP00887;Russian;Vologda Administrative Region;61;40
HGDP00888;Russian;Vologda Administrative Region;61;40
HGDP00889;Russian;Vologda Administrative Region;61;40
HGDP00890;Russian;Vologda Administrative Region;61;40
HGDP00891;Russian;Vologda Administrative Region;61;40
HGDP00892;Russian;Vologda Administrative Region;61;40
HGDP00893;Russian;Vologda Administrative Region;61;40
HGDP00894;Russian;Vologda Administrative Region;61;40
HGDP00895;Russian;Vologda Administrative Region;61;40
HGDP00896;Russian;Vologda Administrative Region;61;40
HGDP00897;Russian;Vologda Administrative Region;61;40
HGDP00898;Russian;Vologda Administrative Region;61;40
HGDP00899;Russian;Vologda Administrative Region;61;40
HGDP00900;Russian;Vologda Administrative Region;61;40
HGDP00901;Russian;Vologda Administrative Region;61;40
HGDP00902;Russian;Vologda Administrative Region;61;40
HGDP00903;Russian;Vologda Administrative Region;61;40
S_Russian-2.DG;Russian.DG;Vologda Administrative Region;61;40
S_Russian-1.DG;Russian.DG;Vologda Administrative Region;61;40



Identifiers like "udmurd8" are made up by Davidski and I don't know what genetic samples they refer to. "Udmurd" is Polish for Udmurt.

The sample GS0000350 is part of the 2016 EGDP release. Its files are split into one bed+bim+fam file for each chromosome, and I don't know how to merge the files. (It wouldn't take long to figure it out, but I already decided that I'm going to stop learning about genetics software.)

I C. So looks like many of the Russian samples already have minor Mongoloid, or they could have Finnic ancestry pulling them closer to the Uralics compared to other Euros. Smolensk doesn't seem to have any East Asian though. Not sure about Ryazan, Orel and Kursk.

Ok. Can you try running the Mari? Im surprised, I thought Poles never heard of these Finnic tribes.

Here are the genetic samples. Can you try running them again?


Udmurt:udmurd8,0.106994,-0.040621,0.079572,0.059755,-0.0397,0.007251,0.00846,0.008769,-0.007772,-0.032438,0.024521,-0.008393,0.012785,-0.034543,-0.00855,-0.006629,-0.009127,-0.002154,-0.014204,-0.012756,0.003743,0.006925,0.000493,0.011086,-0.006347
Udmurt:153_R02C01,0.108132,-0.033512,0.083344,0.063631,-0.048932,0.006693,0.012926,0.015692,-0.009408,-0.040274,0.025008,-0.005695,0.021853,-0.048718,-0.015065,-0.008088,-0.011343,-0.003421,-0.009427,-0.016383,0.006738,0.002844,-0.007765,0.017231,-0.00012

Saami:GS000035025,0.103579,-0.04773,0.121433,0.083657,-0.018773,0.007251,0.005405,0.011307,0.00225,-0.033896,0.028093,-0.008243,0.021853,-0.017065,-0.008143,-0.008353,-0.015646,0.00114,-0.002137,-5e-04,0.019341,-0.003462,-0.006655,-0.001325,0.001557
Saami:saami2,0.108132,-0.052808,0.11653,0.078489,-0.022466,0.005578,0.005875,0.008307,0.006545,-0.03262,0.020948,-0.006294,0.017542,-0.020506,-0.001357,-0.008618,-0.014212,-0.00076,-0.003142,0.008879,0.015722,0.006554,-0.000246,-0.002048,0.00012

[Zanzibar]

Here's ADMIXTURE runs at different K values from 2 to 8 combined to a single CSV table:


,K2:1,K2:2,K3:1,K3:2,K3:3,K4:1,K4:2,K4:3,K4:4,K5:1 ,K5:2,K5:3,K5:4,K5:5,K6:1,K6:2,K6:3,K6:4,K6:5,K6:6 ,K7:1,K7:2,K7:3,K7:4,K7:5,K7:6,K7:7,K8:1,K8:2,K8:3 ,K8:4,K8:5,K8:6,K8:7,K8:8
Bashkir,.6401,.3599,.0488,.4390,.5122,.5841,.0734, .1472,.1954,.1943,.0283,.0354,.2346,.5074,.0100,.1 517,.4935,.0002,.2841,.0606,.0438,.1353,.0131,.499 5,.0000,.2430,.0653,.4913,.1408,.0045,.0025,.0000, .0690,.0137,.2782
Chuvash,.3790,.6210,.0300,.6876,.2824,.1878,.1544, .5677,.0901,.4542,.0805,.0000,.4653,.0000,.0095,.2 575,.0027,.0000,.6655,.0648,.0416,.3317,.0261,.000 0,.0000,.5622,.0384,.0000,.3581,.0000,.0039,.0000, .0232,.0152,.5995
English,.0000,1.0000,.6649,.3351,.0000,.0000,.0000 ,.1518,.8482,.0003,.0000,.0000,.9997,.0000,.0000,. 0000,.0000,.0000,.1824,.8175,.7617,.0000,.0000,.00 00,.0000,.2383,.0000,.0000,.0000,.7611,.0000,.0000 ,.0000,.1489,.0900
Estonian,.0006,.9994,.1837,.8163,.0000,.0000,.0000 ,.7518,.2481,.0016,.6336,.0000,.3648,.0000,.0000,. 0000,.0000,.0552,.6706,.2742,.0772,.0000,.0000,.00 00,.0040,.9188,.0000,.0000,.0000,.0000,.0000,.0000 ,.0000,.3044,.6955
Finnish,.0557,.9443,.1032,.8905,.0063,.0000,.0037, .8857,.1106,.0347,.8051,.0000,.1602,.0000,.0037,.0 000,.0000,.0000,.8741,.1221,.0353,.0090,.0076,.000 0,.0000,.9466,.0015,.0000,.0000,.0796,.0000,.0000, .0000,.9004,.0200
Hungarian,.0031,.9969,.6018,.3970,.0013,.0000,.002 8,.2661,.7311,.0154,.0810,.0020,.9008,.0007,.0010, .0026,.0026,.0132,.2536,.7269,.6468,.0013,.0012,.0 000,.0074,.3403,.0030,.0000,.0023,.5007,.0005,.003 1,.0025,.0142,.4768
Icelandic,.0000,1.0000,.5764,.4236,.0000,.0000,.00 00,.2471,.7529,.0034,.0210,.0000,.9756,.0000,.0000 ,.0000,.0004,.0000,.2712,.7284,.6502,.0000,.0000,. 0000,.0000,.3497,.0000,.0000,.0000,.6929,.0000,.00 00,.0000,.2890,.0181
Italian_North,.0000,1.0000,.9836,.0164,.0000,.0000 ,.0000,.0000,1.0000,.0000,.0000,.0013,.9987,.0000, .0000,.0000,.0005,.0000,.0000,.9994,.9999,.0000,.0 000,.0000,.0000,.0000,.0000,.0000,.0000,.9999,.000 0,.0000,.0000,.0000,.0000
Karakalpak,.9853,.0147,.1451,.0028,.8521,.4000,.57 74,.0068,.0158,.0247,.0000,.4593,.0084,.5075,.0526 ,.4272,.5055,.0000,.0000,.0147,.0046,.0016,.0000,. 4531,.0000,.0098,.5310,.4519,.0021,.0028,.0000,.00 00,.5308,.0000,.0124
Karelian,.0717,.9283,.0231,.9706,.0062,.0000,.0008 ,.9731,.0261,.0258,.9406,.0000,.0336,.0000,.0000,. 0000,.0000,.0000,.9685,.0315,.0070,.0143,.0000,.00 00,.0286,.9496,.0004,.0000,.0000,.0026,.0000,.0000 ,.0001,.9419,.0554
Kyrgyz_Tajikistan,1.0000,.0000,.0372,.0010,.9618,. 0000,1.0000,.0000,.0000,.2700,.0000,.7300,.0000,.0 000,.0360,.9305,.0000,.0000,.0000,.0334,.0000,.000 8,.0000,.0000,.0000,.0000,.9991,.0000,.0077,.0000, .0000,.0000,.9923,.0000,.0000
Mansi,.9476,.0524,.0000,.2618,.7382,.9821,.0000,.0 179,.0000,.9894,.0000,.0000,.0105,.0000,.0000,.736 6,.0000,.0000,.2634,.0000,.0000,.9852,.0000,.0000, .0000,.0147,.0000,.0000,.9836,.0000,.0000,.0000,.0 000,.0164,.0000
Nogai_Astrakhan,.9246,.0754,.1843,.0420,.7736,.000 0,.8696,.1304,.0000,.2872,.0380,.6281,.0467,.0000, .0285,.7613,.0000,.0000,.0062,.2041,.0018,.0239,.0 000,.0000,.0000,.1446,.8297,.0000,.0276,.0009,.000 0,.0000,.8185,.1035,.0496
Nogai_Karachay_Cherkessia,.5136,.4864,.5782,.0082, .4137,.0000,.5076,.0095,.4829,.0368,.0000,.4642,.4 989,.0000,.5220,.2227,.0000,.0000,.0134,.2419,.196 5,.0038,.4772,.0000,.0000,.0514,.2711,.0030,.0020, .1673,.4484,.0000,.2784,.0006,.1003
Nogai_Stavropol,.8467,.1533,.2496,.0407,.7097,.003 2,.8054,.1029,.0885,.2441,.0191,.5930,.1438,.0000, .0658,.6837,.0000,.0000,.0124,.2380,.0908,.0286,.0 000,.0000,.0000,.1197,.7609,.0000,.0232,.0433,.000 0,.0000,.7561,.0316,.1457
Norwegian,.0000,1.0000,.6145,.3855,.0000,.0000,.00 00,.2178,.7822,.0028,.0137,.0000,.9834,.0000,.0000 ,.0000,.0000,.0000,.2407,.7593,.6911,.0000,.0000,. 0000,.0000,.3089,.0000,.0000,.0000,.7261,.0000,.00 00,.0000,.2671,.0068
Romanian,.0035,.9965,.8009,.1971,.0020,.0000,.0073 ,.0436,.9490,.0000,.0000,.0081,.9919,.0000,.0121,. 0024,.0024,.0000,.0455,.9376,.8993,.0000,.0124,.00 00,.0000,.0879,.0004,.0000,.0000,.7630,.0141,.0000 ,.0005,.0000,.2224
Russian,.0376,.9624,.2437,.7409,.0154,.0027,.0148, .6963,.2863,.0407,.5611,.0006,.3947,.0030,.0006,.0 137,.0002,.3383,.4043,.2430,.1554,.0206,.0032,.000 8,.2606,.5553,.0042,.0002,.0219,.0200,.0000,.2325, .0028,.0877,.6349
Russian_Archangelsk_Krasnoborsky,.0940,.9060,.1059 ,.8612,.0328,.0027,.0256,.8458,.1259,.1015,.6275,. 0003,.2706,.0000,.0158,.0140,.0000,.0000,.8237,.14 66,.0047,.0570,.0188,.0000,.0000,.9195,.0000,.0000 ,.0563,.0041,.0051,.0000,.0000,.4566,.4779
Russian_Archangelsk_Leshukonsky,.1824,.8176,.0000, .9036,.0964,.0818,.0150,.9032,.0000,.1648,.8351,.0 000,.0000,.0000,.0000,.0775,.0019,.1607,.7599,.000 0,.0000,.1657,.0000,.0018,.2348,.5977,.0000,.0000, .1316,.0000,.0000,.1284,.0000,.7399,.0000
Russian_Archangelsk_Pinezhsky,.1285,.8715,.0000,.9 514,.0486,.0373,.0082,.9546,.0000,.0700,.9147,.000 0,.0000,.0153,.0000,.0334,.0000,.4395,.5271,.0000, .0000,.0794,.0000,.0000,.5062,.4144,.0000,.0000,.0 517,.0000,.0000,.3697,.0000,.5785,.0000
Saami.DG,.3487,.6513,.0000,.7651,.2349,.2281,.0495 ,.7223,.0000,.3649,.6102,.0000,.0248,.0000,.0000,. 2068,.0000,.0000,.7931,.0000,.0000,.3078,.0000,.00 00,.0000,.6845,.0076,.0000,.2705,.0000,.0000,.0000 ,.0000,.7295,.0000
Tajik,.4302,.5698,.6671,.0000,.3329,.0000,.4241,.0 000,.5759,.0014,.0000,.4279,.5707,.0000,.9190,.013 0,.0000,.0000,.0502,.0178,.0066,.0083,.9612,.0000, .0000,.0152,.0086,.0000,.0071,.0079,.9509,.0000,.0 108,.0092,.0141
Tatar_Kazan,.3590,.6410,.2100,.5129,.2771,.1291,.2 032,.4178,.2498,.3386,.0752,.0709,.5153,.0000,.019 0,.2623,.0007,.0000,.4676,.2504,.1762,.2153,.0396, .0000,.0000,.4448,.1242,.0000,.1962,.0088,.0083,.0 000,.1457,.0154,.6256
Tatar_Mishar,.2480,.7520,.2902,.5211,.1887,.0189,. 2074,.4961,.2776,.2280,.2002,.0544,.5099,.0075,.00 71,.1613,.0392,.0205,.4520,.3198,.1651,.0658,.0000 ,.0000,.0802,.5356,.1533,.0000,.0794,.0322,.0000,. 0804,.1416,.0114,.6549
Tatar_Siberian,.8382,.1618,.0367,.2760,.6873,.3484 ,.4726,.1487,.0303,.5442,.0106,.3222,.1230,.0000,. 0048,.6785,.0000,.0000,.2422,.0744,.0367,.3834,.00 08,.0000,.0000,.1421,.4371,.0000,.3839,.0271,.0009 ,.0000,.4300,.0281,.1300
Tatar_Siberian_Zabolotniye,.9497,.0503,.0000,.2500 ,.7500,1.0000,.0000,.0000,.0000,1.0000,.0000,.0000 ,.0000,.0000,.0000,.7493,.0000,.0000,.2506,.0000,. 0000,.9999,.0000,.0000,.0000,.0000,.0000,.0000,.99 99,.0000,.0000,.0000,.0000,.0000,.0000
Turkmen,.6721,.3279,.4581,.0000,.5419,.0000,.6500, .0085,.3415,.0706,.0000,.5798,.3496,.0000,.5483,.3 441,.0000,.0000,.0047,.1029,.0948,.0106,.4354,.000 0,.0000,.0218,.4374,.0000,.0095,.0812,.4334,.0000, .4306,.0042,.0411
Udmurt,.4808,.5192,.0000,.6447,.3553,.4946,.0000,. 4197,.0857,.6007,.0000,.0000,.3993,.0000,.0000,.32 39,.0000,.0000,.6761,.0000,.0088,.5270,.0056,.0000 ,.0000,.4586,.0000,.0000,.5298,.0000,.0000,.0000,. 0000,.0000,.4701
Uyghur,.9340,.0660,.2192,.0000,.7808,.0000,.9088,. 0082,.0830,.1677,.0007,.7443,.0873,.0000,.3276,.64 83,.0000,.0000,.0005,.0236,.0273,.0012,.1425,.0000 ,.0000,.0163,.8127,.0000,.0024,.0318,.1306,.0000,. 8097,.0103,.0152
Uzbek,.7304,.2696,.3950,.0034,.6016,.0000,.7125,.0 235,.2640,.0902,.0215,.6004,.2635,.0245,.5339,.383 0,.0000,.0000,.0160,.0670,.0491,.0066,.3681,.0145, .0000,.0627,.4989,.0135,.0067,.0210,.3495,.0122,.4 920,.0190,.0862

If you use the CSV table to calculate Euclidean distances between populations, Udmurts are still closer to many Central Asians than to the English:

.000 Udmurt
.556 Chuvash
.895 Tatar_Kazan
1.209 Tatar_Mishar
1.323 Saami.DG
1.401 Tatar_Siberian
1.411 Bashkir
1.598 Russian_Archangelsk_Krasnoborsky
1.616 Russian
1.616 Mansi
1.657 Tatar_Siberian_Zabolotniye
1.701 Estonian
1.736 Russian_Archangelsk_Leshukonsky
1.974 Russian_Archangelsk_Pinezhsky
2.002 Finnish
2.080 Hungarian
2.095 Nogai_Karachay_Cherkessia
2.122 Karelian
2.158 Uzbek
2.166 Turkmen
2.207 Nogai_Stavropol
2.220 Icelandic
2.288 Norwegian
2.308 Karakalpak
2.347 Nogai_Astrakhan
2.384 English
2.473 Uyghur
2.525 Tajik
2.604 Romanian
2.710 Kyrgyz_Tajikistan
2.909 Italian_North

In a K=2 ADMIXTURE run, Udmurts have a balanced mix of the two admixture components:

0 100 English
0 100 Estonian
0 100 Hungarian
0 100 Icelandic
0 100 Italian_North
0 100 Norwegian
0 100 Romanian
4 96 Russian
6 94 Finnish
7 93 Karelian
9 91 Russian_Archangelsk_Krasnoborsky
13 87 Russian_Archangelsk_Pinezhsky
18 82 Russian_Archangelsk_Leshukonsky
25 75 Tatar_Mishar
35 65 Saami.DG
36 64 Tatar_Kazan
38 62 Chuvash
43 57 Tajik
48 52 Udmurt
51 49 Nogai_Karachay_Cherkessia
64 36 Bashkir
67 33 Turkmen
73 27 Uzbek
84 16 Tatar_Siberian
85 15 Nogai_Stavropol
92 8 Nogai_Astrakhan
93 7 Uyghur
95 5 Mansi
95 5 Tatar_Siberian_Zabolotniye
99 1 Karakalpak
100 0 Kyrgyz_Tajikistan

In the K=3 run, it's interesting how some Bashkirs only have the Karelian and Kyrgyz components, but Tatars have a fairly high proportion of the Italian component:

https://i.ibb.co/ryFPw6Y/3.png

In the K=4 run, Karakalpaks have a fairly large proportion of the Mansi component, which brings them closer to Udmurts. The proportion of the Mansi component is over 50% both in some Udmurt samples and some Karakalpak samples.

https://i.ibb.co/KyfK9Rq/4.png

Interesting how Hungarians are closer to the Udmurts than Icelandic, Norwegians and English are. Probably due to very minor East Asian admixture (derived from Turkics and ancient Magyars) in the Hungarian samples. Also strange how Estonians are slighty closer to Udmurts than Finns are when it should be the opposite.

Udmurts are still closer to Mansi, Turkics such as Uzbek, Turkmen, Nogais from Stavropol and Karachay_Cherkessia than to Icelanders, Norwegians, English and Romanians, which shows that they are hapas than part of Euros.

[NSXD60]

Mongs are a race that seem to vary less than others, yellowish and swarthy being their main distinction, so nothing new here.

[vbnetkhio]

On surprising thing is that Chuvashes are closer to Tajiks than to Udmurts, but Udmurts are a drifted population that is far from everyone.


maybe it's caused by different SNP counts or .SG vs non-SG sets?

[Komintasavalta]

maybe it's caused by different SNP counts or .SG vs non-SG sets?

No, I excluded .SG samples. And they're modern samples with few missing SNPs.

The list below shows a normalized number of shared IBD fragments of populations with themselves from Table S1 of Khvorykh et al. 2020 (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7696950/). Udmurts and Saami have a high number of shared IBD segments with themselves, so they also had high FST distances to other populations in my heatmap.

$ curl -Ls pastebin.com/raw/CnCPEmff|tr -d \\r>khvorykh-2020-table-s1-normalized-number-of-shared-ibd-fragments
$ curl -Ls pastebin.com/raw/KRTyxqhP|tr -d \\r>khvorykh-2020-table-s1-average-length-of-shared-ibd-fragments
$ head -n-3 khvorykh-2020-table-s1-normalized-number-of-shared-ibd-fragments|sed 1,3d|awk -F, '{print$(NR+3),$2,$3,$1}'|grep 'EUR\|CAS'|sort -rn|awk '$1!=0'
186.11 Saa_EUR Saami:Finland 5se
141.03 Rom_EUR Roma_Bosnia-Herzegovina 3e
112.14 Bas_EUR Basque:France 2s
99.14 Udm_EUR Udmurds 4e
97.57 FIN_EUR Finnish_in_Finland 99
85.66 Mar_EUR Maris_Russia 4e
60.35 Vep_EUR Vepsas_Russia 6ev
58.51 Chu_EUR Chuvashes_Russia 3e
57.32 Kar_EUR Karelians 4ev
56.27 Fin_EUR Finnish:Finland 6se
54.35 Ish_CAS Ishkasim_Tajikistan 2e
52.21 Ice_EUR Icelandic:Iceland 2s
51.92 Ing_EUR Ingrians_Russia_North 3e
49.39 Sar_EUR Sardinian:Italy 3s
48.39 Rus_CAS Rushan-Vanch_Tajikistan 2e
47.75 Alb_EUR Albanian:Albania 4se
42.71 Swe_EUR Swedes_Sweden 2e
40.14 Lat_EUR Latvians 3e
38.79 TKm_CAS Turkmens_Uzbekistan 3e
38.79 Lit_EUR Lithuanians 3e
36.85 Est_EUR Estonian:Estonia 8se
36.84 GBR_EUR British_in_England_and_Scotland 88
35.08 CEU_EUR Utah_(CEPH)_NW_Eur_Ancestry 91
34.53 Alt_CAS Altaian 8sev
32.98 Mor_EUR Mordvins_Russia 3e
32.44 Kom_EUR Komis_Russia 6ev
28.88 BSh_EUR Bashkirs_Russia 5e
28.18 Cro_EUR Croats_Bosnia-Herzegovina 4e
25.97 Taj_CAS Tajiks 3se
24.39 Pol_EUR Polish:Poland 5se
24.24 Bel_EUR Belarusians 4e
23.68 Spa_EUR Spanish:Spain 2s
23.39 Rus_EUR Russian:Russia 15sev
22.77 Orc_EUR Orcadian:OrkneyIslands 4s
22.14 Ukr_EUR Ukrainians 7e
20.55 Fre_EUR French:France 3s
20.13 Bul_EUR Bulgarian:Bulgaria 2s
19.54 IBS_EUR Iberian_Population_in_Spain 107
19.24 Cos_EUR Cossacks_Ukraine 4e
18.37 Kyr_CAS Kyrgyz:Kyrgyzystan 9se
18.18 Kaz_CAS Kazakhs_Kazakhstan 3e
17.76 Ber_EUR Bergamo:Italy 2s
17.69 Tat_EUR Tatars 3e
17.44 Cre_EUR Crete:Greece 2s
17.22 Tus_EUR Tuscan:Italy 2s
16.37 TSI_EUR Toscani_Italia 106
14.97 Ger_EUR Germans 3e
14.19 Hun_EUR Hungarian:Hungary 4se
14.15 Kry_EUR Kryashen-Tatars_Russia 3e
12.65 Gre_EUR Greek:Greece 2s
11.86 Mol_EUR Moldavians 2e
11.12 Uzb_CAS Uzbek 3e
10.84 Uyg_CAS Uygurs_Kazakhstan 3se


Also strange how Estonians are slighty closer to Udmurts than Finns are when it should be the opposite.

Finns are more drifted than Estonians. On the list above, there are two Finnish populations, but both of them have much higher IBD with themselves than Estonians have.


Ok. Can you try running the Mari?

I'm restricting myself to samples in the 1240K+HO dataset (https://reich.hms.harvard.edu/allen-ancient-dna-resource-aadr-downloadable-genotypes-present-day-and-ancient-dna-data) so it will be easier for others to replicate what I'm doing. And it only contains Mari samples with an ".SG" suffix, and the ".SG" samples sometimes give weird results.


Im surprised, I thought Poles never heard of these Finnic tribes.

In Uralistics, the term Finnic is considered to be synonymous with the term Baltic Finnic. A term that can be used to refer to all extant non-Ugric Finno-Ugric peoples is Finno-Permic.

[vbnetkhio]

No, I excluded .SG samples. And they're modern samples with few missing SNPs.

it's probably the isolation of Udmurts then. for example, in my FST analysis, Albanians and Montengirns were far away from each other, and from all other pops.

[Zanzibar]

No, I excluded .SG samples. And they're modern samples with few missing SNPs.

The list below shows a normalized number of shared IBD fragments of populations with themselves from Table S1 of Khvorykh et al. 2020 (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7696950/). Udmurts and Saami have a high number of shared IBD segments with themselves, so they also had high FST distances to other populations in my heatmap.

$ curl -Ls pastebin.com/raw/CnCPEmff|tr -d \\r>khvorykh-2020-table-s1-normalized-number-of-shared-ibd-fragments
$ curl -Ls pastebin.com/raw/KRTyxqhP|tr -d \\r>khvorykh-2020-table-s1-average-length-of-shared-ibd-fragments
$ head -n-3 khvorykh-2020-table-s1-normalized-number-of-shared-ibd-fragments|sed 1,3d|awk -F, '{print$(NR+3),$2,$3,$1}'|grep 'EUR\|CAS'|sort -rn|awk '$1!=0'
186.11 Saa_EUR Saami:Finland 5se
141.03 Rom_EUR Roma_Bosnia-Herzegovina 3e
112.14 Bas_EUR Basque:France 2s
99.14 Udm_EUR Udmurds 4e
97.57 FIN_EUR Finnish_in_Finland 99
85.66 Mar_EUR Maris_Russia 4e
60.35 Vep_EUR Vepsas_Russia 6ev
58.51 Chu_EUR Chuvashes_Russia 3e
57.32 Kar_EUR Karelians 4ev
56.27 Fin_EUR Finnish:Finland 6se
54.35 Ish_CAS Ishkasim_Tajikistan 2e
52.21 Ice_EUR Icelandic:Iceland 2s
51.92 Ing_EUR Ingrians_Russia_North 3e
49.39 Sar_EUR Sardinian:Italy 3s
48.39 Rus_CAS Rushan-Vanch_Tajikistan 2e
47.75 Alb_EUR Albanian:Albania 4se
42.71 Swe_EUR Swedes_Sweden 2e
40.14 Lat_EUR Latvians 3e
38.79 TKm_CAS Turkmens_Uzbekistan 3e
38.79 Lit_EUR Lithuanians 3e
36.85 Est_EUR Estonian:Estonia 8se
36.84 GBR_EUR British_in_England_and_Scotland 88
35.08 CEU_EUR Utah_(CEPH)_NW_Eur_Ancestry 91
34.53 Alt_CAS Altaian 8sev
32.98 Mor_EUR Mordvins_Russia 3e
32.44 Kom_EUR Komis_Russia 6ev
28.88 BSh_EUR Bashkirs_Russia 5e
28.18 Cro_EUR Croats_Bosnia-Herzegovina 4e
25.97 Taj_CAS Tajiks 3se
24.39 Pol_EUR Polish:Poland 5se
24.24 Bel_EUR Belarusians 4e
23.68 Spa_EUR Spanish:Spain 2s
23.39 Rus_EUR Russian:Russia 15sev
22.77 Orc_EUR Orcadian:OrkneyIslands 4s
22.14 Ukr_EUR Ukrainians 7e
20.55 Fre_EUR French:France 3s
20.13 Bul_EUR Bulgarian:Bulgaria 2s
19.54 IBS_EUR Iberian_Population_in_Spain 107
19.24 Cos_EUR Cossacks_Ukraine 4e
18.37 Kyr_CAS Kyrgyz:Kyrgyzystan 9se
18.18 Kaz_CAS Kazakhs_Kazakhstan 3e
17.76 Ber_EUR Bergamo:Italy 2s
17.69 Tat_EUR Tatars 3e
17.44 Cre_EUR Crete:Greece 2s
17.22 Tus_EUR Tuscan:Italy 2s
16.37 TSI_EUR Toscani_Italia 106
14.97 Ger_EUR Germans 3e
14.19 Hun_EUR Hungarian:Hungary 4se
14.15 Kry_EUR Kryashen-Tatars_Russia 3e
12.65 Gre_EUR Greek:Greece 2s
11.86 Mol_EUR Moldavians 2e
11.12 Uzb_CAS Uzbek 3e
10.84 Uyg_CAS Uygurs_Kazakhstan 3se



Finns are more drifted than Estonians. On the list above, there are two Finnish populations, but both of them have much higher IBD with themselves than Estonians have.



I'm restricting myself to samples in the 1240K+HO dataset (https://reich.hms.harvard.edu/allen-ancient-dna-resource-aadr-downloadable-genotypes-present-day-and-ancient-dna-data) so it will be easier for others to replicate what I'm doing. And it only contains Mari samples with an ".SG" suffix, and the ".SG" samples sometimes give weird results.



In Uralistics, the term Finnic is considered to be synonymous with the term Baltic Finnic. A term that can be used to refer to all extant non-Ugric Finno-Ugric peoples is Finno-Permic.

You are not using the G25 data from David but rather from 1240K+HO?

That make sense. Being more drifted, would make them more distant from Udmurts?

I see. But how do Poles know about Udmurts to call them "Udmurd" since Finno-Permic tribes don't exist in Poland?

Btw this is fascinating. It shows Russians from Voronez, Smolensk, Orel, etc. and Belarusians being more genetically closer to churkas than many Finno-Ugrics lol with the exception of Mordovian, Komi, Saami_Kola and Besermyan who seem to be much less Mongoloid and more Euro-shifted than other Finnics. Even they are closer to several MENAs than the most Mongoloid-shifted Saami, Udmurt samples and the Mari. Thus, we can be sure that most Euros will be closer to Caucasians and even some MENAs than to many Finno-Ugrics. The only exceptions to the rule are Finns, Estonians, other Balts and Northern Russians probably due to lower EEF and higher Mongoloid/Uralic ancestry.

Distance to: Russian_Voronez

0.04460455 Mordovian
0.10760316 Komi
0.12526392 Saami_Kola
0.12764725 Basque_Spanish
0.13547009 French_Corsica
0.13651067 Spanish_Canarias
0.14415022 Italian_Lazio
0.14681511 Sicilian_West
0.15430786 Kaitag
0.15693969 Besermyan
0.15782142 Italian_Campania
0.15815524 Greek_Crete
0.15848588 Avar
0.15912730 Tabasaran
0.16005881 Darginian
0.16104448 Italian_Calabria
0.16179443 Kubachinian
0.16212036 Kumyk
0.16217060 Turkish_Northwest
0.16241381 Kabardin
0.16619190 Circassian
0.16717840 Balkar
0.16722733 Chuvash
0.16892346 Chechen
0.16927785 Karachay
0.17066881 Turkish_Southwest
0.17096740 Ingushian
0.17265718 Udmurt
0.17518874 Saami
0.17541711 Greek_Dodecanese
0.18047767 North_Ossetian
0.18446296 Moroccan_Jew
0.18676988 Turkish_East
0.19103346 Azeri
0.19136409 Sardinian
0.19235765 Syrian_Jew
0.19365695 Iranian_Zoroastrian
0.19477111 Iranian_Persian
0.19497843 Cypriot
0.19543075 Udmurt:udmurd8
0.19724333 Talysh_Azerbaijan
0.19761805 Saami:GS000035025
0.19770669 Kurdish
0.19818717 Tatar_Crimean_steppe
0.19979515 Udmurt:153_R02C01
0.20084988 Saami:saami2
0.20233191 Syrian_West
0.20361911 Georgian_Laz
0.20845502 Assyrian
0.21101336 Lebanese_Christian_Maronite
0.21182345 Georgian_Imer
0.21988262 Palestinian_Beit_Sahour
0.22059257 Mari
0.22083148 Iraqi_Arab
0.23252310 FIN_Levanluhta_IA:DA238



Distance to: Russian_Smolensk

0.04976528 Mordovian
0.11238237 Komi
0.12924781 Saami_Kola
0.13065384 Basque_Spanish
0.14100291 French_Corsica
0.14139294 Spanish_Canarias
0.15016147 Italian_Lazio
0.15235375 Sicilian_West
0.15864720 Kaitag
0.16220037 Besermyan
0.16303716 Avar
0.16377578 Italian_Campania
0.16418547 Tabasaran
0.16429298 Greek_Crete
0.16459809 Darginian
0.16612740 Kubachinian
0.16715701 Italian_Calabria
0.16756337 Kabardin
0.16777801 Kumyk
0.16895172 Turkish_Northwest
0.17149147 Circassian
0.17250406 Chuvash
0.17257852 Balkar
0.17377404 Chechen
0.17451075 Karachay
0.17594586 Ingushian
0.17779682 Turkish_Southwest
0.17796271 Udmurt
0.17952044 Saami
0.18168273 Greek_Dodecanese
0.18527958 North_Ossetian
0.19009804 Moroccan_Jew
0.19283343 Turkish_East
0.19608048 Sardinian
0.19686795 Azeri
0.19804541 Syrian_Jew
0.19878699 Iranian_Zoroastrian
0.19999831 Iranian_Persian
0.20046634 Udmurt:udmurd8
0.20102965 Cypriot
0.20143800 Saami:GS000035025
0.20275034 Talysh_Azerbaijan
0.20316390 Kurdish
0.20379176 Tatar_Crimean_steppe
0.20458057 Saami:saami2
0.20508979 Udmurt:153_R02C01
0.20861866 Syrian_West
0.20893068 Georgian_Laz
0.21421595 Assyrian
0.21627636 Georgian_Imer
0.21699811 Lebanese_Christian_Maronite
0.22557314 Mari
0.22605905 Palestinian_Beit_Sahour
0.22687786 Iraqi_Arab
0.23719278 FIN_Levanluhta_IA:DA238


Distance to: Ukrainian

0.04759996 Mordovian
0.11107789 Komi
0.12162684 Basque_Spanish
0.12816704 French_Corsica
0.12981733 Saami_Kola
0.12989202 Spanish_Canarias
0.13690875 Italian_Lazio
0.14014558 Sicilian_West
0.15007248 Kaitag
0.15068189 Italian_Campania
0.15138045 Greek_Crete
0.15406687 Italian_Calabria
0.15430214 Avar
0.15446915 Tabasaran
0.15606868 Darginian
0.15757451 Kubachinian
0.15760017 Kumyk
0.15781442 Turkish_Northwest
0.15816763 Kabardin
0.15935893 Besermyan
0.16218235 Circassian
0.16325309 Balkar
0.16422988 Chechen
0.16513558 Karachay
0.16602807 Turkish_Southwest
0.16653777 Ingushian
0.16880609 Greek_Dodecanese
0.17097408 Chuvash
0.17552127 Udmurt
0.17652083 North_Ossetian
0.17762396 Moroccan_Jew
0.17927329 Saami
0.18120890 Turkish_East
0.18478019 Sardinian
0.18590878 Azeri
0.18596401 Syrian_Jew
0.18819131 Iranian_Zoroastrian
0.18861781 Cypriot
0.18954469 Iranian_Persian
0.19164672 Talysh_Azerbaijan
0.19196564 Kurdish
0.19622748 Syrian_West
0.19757256 Tatar_Crimean_steppe
0.19802289 Georgian_Laz
0.19809225 Udmurt:udmurd8
0.20240172 Assyrian
0.20258413 Saami:GS000035025
0.20277212 Udmurt:153_R02C01
0.20482081 Lebanese_Christian_Maronite
0.20524660 Saami:saami2
0.20666322 Georgian_Imer
0.21320522 Palestinian_Beit_Sahour
0.21579824 Iraqi_Arab
0.22486058 Mari
0.23674141 FIN_Levanluhta_IA:DA238



Distance to: Belarusian

0.04940744 Mordovian
0.11245056 Komi
0.12873390 Saami_Kola
0.13305304 Basque_Spanish
0.14398276 Spanish_Canarias
0.14408386 French_Corsica
0.15336219 Italian_Lazio
0.15589179 Sicilian_West
0.16253349 Kaitag
0.16281578 Besermyan
0.16691386 Avar
0.16720830 Italian_Campania
0.16782875 Tabasaran
0.16784285 Greek_Crete
0.16824596 Darginian
0.16988527 Kubachinian
0.17056709 Italian_Calabria
0.17215430 Kumyk
0.17242623 Kabardin
0.17246290 Turkish_Northwest
0.17354646 Chuvash
0.17639895 Circassian
0.17734229 Balkar
0.17820864 Udmurt
0.17837262 Chechen
0.17926072 Saami
0.17932742 Karachay
0.18076870 Ingushian
0.18100616 Turkish_Southwest
0.18518620 Greek_Dodecanese
0.19040213 North_Ossetian
0.19329828 Moroccan_Jew
0.19669238 Turkish_East
0.19834510 Sardinian
0.20052267 Azeri
0.20105008 Udmurt:udmurd8
0.20128495 Saami:GS000035025
0.20178264 Syrian_Jew
0.20190985 Iranian_Zoroastrian
0.20325232 Iranian_Persian
0.20479626 Cypriot
0.20482423 Saami:saami2
0.20540007 Udmurt:153_R02C01
0.20546672 Tatar_Crimean_steppe
0.20628392 Talysh_Azerbaijan
0.20661241 Kurdish
0.21200320 Syrian_West
0.21367556 Georgian_Laz
0.21790185 Assyrian
0.22064817 Lebanese_Christian_Maronite
0.22148968 Georgian_Imer
0.22654627 Mari
0.22931495 Palestinian_Beit_Sahour
0.22987184 Iraqi_Arab
0.23677099 FIN_Levanluhta_IA:DA238


Now compare to Estonians and Finns:

Distance to: Estonian

0.04806155 Mordovian
0.10446297 Komi
0.11586627 Saami_Kola
0.14362282 Basque_Spanish
0.15644797 Besermyan
0.15844823 Spanish_Canarias
0.16154386 French_Corsica
0.16630835 Chuvash
0.16632238 Saami
0.17017327 Udmurt
0.17171667 Italian_Lazio
0.17436450 Kaitag
0.17453626 Sicilian_West
0.17830297 Avar
0.17874494 Darginian
0.17973598 Tabasaran
0.18134296 Kubachinian
0.18528417 Turkish_Northwest
0.18553220 Kumyk
0.18615198 Italian_Campania
0.18627333 Kabardin
0.18740786 Greek_Crete
0.18893651 Saami:GS000035025
0.18964153 Italian_Calabria
0.19013415 Circassian
0.19043516 Balkar
0.19127369 Chechen
0.19280981 Karachay
0.19302237 Saami:saami2
0.19334510 Udmurt:udmurd8
0.19376325 Turkish_Southwest
0.19438987 Ingushian
0.19705576 Udmurt:153_R02C01
0.20401790 North_Ossetian
0.20474828 Greek_Dodecanese
0.20632956 Tatar_Crimean_steppe
0.21102903 Moroccan_Jew
0.21338046 Turkish_East
0.21481596 Sardinian
0.21597192 Azeri
0.21737192 Iranian_Zoroastrian
0.21763448 Mari
0.21841752 Iranian_Persian
0.22042934 Syrian_Jew
0.22227948 Talysh_Azerbaijan
0.22302298 Kurdish
0.22394715 Cypriot
0.22465757 FIN_Levanluhta_IA:DA238
0.22986160 Syrian_West
0.23182964 Georgian_Laz
0.23604487 Assyrian
0.23872121 Georgian_Imer
0.23952705 Lebanese_Christian_Maronite
0.24581920 Iraqi_Arab
0.24749069 Palestinian_Beit_Sahour


Distance to: Finnish

0.03738447 Mordovian
0.07749844 Komi
0.08928522 Saami_Kola
0.12768960 Besermyan
0.13721173 Basque_Spanish
0.13826217 Saami
0.14117864 Chuvash
0.14179315 Udmurt
0.15186334 Spanish_Canarias
0.15734452 French_Corsica
0.16114704 Saami:GS000035025
0.16399254 Saami:saami2
0.16412459 Udmurt:udmurd8
0.16442518 Kaitag
0.16749674 Italian_Lazio
0.16815307 Darginian
0.16829417 Udmurt:153_R02C01
0.16834001 Avar
0.16958096 Turkish_Northwest
0.16971041 Sicilian_West
0.16974312 Tabasaran
0.17188230 Kubachinian
0.17366994 Kumyk
0.17398577 Kabardin
0.17831625 Circassian
0.17851763 Turkish_Southwest
0.17857151 Balkar
0.18057007 Karachay
0.18115750 Chechen
0.18153413 Italian_Campania
0.18226683 Tatar_Crimean_steppe
0.18348462 Greek_Crete
0.18358057 Ingushian
0.18505497 Italian_Calabria
0.19240137 North_Ossetian
0.19255765 Mari
0.19852037 FIN_Levanluhta_IA:DA238
0.19996267 Greek_Dodecanese
0.20435528 Turkish_East
0.20487239 Moroccan_Jew
0.20493534 Azeri
0.20891102 Iranian_Persian
0.20891324 Iranian_Zoroastrian
0.21175799 Sardinian
0.21385992 Talysh_Azerbaijan
0.21449160 Syrian_Jew
0.21537047 Kurdish
0.21884399 Cypriot
0.22348310 Syrian_West
0.22648013 Georgian_Laz
0.22986635 Assyrian
0.23275785 Georgian_Imer
0.23446319 Lebanese_Christian_Maronite
0.23774846 Iraqi_Arab
0.24221988 Palestinian_Beit_Sahour


Distance to: Latvian

0.06113334 Mordovian
0.11824265 Komi
0.12900749 Saami_Kola
0.15678057 Basque_Spanish
0.17054801 Besermyan
0.17084581 Spanish_Canarias
0.17297243 French_Corsica
0.17931411 Saami
0.18028483 Chuvash
0.18204968 Kaitag
0.18235709 Italian_Lazio
0.18369906 Udmurt
0.18520718 Sicilian_West
0.18609000 Avar
0.18652888 Darginian
0.18785135 Tabasaran
0.18851541 Kubachinian
0.19492172 Kumyk
0.19551946 Kabardin
0.19638298 Italian_Campania
0.19675672 Greek_Crete
0.19721167 Turkish_Northwest
0.19892069 Circassian
0.19915707 Balkar
0.19969485 Chechen
0.19978546 Italian_Calabria
0.20114102 Saami:GS000035025
0.20184115 Karachay
0.20294149 Ingushian
0.20555402 Saami:saami2
0.20559627 Turkish_Southwest
0.20715504 Udmurt:udmurd8
0.21086239 Udmurt:153_R02C01
0.21250644 North_Ossetian
0.21404650 Greek_Dodecanese
0.21954164 Tatar_Crimean_steppe
0.22134759 Moroccan_Jew
0.22244866 Turkish_East
0.22523437 Iranian_Zoroastrian
0.22544111 Azeri
0.22550326 Sardinian
0.22678309 Iranian_Persian
0.22975817 Syrian_Jew
0.23035723 Talysh_Azerbaijan
0.23093457 Kurdish
0.23128921 Mari
0.23311140 Cypriot
0.23591365 FIN_Levanluhta_IA:DA238
0.23892574 Georgian_Laz
0.23895641 Syrian_West
0.24409958 Assyrian
0.24547177 Georgian_Imer
0.24825255 Lebanese_Christian_Maronite
0.25496474 Iraqi_Arab
0.25639490 Palestinian_Beit_Sahour


Distance to: Russian_Kostroma

0.01538347 Mordovian
0.06946755 Komi
0.08657729 Saami_Kola
0.12050012 Besermyan
0.13185412 Chuvash
0.13509091 Udmurt
0.13609329 Saami
0.14457330 Basque_Spanish
0.15133949 Spanish_Canarias
0.15459186 Kaitag
0.15466784 French_Corsica
0.15691549 Turkish_Northwest
0.15769654 Avar
0.15802376 Darginian
0.15807654 Udmurt:udmurd8
0.15913559 Tabasaran
0.15928761 Saami:GS000035025
0.16118803 Kabardin
0.16119872 Kumyk
0.16160036 Kubachinian
0.16219836 Italian_Lazio
0.16238275 Saami:saami2
0.16271738 Udmurt:153_R02C01
0.16362190 Sicilian_West
0.16528821 Circassian
0.16562770 Balkar
0.16604465 Turkish_Southwest
0.16779885 Karachay
0.16983559 Chechen
0.17178375 Tatar_Crimean_steppe
0.17212861 Ingushian
0.17444585 Greek_Crete
0.17449152 Italian_Campania
0.17744845 Italian_Calabria
0.18010653 North_Ossetian
0.18522712 Mari
0.19092550 Greek_Dodecanese
0.19273833 Turkish_East
0.19285033 Azeri
0.19438868 FIN_Levanluhta_IA:DA238
0.19727555 Iranian_Persian
0.19771883 Iranian_Zoroastrian
0.19772501 Moroccan_Jew
0.20172538 Talysh_Azerbaijan
0.20368709 Kurdish
0.20538967 Syrian_Jew
0.20948086 Cypriot
0.21111663 Sardinian
0.21319319 Syrian_West
0.21452025 Georgian_Laz
0.21857094 Assyrian
0.22111959 Georgian_Imer
0.22459744 Lebanese_Christian_Maronite
0.22755070 Iraqi_Arab
0.23282571 Palestinian_Beit_Sahour


Russian_Kostroma seems to be Northern Russians who are Slavicized Finnics it seems.

[Komintasavalta]

Btw this is fascinating. It shows Russians from Voronez, Smolensk, Orel, etc. and Belarusians being more genetically closer to churkas than many Finno-Ugrics lol with the exception of Mordovian, Komi, Saami_Kola and Besermyan who seem to be much less Mongoloid and more Euro-shifted than other Finnics. Even they are closer to several MENAs than the most Mongoloid-shifted Saami, Udmurt samples and the Mari. Thus, we can be sure that most Euros will be closer to Caucasians and even some MENAs than to many Finno-Ugrics. The only exceptions to the rule are Finns, Estonians, other Balts and Northern Russians probably due to lower EEF and higher Mongoloid/Uralic ancestry.

The image below shows FST distances between populations in the 1240K+HO dataset. The population I named Russian_Southwest consists of 4 samples from the Kursk region. Russian_Southwest is actually closer to Chuvashes than to most Caucasians included here, but that's probably partially because the Chuvash samples have lower Mongoloid ancestry on average than in G25.

The FST distances are so sensitive to drift that Southwestern Russians are closer to Kazan Tatars than Udmurts are to Besermyans.

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

[Zanzibar]

The image below shows FST distances between populations in the 1240K+HO dataset. The population I named Russian_Southwest consists of 4 samples from the Kursk region. Russian_Southwest is actually closer to Chuvashes than to most Caucasians included here, but that's probably partially because the Chuvash samples have lower Mongoloid ancestry on average than in G25.

The FST distances are so sensitive to drift that Southwestern Russians are closer to Kazan Tatars than Udmurts are to Besermyans.

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

Can you also include the Ugrics and Central Asians? I presume the Udmurts will be closer to Mansis, Khantys, Uzbeks, Turkmens, Nogais, Siberian Tatars, Tubalars/Shors than to Russians.

Chuvashes here having lower Mongoloid ancestry than those in G25 make sense. Or it could be that Chuvashes also have more shared ancestry with Russians/more admixture with them than other Finnics do which could lead to the closer distance.

Intriguing to see how Southwest Russians and Vologda Russians are genetically closer to Caucasian wogs such as Circassian, Balkar, Azeri and even Chechen, Ingush than to Udmurts and to a lesser degree, Besermyans.

[Komintasavalta]

Can you also include the Ugrics and Central Asians? I presume the Udmurts will be closer to Mansis, Khantys, Uzbeks, Turkmens, Nogais, Siberian Tatars, Tubalars/Shors than to Russians.

Shors and Tubalars are also drifted populations, and the Shor and Tubalar samples in 1240K+HO include some related individuals that I did not try to exclude, so Udmurts have a really high FST distance to them:

FST distance to Udmurt:
.0000 Udmurt
.0064 Besermyan
.0096 Tatar_Kazan
.0099 Bashkir
.0120 Chuvash
.0146 Tatar_Mishar
.0148 Nogai_Karachay_Cherkessia
.0150 Tatar_Siberian
.0158 Uzbek
.0160 Russian_Archangelsk_Krasnoborsky
.0168 Tajik
.0174 Nogai_Stavropol
.0179 Russian
.0181 Turkmen
.0187 Russian_Archangelsk_Pinezhsky
.0188 Finnish
.0196 Russian_Archangelsk_Leshukonsky
.0196 Karelian
.0196 Uyghur.DG
.0207 Estonian
.0209 Hungarian
.0217 Uyghur
.0218 Karakalpak
.0221 Nogai_Astrakhan
.0221 Circassian
.0229 English
.0231 Norwegian
.0236 Icelandic
.0237 Romanian
.0242 Mansi
.0247 Azeri
.0261 Iranian
.0264 Italian_North
.0277 Kazakh
.0286 Tatar_Siberian_Zabolotniye
.0288 Canary_Islander
.0300 Kyrgyz_Tajikistan
.0314 Lebanese
.0321 Saami.DG
.0323 Khakass
.0359 Yemeni
.0370 Altaian_Chelkan
.0385 Tubalar
.0391 Altaian
.0398 Shor_Mountain
.0422 Khakass_Kachin
.0428 Saudi
.0434 Moroccan
.0508 Mongol
.0511 Ket
.0513 Shor_Khakassia
.0577 Enets
.0688 Xibo
.0726 Tibetan
.0795 Han


Chuvashes here having lower Mongoloid ancestry than those in G25 make sense. Or it could be that Chuvashes also have more shared ancestry with Russians/more admixture with them than other Finnics do which could lead to the closer distance.

Yeah it could be that Davidski excluded some of the least Mongoloid Chuvash samples from G25 if he thought that they were mixed. 1240K+HO also has a wider range of Mongoloid admixture among Bashkirs than G25, with some Bashkirs neighboring Tatars.


Intriguing to see how Southwest Russians and Vologda Russians are genetically closer to Caucasian wogs such as Circassian, Balkar, Azeri and even Chechen, Ingush than to Udmurts and to a lesser degree, Besermyans.

Yeah but I think a lot of it is because of Udmurt drift, because Russians still have really low FST distance to Kazan Tatars (.00485). The distance between Udmurts and Kazan Tatars is about twice as big (.00954)

[Zanzibar]

Shors and Tubalars are also drifted populations, and the Shor and Tubalar samples in 1240K+HO include some related individuals that I did not try to exclude, so Udmurts have a really high FST distance to them:

FST distance to Udmurt:
.0000 Udmurt
.0064 Besermyan
.0096 Tatar_Kazan
.0099 Bashkir
.0120 Chuvash
.0146 Tatar_Mishar
.0148 Nogai_Karachay_Cherkessia
.0150 Tatar_Siberian
.0158 Uzbek
.0160 Russian_Archangelsk_Krasnoborsky
.0168 Tajik
.0174 Nogai_Stavropol
.0179 Russian
.0181 Turkmen
.0187 Russian_Archangelsk_Pinezhsky
.0188 Finnish
.0196 Russian_Archangelsk_Leshukonsky
.0196 Karelian
.0196 Uyghur.DG
.0207 Estonian
.0209 Hungarian
.0217 Uyghur
.0218 Karakalpak
.0221 Nogai_Astrakhan
.0221 Circassian
.0229 English
.0231 Norwegian
.0236 Icelandic
.0237 Romanian
.0242 Mansi
.0247 Azeri
.0261 Iranian
.0264 Italian_North
.0277 Kazakh
.0286 Tatar_Siberian_Zabolotniye
.0288 Canary_Islander
.0300 Kyrgyz_Tajikistan
.0314 Lebanese
.0321 Saami.DG
.0323 Khakass
.0359 Yemeni
.0370 Altaian_Chelkan
.0385 Tubalar
.0391 Altaian
.0398 Shor_Mountain
.0422 Khakass_Kachin
.0428 Saudi
.0434 Moroccan
.0508 Mongol
.0511 Ket
.0513 Shor_Khakassia
.0577 Enets
.0688 Xibo
.0726 Tibetan
.0795 Han



Yeah it could be that Davidski excluded some of the least Mongoloid Chuvash samples from G25 if he thought that they were mixed. 1240K+HO also has a wider range of Mongoloid admixture among Bashkirs than G25, with some Bashkirs neighboring Tatars.



Yeah but I think a lot of it is because of Udmurt drift, because Russians still have really low FST distance to Kazan Tatars (.00485). The distance between Udmurts and Kazan Tatars is about twice as big (.00954)

Can you show how the Shors and Tubalars are also drifted? Mansi are surprisingly very far from Udmurts, is it also due to drift? Nice to see how Udmurts are genetically closer to Nogais, Uzbeks, Siberian Tatars than they are to Russians. Is the "Russian" sample without any label also from Northern Russia? The three Russian groups from Archangelsk seems to heavily Finnic admixed.

Can you also try to add more Balts and Slavs like Poles, Slovakians, Ukrainians and Serbians into the Udmurt distance run? Want to see whether they are further away from Udmurts than Central Asians are.

Yup he could thought they have recent Russian admixture. Actually some Bashkirs on G25 also resemble Tatars in their Mongoloid ancestry.

Make sense. Or it could be that Kazan Tatars have recent Slavic admixture from Russians causing them to be much closer unlike with Udmurts who seem to lack Russian input. If I remember on G25, many Kazan Tatar show significant Russian-like admixture.

[Komintasavalta]

Can you show how the Shors and Tubalars are also drifted?

They're similar to Saami in the sense that in these FST runs, they have a high FST distance even to their closest neighbors. For example below Tubalars are closest Altaian_Chelkan, with an FST distance of .014. The numbers shown in the heatmap are multiplied by 1000.

https://i.ibb.co/GcXG0z5/a.png


Can you also try to add more Balts and Slavs like Poles, Slovakians, Ukrainians and Serbians into the Udmurt distance run? Want to see whether they are further away from Udmurts than Central Asians are.

I added Ukrainians, Poles, and Croatians in the heatmap above. Udmurts are slightly closer to Circassians than to Croatians. It could be because Circassians are more Mongoloid than Croatians, or because Udmurts have extra CHG or Tajik-like ancestry. Also Udmurts are slightly closer to Iranians than to North Italians. And they are closer to Turkmens than to Ukrainians.


Is the "Russian" sample without any label also from Northern Russia?

It contains the same samples that I showed in post #8. Samples from Northern Russia are overrepresented because there's a lot of samples from Vologda from HGDP. But the average latitude of the samples is still 56.7, which is very close to the latitude of the center of population of Russia (https://en.wikipedia.org/wiki/Center_of_population#Russia).


The three Russian groups from Archangelsk seems to heavily Finnic admixed.

It's not necessarily Finnic (i.e. Baltic Finnic), because some of the Arkhangelsk Russians have higher Mongoloid admixture than any present-day Finnic-speaking population, apart from maybe Finnish-Saami mixes.

Arkhangelsk Oblast has been inhabited by a huge number of different Uralic peoples. There were Bjarmians who were possibly Permian. There's also toponyms attributed to Mansi in Arkhangelsk Oblast (http://www.elisanet.fi/alkupera/Pven.html).

There is a small tundra region in northern Arkhangelsk Oblast, where there are a few settlements with a Nenets majority, and where some people look like Nenets-Russian mestizos (https://www.theapricity.com/forum/showthread.php?309996-Inhabitants-of-Mezensky-District-(northern-Archangelsk-Oblast)). Some Nenetses from the Tundra region of Arkhangelsk Oblast have claimed that their ancestors were Sikhirtya, who are thought to be a Samoyedic people that inhabited Nenetsia before Nenetses (https://avaldsnes.info/en/informasjon/hjor/).

There have also been Izhma Komi reindeer herders in Arkhangelsk Oblast (https://www.researchgate.net/publication/269809402_Izhma_Komis_and_Pomors_Two_Models_of_Cul tural_Transformation_Journal_of_Ethnology_and_Folk loristics_2011_Vol_5_1): "Izhma reindeer herders intentionally increased the size of their herds, and by mid-1830s, the Nenets had already lost their priority in the tundra - an obvious evidence of this is the _Decree on the Administration of Samoyeds Living in the Mezen Region of Arkhangelsk Province_, adopted in 1835. According to this document, all the "foreigners", who pastured their reindeer in the lands possessed by the Samoyeds, had to pay a fee for each grazing reindeer. Researchers have also noted that by the 1840s, the ratio of reindeer herds belonging to the Nenets and Komi was 1:4, respectively, and this situation continued also in the subsequent years (Konakov 2004: 154)."

In case that Bolshoy Oleni Ostrov represented an early Uralic migration to Kola, some lost Uralic population related to BOO could also have lived in Arkhangelsk Oblast.

[Zanzibar]

They're similar to Saami in the sense that in these FST runs, they have a high FST distance even to their closest neighbors. For example below Tubalars are closest Altaian_Chelkan, with an FST distance of .014. The numbers shown in the heatmap are multiplied by 1000.

You are right. Tubalars are definitely drifted if the closest distance to other groups are already 14 while other pops such as Nogai_Stavropol still have the closest FST distances of 1 to Karakalpak or Norwegians still have the closest distance to English at 2.


I added Ukrainians, Poles, and Croatians in the heatmap above. Udmurts are slightly closer to Circassians than to Croatians. It could be because Circassians are more Mongoloid than Croatians, or because Udmurts have extra CHG or Tajik-like ancestry. Also Udmurts are slightly closer to Iranians than to North Italians. And they are closer to Turkmens than to Ukrainians.

Thx. This confirms what I thought. The Circassians do have minor Mongoloid ancestry along with massive loads of CHG and Iranian admixture which makes them closer to Udmurts than Croatians. And yeah, from some runs that I did, Udmurts do indeed have elevated CHG or Central Asian-related ancestry that makes them closer to many Turkics and Tajiks than to Croatians and other Euros. Make sense though as Udmurts shared CHG and Steppe ancestry with Iranians thus making them closer. Udmurts have at least 25% Mongoloid or more along with Iranic-related ancestry which makes them genetically closer to Turkmens than to Ukrainians.


It contains the same samples that I showed in post #8. Samples from Northern Russia are overrepresented because there's a lot of samples from Vologda from HGDP. But the average latitude of the samples is still 56.7, which is very close to the latitude of the center of population of Russia.

Right. The abundance of Northern Russian samples will heavily skewed the Russian average, therefore making them appear to be closer to Udmurts than other Euros.


It's not necessarily Finnic (i.e. Baltic Finnic), because some of the Arkhangelsk Russians have higher Mongoloid admixture than any present-day Finnic-speaking population, apart from maybe Finnish-Saami mixes.

Arkhangelsk Oblast has been inhabited by a huge number of different Uralic peoples. There were Bjarmians who were possibly Permian. There's also toponyms attributed to Mansi in Arkhangelsk Oblast (http://www.elisanet.fi/alkupera/Pven.html).

There is a small tundra region in northern Arkhangelsk Oblast, where there are a few settlements with a Nenets majority, and where some people look like Nenets-Russian mestizos (https://www.theapricity.com/forum/sh...ngelsk-Oblast)). Some Nenetses from the Tundra region of Arkhangelsk Oblast have claimed that their ancestors were Sikhirtya, who are thought to be a Samoyedic people that inhabited Nenetsia before Nenetses (https://avaldsnes.info/en/informasjon/hjor/).

There have also been Izhma Komi reindeer herders in Arkhangelsk Oblast (https://www.researchgate.net/publica...s_2011_Vol_5_1): "Izhma reindeer herders intentionally increased the size of their herds, and by mid-1830s, the Nenets had already lost their priority in the tundra - an obvious evidence of this is the _Decree on the Administration of Samoyeds Living in the Mezen Region of Arkhangelsk Province_, adopted in 1835. According to this document, all the "foreigners", who pastured their reindeer in the lands possessed by the Samoyeds, had to pay a fee for each grazing reindeer. Researchers have also noted that by the 1840s, the ratio of reindeer herds belonging to the Nenets and Komi was 1:4, respectively, and this situation continued also in the subsequent years (Konakov 2004: 154)."

In case that Bolshoy Oleni Ostrov represented an early Uralic migration to Kola, some lost Uralic population related to BOO could also have lived in Arkhangelsk Oblast.


These information are new to me. Thanks. I used to think Northern Russia was mainly populated by Finnics but it seems there are a lot of influences from other Uralics as well.

[Lemminkäinen]

No, I excluded .SG samples. And they're modern samples with few missing SNPs.

The list below shows a normalized number of shared IBD fragments of populations with themselves from Table S1 of Khvorykh et al. 2020 (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7696950/). Udmurts and Saami have a high number of shared IBD segments with themselves, so they also had high FST distances to other populations in my heatmap.

$ curl -Ls pastebin.com/raw/CnCPEmff|tr -d \\r>khvorykh-2020-table-s1-normalized-number-of-shared-ibd-fragments
$ curl -Ls pastebin.com/raw/KRTyxqhP|tr -d \\r>khvorykh-2020-table-s1-average-length-of-shared-ibd-fragments
$ head -n-3 khvorykh-2020-table-s1-normalized-number-of-shared-ibd-fragments|sed 1,3d|awk -F, '{print$(NR+3),$2,$3,$1}'|grep 'EUR\|CAS'|sort -rn|awk '$1!=0'
186.11 Saa_EUR Saami:Finland 5se
141.03 Rom_EUR Roma_Bosnia-Herzegovina 3e
112.14 Bas_EUR Basque:France 2s
99.14 Udm_EUR Udmurds 4e
97.57 FIN_EUR Finnish_in_Finland 99
85.66 Mar_EUR Maris_Russia 4e
60.35 Vep_EUR Vepsas_Russia 6ev
58.51 Chu_EUR Chuvashes_Russia 3e
57.32 Kar_EUR Karelians 4ev
56.27 Fin_EUR Finnish:Finland 6se
54.35 Ish_CAS Ishkasim_Tajikistan 2e
52.21 Ice_EUR Icelandic:Iceland 2s
51.92 Ing_EUR Ingrians_Russia_North 3e
49.39 Sar_EUR Sardinian:Italy 3s
48.39 Rus_CAS Rushan-Vanch_Tajikistan 2e
47.75 Alb_EUR Albanian:Albania 4se
42.71 Swe_EUR Swedes_Sweden 2e
40.14 Lat_EUR Latvians 3e
38.79 TKm_CAS Turkmens_Uzbekistan 3e
38.79 Lit_EUR Lithuanians 3e
36.85 Est_EUR Estonian:Estonia 8se
36.84 GBR_EUR British_in_England_and_Scotland 88
35.08 CEU_EUR Utah_(CEPH)_NW_Eur_Ancestry 91
34.53 Alt_CAS Altaian 8sev
32.98 Mor_EUR Mordvins_Russia 3e
32.44 Kom_EUR Komis_Russia 6ev
28.88 BSh_EUR Bashkirs_Russia 5e
28.18 Cro_EUR Croats_Bosnia-Herzegovina 4e
25.97 Taj_CAS Tajiks 3se
24.39 Pol_EUR Polish:Poland 5se
24.24 Bel_EUR Belarusians 4e
23.68 Spa_EUR Spanish:Spain 2s
23.39 Rus_EUR Russian:Russia 15sev
22.77 Orc_EUR Orcadian:OrkneyIslands 4s
22.14 Ukr_EUR Ukrainians 7e
20.55 Fre_EUR French:France 3s
20.13 Bul_EUR Bulgarian:Bulgaria 2s
19.54 IBS_EUR Iberian_Population_in_Spain 107
19.24 Cos_EUR Cossacks_Ukraine 4e
18.37 Kyr_CAS Kyrgyz:Kyrgyzystan 9se
18.18 Kaz_CAS Kazakhs_Kazakhstan 3e
17.76 Ber_EUR Bergamo:Italy 2s
17.69 Tat_EUR Tatars 3e
17.44 Cre_EUR Crete:Greece 2s
17.22 Tus_EUR Tuscan:Italy 2s
16.37 TSI_EUR Toscani_Italia 106
14.97 Ger_EUR Germans 3e
14.19 Hun_EUR Hungarian:Hungary 4se
14.15 Kry_EUR Kryashen-Tatars_Russia 3e
12.65 Gre_EUR Greek:Greece 2s
11.86 Mol_EUR Moldavians 2e
11.12 Uzb_CAS Uzbek 3e
10.84 Uyg_CAS Uygurs_Kazakhstan 3se



Finns are more drifted than Estonians. On the list above, there are two Finnish populations, but both of them have much higher IBD with themselves than Estonians have.



I'm restricting myself to samples in the 1240K+HO dataset (https://reich.hms.harvard.edu/allen-ancient-dna-resource-aadr-downloadable-genotypes-present-day-and-ancient-dna-data) so it will be easier for others to replicate what I'm doing. And it only contains Mari samples with an ".SG" suffix, and the ".SG" samples sometimes give weird results.



In Uralistics, the term Finnic is considered to be synonymous with the term Baltic Finnic. A term that can be used to refer to all extant non-Ugric Finno-Ugric peoples is Finno-Permic.

We have in Finland ten times more shared segments in the east than in the west. Then if we take any locality from the west we see high IBD sharings resebling the east. Demographically East Finland corresponds a small locality in the west, although the geographic area is large. The get a demographically proper result we should take only 10% of samples from East Finland, but usually people without knowing the history see the east and west equal.

[Komintasavalta]

We have in Finland ten times more shared segments in the east than in the west. Then if we take any locality from the west we see high IBD sharings resebling the east. Demographically East Finland corresponds a small locality in the west, although the geographic area is large. The get a demographically proper result we should take only 10% of samples from East Finland, but usually people without knowing the history see the east and west equal.

I used IBD data from Khvorykh et al. 2020 (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7696950/).

The population labeled "FIN_EUR" ("Finnish_in_Finland") consisted of 99 Finnish samples from 1000 Genomes. I don't know where the samples are from.

The population labeled "Fin_EUR" ("Finnish:Finland") consisted of 3 samples EGDP (Estonian Biocentre) and 3 samples from SGDP (Simons). It had a lower number of shared IBD segments with itself than the samples from 1000 Genomes. The location of the samples from EGDP was set as "approximate_but_born_in_Tallinn", "approximate_but_born_in_Rakvere", and "approximate_probably_born_in_Finland" (https://evolbio.ut.ee/CGgenomes_VCF/Samples.xlsx). The samples from SGDP had the label "S_Finnish" and their latitude and longitude were set as the coordinates of Helsinki (https://simonsfoundation.s3.amazonaws.com/share/SCDA/datasets/10_24_2014_SGDP_metainformation_update.txt).


These information are new to me. Thanks. I used to think Northern Russia was mainly populated by Finnics but it seems there are a lot of influences from other Uralics as well.

In this map by Rahkonen, the area of Arkhangelsk Oblast also overlaps with the area of Para-Saami, Archaic Uralic, and North Meryan (https://journal.fi/susa/article/view/70231/31260):

https://i.ibb.co/9nbTGxC/20191128140816.png

And here it overlaps with the "core area of language X" (language X is Rahkonen's term for a lost Uralic language or languages possibly related to Meryan):

https://i.ibb.co/tw0qwLv/20191128140625.png

[Lemminkäinen]

I used IBD data from Khvorykh et al. 2020 (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7696950/).

The population labeled "FIN_EUR" ("Finnish_in_Finland") consisted of 99 Finnish samples from 1000 Genomes. I don't know where the samples are from.

The population labeled "Fin_EUR" ("Finnish:Finland") consisted of 3 samples EGDP (Estonian Biocentre) and 3 samples from SGDP (Simons). It had a lower number of shared IBD segments with itself than the samples from 1000 Genomes. The location of the samples from EGDP was set as "approximate_but_born_in_Tallinn", "approximate_but_born_in_Rakvere", and "approximate_probably_born_in_Finland" (https://evolbio.ut.ee/CGgenomes_VCF/Samples.xlsx). The samples from SGDP had the label "S_Finnish" and their latitude and longitude were set as the coordinates of Helsinki (https://simonsfoundation.s3.amazonaws.com/share/SCDA/datasets/10_24_2014_SGDP_metainformation_update.txt).



In this map by Rahkonen, the area of Arkhangelsk Oblast also overlaps with the area of Para-Saami, Archaic Uralic, and North Meryan (https://journal.fi/susa/article/view/70231/31260):

https://i.ibb.co/9nbTGxC/20191128140816.png

And here it overlaps with the "core area of language X" (language X is Rahkonen's term for a lost Uralic language or languages possibly related to Meryan):

https://i.ibb.co/tw0qwLv/20191128140625.png

Pity that Finnish researchers don't publish any Finnish data. Only they know the locatilies. I have, but can't publish. You can easily see the trend from Gedmatch's one-to-many comparisons. Simply select your Southwest and East Finnish matches and search their results. Compare their matches. East Finnish shared IBDs and matches are numerous, but still they have not higher ROH profiles, because they are not an isolated group in a sense of being a young mixture of older Finnic groups. Saamis are an old isolated group.

[Zanzibar]

I used IBD data from Khvorykh et al. 2020 (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7696950/).

The population labeled "FIN_EUR" ("Finnish_in_Finland") consisted of 99 Finnish samples from 1000 Genomes. I don't know where the samples are from.

The population labeled "Fin_EUR" ("Finnish:Finland") consisted of 3 samples EGDP (Estonian Biocentre) and 3 samples from SGDP (Simons). It had a lower number of shared IBD segments with itself than the samples from 1000 Genomes. The location of the samples from EGDP was set as "approximate_but_born_in_Tallinn", "approximate_but_born_in_Rakvere", and "approximate_probably_born_in_Finland" (https://evolbio.ut.ee/CGgenomes_VCF/Samples.xlsx). The samples from SGDP had the label "S_Finnish" and their latitude and longitude were set as the coordinates of Helsinki (https://simonsfoundation.s3.amazonaws.com/share/SCDA/datasets/10_24_2014_SGDP_metainformation_update.txt).



In this map by Rahkonen, the area of Arkhangelsk Oblast also overlaps with the area of Para-Saami, Archaic Uralic, and North Meryan (https://journal.fi/susa/article/view/70231/31260):

https://i.ibb.co/9nbTGxC/20191128140816.png

And here it overlaps with the "core area of language X" (language X is Rahkonen's term for a lost Uralic language or languages possibly related to Meryan):

https://i.ibb.co/tw0qwLv/20191128140625.png

Btw, this PuntDNAL K12 distance run seems to confirm the validity of the G25 distance run on many VURers being close to Turkics/Central Asians than to most Euros. Unfortunately, there are no Khanty, Mansi samples in this calc and I cannot find their gedmatch kits, but I'm certain they will be among the top populations of VURers.

Distance to: P.B. (ethnic Mari, his lastname sounds Bashkir-ish though)
19.84765225 Soispaev
20.64161331 Turkmen9_5Afghanistan
22.39830351 Turkmen9_36Afghanistan
23.83563718 Uzbek_usb16
23.85676843 Turkmen9_46Afghanistan
23.90824544 Karakhanid
24.65175856 Uzbek
24.99538357 Turkmen
24.99890398 Uzbek_usb2
24.99890398 Turkmen_Uzbekistan101
25.68285810 Russian
26.96496245 Nogai
27.67626059 Karakalpak_KKA051
28.02165056 Karakalpak_KKA052
29.23985636 Finnish
30.77197101 Karakalpak_KKA048
31.31732109 Uyghur_Hgdp01298
31.48204568 Croatian
31.56404917 Hazara
31.82152102 Hungarian
32.10450436 Tajik_Pomiri
32.27846341 Belarusian
32.35613079 Czech
33.00968343 Dutch_North
33.40747222 Romanian
34.22220332 English_South
34.63263201 Estonian
35.59689874 Lithuanian
37.82511335 Chechen
39.35084751 Greek
40.22398787 Balkar
43.51987132 Sicilian_West
44.30710101 Sicilian_East
44.60794996 North_Ossetian
51.99499207 Cypriot

Distance to: Mari_B (ethnic Mari individual)
19.59667319 Soispaev
22.56622476 Turkmen9_5Afghanistan
24.90538295 Turkmen9_36Afghanistan
26.14560575 Russian
26.74174078 Uzbek_usb16
26.85308735 Turkmen9_46Afghanistan
26.88536591 Karakhanid
27.39011318 Uzbek_usb2
27.39011318 Turkmen_Uzbekistan101
28.01736426 Turkmen
28.31152945 Uzbek
29.12552832 Karakalpak_KKA052
29.12975626 Finnish
29.51636665 Karakalpak_KKA051
29.82503479 Nogai
31.61016767 Croatian
31.83068802 Hungarian
32.15866135 Karakalpak_KKA048
32.25697909 Czech
32.65689361 Belarusian
32.86019933 Dutch_North
33.06119629 Romanian
33.76481453 English_South
34.41079336 Hazara
34.98497820 Uyghur_Hgdp01298
34.99132321 Estonian
35.98586806 Lithuanian
35.99295348 Tajik_Pomiri
39.35000254 Greek
40.58402025 Chechen
42.40875735 Balkar
43.41512064 Sicilian_West
44.39406154 Sicilian_East
47.40646264 North_Ossetian
52.49164410 Cypriot

Distance to: Chuvash/Udmurt (not sure his ethnic group)
22.41824257 Russian
23.05922158 Soispaev
23.65114374 Turkmen9_5Afghanistan
25.28211225 Turkmen9_36Afghanistan
25.61782582 Turkmen9_46Afghanistan
26.03973118 Finnish
26.40563576 Uzbek
26.64905627 Uzbek_usb16
27.53575131 Nogai
28.02316185 Croatian
28.20722602 Turkmen
28.21537879 Hungarian
28.55884451 Czech
28.72834141 Belarusian
28.87880884 Karakhanid
28.97655604 Uzbek_usb2
28.97655604 Turkmen_Uzbekistan101
29.42511852 Dutch_North
29.97828547 Romanian
30.04708971 Tajik_Pomiri
30.65840178 English_South
31.16115531 Estonian
32.09828033 Karakalpak_KKA051
32.15956467 Lithuanian
32.76504387 Karakalpak_KKA052
34.26262687 Uyghur_Hgdp01298
35.44064616 Karakalpak_KKA048
35.53220511 Hazara
36.35158318 Chechen
36.64884173 Greek
39.64829883 Balkar
41.01070104 Sicilian_West
41.98711231 Sicilian_East
44.02894048 North_Ossetian
50.26567019 Cypriot

P.S.- The Turkmen, Uzbek, Karakalpak indivdiual samples are not part of the PuntDNA K12 spreadsheet but gedmatch kits that I add to the run.

[Komintasavalta]

Btw, this PuntDNAL K12 distance run seems to confirm the validity of the G25 distance run on many VURers being close to Turkics/Central Asians than to most Euros. Unfortunately, there are no Khanty, Mansi samples in this calc and I cannot find their gedmatch kits, but I'm certain they will be among the top populations of VURers.

Is there an FST matrix for PuntDNAL K12? Can you somehow access it through Gedmatch?

I tried going here: https://classic.gedmatch.com/ap_pops2.php. I selected "Admixture / Oracle with Population Search", searched for Finnish, and selected "puntDNAL K12 Modern". But then it gives me an error like "User NOT LOGGED IN!".

[Zanzibar]

Is there an FST matrix for PuntDNAL K12? Can you somehow access it through Gedmatch?

I tried going here: https://classic.gedmatch.com/ap_pops2.php. I selected "Admixture / Oracle with Population Search", searched for Finnish, and selected "puntDNAL K12 Modern". But then it gives me an error like "User NOT LOGGED IN!".

I can't find the FST matrix for it. But I believe I can guess the reason why the G25 and PuntDNAL K12 distance runs for VURers are so different from other calcs. The other calcs assume "North European", "Atlantic", "Baltic", "West Med", "East Med", etc. as absolute unadmixed components when they are actually different mixes between EEF/WHG/Steppe (EHG+CHG+ a bit EEF), etc. While in G25, PuntDNA K12, almost no one is pure but a mix of different ancient populations. In many calcs, VURers such as Udmurt, Mari have score very high amounts of "North Europe/Baltic" component. This could make them pull towards North Euros/East Euros and thus make them seem closer to the former than to Turkics/Central Asians. In G25, PuntDNAL K12, no one is pure but a multi mix of different components, in this case the VURers seem to share much more East Asian+Iranic/Central Asian-related ancestry with Turkics/Central Asians than to most Euros, thus makes them genetically closer to Turkics.

Btw can you do a Dodecad K12b script for Maris please similar to what you did for Eurogenes K13?

[Komintasavalta]

In many calcs, VURers such as Udmurt, Mari have score very high amounts of "North Europe/Baltic" component. This could make them pull towards North Euros/East Euros and thus make them seem closer to the former than to Turkics/Central Asians.

Doesn't that include PuntDNAL K12 though? In the CSV table at Lucas's Vahaduo fork (http://vahaduo.genetics.ovh/puntdnal-k12modern-vahaduo.htm), Chuvashes have one of the highest percentages of the European_HG component:

European_HG,Population
58.5,Lithuanian
57.5,Estonian
55.0,Finnish
53.0,Belarusian
52.0,Russian
51.0,Icelandic
50.0,Swedish
48.0,Norwegian
47.5,Mordovian
47.0,Scottish_West
46.0,German_North
46.0,Czech
45.5,Dutch_North
45.5,Chuvash
45.0,Irish
43.5,English_South
42.0,Hungarian
41.5,Utahn_European
40.5,German_South
40.5,Dutch_South

Chuvashes even end up in the same cluster with Finns and Hungarians (if this took FST into account, I think Chuvashes would cluster with Nogais based on their level of Mongoloid admixture):

https://i.ibb.co/4tLk3B5/a.png


Btw can you do a Dodecad K12b script for Maris please similar to what you did for Eurogenes K13?

Here:


t=read.csv("https://pastebin.com/raw/2TdwA3Le",row.names=1,check.names=F) # Dodecad K12b updated
t=t/100

fst=as.matrix(as.dist(read.csv(text="0,,,,,,,,,,,
121,0,,,,,,,,,,
074,144,0,,,,,,,,,
123,072,142,0,,,,,,,,
062,139,056,142,0,,,,,,,
048,123,067,129,041,0,,,,,,
081,101,099,091,098,086,0,,,,,
132,181,097,173,136,140,135,0,,,,
066,146,060,145,052,063,099,124,0,,,
118,052,137,032,137,123,085,170,139,0,,
041,129,052,130,033,041,082,123,047,125,0,
173,218,129,209,185,183,172,051,169,206,171,0",header=F)))
fst=fst/mean(fst)
t=as.matrix(t)%*%fst

d=as.matrix(dist(t))
s=sort(d["Mari",])
cat(paste(sprintf("%.3f",s),names(s)),sep="\n")

I still don't know if this is the right way to account for FST.

Maris ended up being closer to many South Asian populations than to Karelians, and they're closer to Turkmens and Uzbeks than to Komis.

Also Maris are closer to Bashkir_Central than to Bashkir_North, because the combined proportion of the Siberian, East_Asian, and Southeast_Asian components is 30% in Maris, 31% in central Bashkirs, 25% in northern Bashkirs, and 41% in southern Bashkirs. The Maris who live in Bashkortostan mostly live in northern Bashkortostan, so if they mix with the local Bashkirs, maybe it only makes them less Mongoloid.

0.000 Mari
0.070 Bashkir_Central
0.114 Udmurt
0.140 Bashkir_North
0.142 Chuvash
0.162 Crimean_Tatar_Steppe
0.174 Besermyan_Udmurtia
0.206 Lipka_Tatar
0.238 Turkmen_Uzbekistan
0.266 Tatar_Kazan
0.280 Uzbek
0.300 Turkmen_Afghanistan
0.312 Nogai
0.319 Bashkir_South
0.326 Komi
0.328 Turkmen_Iran
0.345 Uzbeki
0.397 Tatar_Mishar
0.401 Turkmen_TM
0.404 Tajik_Mountain
0.420 Tajik_Lowland
0.449 Tatar_Siberia
0.452 Burusho
0.470 Tajik_Kabul
0.483 Pamiri_Ishkashim
0.489 Nepali_Khas_Brahmin
0.492 Brahmin_Uttaranchal
0.505 Kho
0.522 PAK_Kohistani
0.522 Pamiri_Shughnan
0.522 Russian_Ural
0.526 Tajik_Herat
0.530 Kashmiri
0.539 Haryana_Ror
0.543 Veps
0.544 Punjabi_Tarkhan
0.548 Pamiri_Rushan
0.550 Punjabi_Jatt
0.551 West_Bengal_Brahmin
0.552 Nepali_Khas_Kshatriya
0.555 Punjabi_Khatri
0.556 Pashtun_Yusafzai
0.558 Gujarati_Brahmin
0.561 Tatar_Zabolotniye
0.563 Pashtun_Uthmankhel
0.565 Sindhi_Hindu
0.567 Tajik_Panjshir&Kapisa
0.569 Kalash
0.571 Russian_Northern_Dvina
0.572 Finnish_East
0.574 Pashtun_Tarkalani
0.578 Nogai_Stavropol
0.584 Turk_Northwest
0.586 Pashtun_Kandahar
0.586 Nuristani
0.587 Meena
0.589 Cochin_Jews
0.593 Kshatriya
0.595 Karelian
0.599 Turk_Southwest
0.608 Brahmins_from_Tamil_Nadu
0.616 Bnei_Menashe_Jews
0.617 Turk_Central_Black_Sea
0.617 Malayali
0.619 Yaghnobi_Tajikistan
0.620 North_Russian
0.620 Iyer
0.621 Mordovian
0.628 Russian_Kostroma
0.629 Iyengar
0.635 Uyghur
0.635 Balkan_Gypsy
0.635 Turk_South
0.635 Nogai_Astrakhan
0.636 Bangladeshi
0.640 Lambadi
0.642 Karakalpak
0.646 Finnish_West
0.648 Hazara
0.651 Tharus
0.652 Meghawal
0.654 Dharkars
0.657 Kurmi
0.661 Abazin
0.663 Kanjars
0.667 Turk_West_BlackSea
0.668 Crimean_Tatar_Mountain
0.669 Kabardin
0.679 Parsi_India
0.681 Russian
0.683 Turk_Central_West
0.683 Karachay
0.684 Balkar
0.690 Iranian_Khorasan
0.691 Velamas
0.701 Circassian
0.705 Uttar_Pradesh_Scheduled_Caste
0.707 Tamil_Nadu_Scheduled_Caste
0.709 Balochi
0.713 Turk_Trakya
0.715 Turk_Central_East
0.717 Russian_Ryazan
0.718 Dusadh
0.719 Azerbaijani_Iran
0.723 Azerbaijani_Turkey
0.725 Kurumba
0.727 Kumyk
0.728 Turk_Deliorman
0.735 Russian_Tver
0.736 Turk_Southeast
0.741 Estonian
0.741 Kol
0.746 Piramalai_Kallars
0.747 Iranian_Bandari
0.747 Ossetian
0.749 Azerbaijani_Republic
0.762 Ingush
0.764 Azerbaijani_Dagestan
0.765 Chenchus
0.767 Tubalar
0.773 Russian_Kursk
0.776 Iranian_Fars
0.777 Iranian_Kerman
0.778 Adyghe
0.779 Russian_Oryol
0.780 Chamar
0.782 Lak
0.782 Chechen
0.786 Altaian_Chelkan
0.787 Ossetian_South
0.788 Tabasaran
0.789 SAKILLI
0.790 Dargin
0.792 Dargin_Kaitag
0.792 Hungarian_Transylvania+Székely
0.796 Russian_Voronezh
0.798 Lezgin
0.799 Turkmen_Iraq
0.802 Ukrainian
0.802 Russian_Smolensk
0.803 Belarusian_Minsk
0.806 Dargin_Kubachi
0.809 Latvian
0.814 Hakkipikki
0.814 Belorussian
0.815 Lithuanian
0.822 Polish_Mazovia
0.823 Talysh_Azerbaijan
0.823 Polish_Warmia-Masuria
0.823 Ukrainian_Ivano-Frankivsk
0.824 Moldovan_North
0.825 Iranian_Lur
0.826 North_Kannadi
0.827 Hungarian_Alföld
0.828 Hungarian_North
0.829 Turk_Makedonya
0.830 Iranian_Mazandaran
0.830 Moldovan_Central
0.831 Norwegian
0.831 Hungarian
0.834 Slovak
0.835 Polish
0.838 Kurd_Sorani
0.840 Swedish
0.841 Hungarian_Transdanubia+Budapest
0.842 Kurd_Feyli
0.844 Turk_East
0.845 Yazidi_Kurd
0.845 Kurd_Kurmanji
0.845 Sorb_Lusatia
0.849 Icelandic
0.849 Czech
0.850 Shor
0.852 German
0.852 Dutch
0.857 Danish
0.858 Moldovan_South
0.858 Gond
0.859 Kazakh
0.859 Croat
0.861 French_North
0.862 German_Northwest
0.862 Irish
0.862 Moldovan_Gagauz
0.863 Scottish
0.863 Slovenian
0.863 Romanian
0.864 Bosnian
0.865 Serb
0.866 English_North
0.866 Croat_South
0.866 Pomak_Greece
0.866 English_South
0.868 French_Northwest
0.869 Iraqi_Baghdad
0.870 English
0.875 Abkhazian
0.875 Belgian
0.878 Bulgarian_West
0.879 French_Northeast
0.880 Pomak_Bulgaria
0.884 Bavarian_German
0.884 Arab_Iran
0.885 Bulgarian_Central
0.886 Bulgarian_East
0.886 Montenegrin
0.887 Georgian_Svan
0.891 Greek_Macedonia
0.892 Iraqi_Arab
0.900 Macedonian_East
0.901 Udi_Azerbaijan
0.904 Macedonian_Vardar
0.905 Macedonian_Northeast&Skopje
0.905 Macedonian_Polog
0.906 Spanish_Galicia
0.906 Bulgarian_Thrace
0.913 French_Southwest
0.914 Spanish_Baleares
0.914 Spanish_Canarias
0.914 Turk_Cyprus
0.915 Macedonian_South
0.915 Nihali
0.915 Greek_Thessaloniki
0.916 Portuguese
0.917 Greek_Lemnos
0.918 Italian_Aosta_Valley
0.918 Greek_Thessaly
0.918 Albanian_Kosovo
0.919 Greek_Peloponnese
0.920 Syrian_Muslim
0.920 Turk_East_Black_Sea
0.921 Italian_Friuli_VG
0.921 Spanish_Cantabria
0.922 Greek_Thrace
0.923 Italian_Apulia
0.923 Greek_Athens
0.923 Georgian
0.924 Spanish_Catalonia
0.924 Spanish_Andalusia
0.925 Turk_Ahiska
0.925 Ashkenazi_Jews
0.926 Spanish_Valencia
0.926 Spanish_Asturias
0.926 Italian_Trentino
0.926 Albanian
0.926 Italian_Veneto
0.929 Georgian_Mingrelian
0.929 Spanish_Castilla-Leon
0.930 Greek_Central
0.930 Italian_Piedmont
0.932 Moldovan_Jewish
0.932 Lebanese_Muslim
0.933 Italian_Emilia
0.934 Spanish_Aragon
0.935 Spanish_La_Rioja
0.936 Greek_Foca
0.936 Swiss_Italian
0.936 Spanish_Basque
0.937 Georgian_Gurian
0.940 Italian_Lombardy
0.941 Greek_Fournoi
0.942 Italian_Liguria
0.943 Italian_Sicily
0.943 Italian_Tuscany
0.943 Georgian_Adjara
0.943 Italian_Lazio
0.944 Georgian_Imereti
0.946 Mandean
0.948 Italian_Romagna
0.948 Kyrgyz_Pamir
0.949 Azeri_Jew
0.949 Italian_Marche
0.949 Armenian_East
0.950 Greek_Icaria
0.951 Italian_Abruzzo
0.952 Greek_Crete
0.954 Nusayri_Turkey
0.955 Greek_Izmir
0.957 Assyrian_South
0.960 Assyrian_North
0.960 Greek_Kos
0.961 Kurdish_Jew
0.962 Italian_Calabria
0.963 Italian_Campania
0.964 Greek_Rhodes
0.965 Palestinian
0.966 Assyrian_West
0.966 Hemshin
0.966 Armenian_West
0.966 Jordanian_Muslim
0.967 Laz
0.967 French_Corsica
0.967 Iraqi_Jew
0.969 Greek_Cappadocia
0.969 Italian_Jews
0.971 Nepali_Newar_Shrestha
0.979 Greek_Pontus
0.984 Greek_Cypriot
0.992 Lebanese_Christian
0.994 Sephardic_Jews
0.996 Kuwait1
1.002 Jordanian_Christian
1.002 Morocco_Jews
1.003 Kyrgyz
1.004 Syrian_SW_Christian
1.004 Palestinian_Christian
1.032 Sardinian
1.034 Saudi
1.052 Santhal
1.054 Khakass
1.058 Mawasi
1.059 Yemenite_Mahra
1.060 Bedouin
1.061 Kuwait2
1.062 Egyptian
1.071 Coptic
1.099 Bhunjia
1.107 Dhurwa
1.122 Ho
1.128 Kharia
1.128 Savara
1.156 Altaian_Telengit
1.162 Gadaba
1.166 Altaian_Kizhi
1.170 Yemenite_mixed
1.177 Juang
1.179 BONDA
1.186 Algerian
1.197 Moroccan
1.325 Khasi
1.382 Kalmyk
1.426 Tuvan
1.452 Mongol_Uuld
1.516 Mongol_Khalkh
1.518 Malay_Malaysia
1.528 Buryat
1.570 Burmanese
1.576 Western_Indonesian
1.602 Nepali_Gurung
1.608 PANIYA
1.616 Khamnigan
1.640 Garo
1.674 Dungan
1.675 Sakha_Yakutia
1.724 Tibetan
1.731 Tu
1.734 Ethiopian
1.750 Yukagir
1.757 Evenk
1.760 Cambodians
1.761 Nepali_Kirant_Rai
1.823 Xibo
1.845 Nivh
1.855 Negidal
1.856 Nanai
1.860 Oroqen
1.866 Daur
1.867 Naga
1.882 Hezhen
1.884 Yizu
1.885 Naxi
1.896 Han_north
1.906 Japanese
1.914 Korean
1.931 Lahu
1.934 Han_central
1.942 Han_south
1.945 Vietnamese
1.946 Tujia
1.952 She
1.954 Miaozu
1.969 ZHUANG
1.987 Dai
2.108 Somali
2.956 Sandawe_He
3.516 Luhya
3.535 Bantu_N.E.
3.645 Bantu_S.E._Tswana
3.647 Bantu_S.E._Pedi
3.666 Bantu_S.E._Zulu
3.671 Bantu_S.E._S.Sotho
3.686 Bantu_S.W._Herero
3.701 Mandenka
3.713 Bantu_S.W._Ovambo
3.785 Yoruba

[Lemminkäinen]

Doesn't that include PuntDNAL K12 though? In the CSV table at Lucas's Vahaduo fork (http://vahaduo.genetics.ovh/puntdnal-k12modern-vahaduo.htm), Chuvashes have one of the highest percentages of the European_HG component:

European_HG,Population
58.5,Lithuanian
57.5,Estonian
55.0,Finnish
53.0,Belarusian
52.0,Russian
51.0,Icelandic
50.0,Swedish
48.0,Norwegian
47.5,Mordovian
47.0,Scottish_West
46.0,German_North
46.0,Czech
45.5,Dutch_North
45.5,Chuvash
45.0,Irish
43.5,English_South
42.0,Hungarian
41.5,Utahn_European
40.5,German_South
40.5,Dutch_South

Chuvashes even end up in the same cluster with Finns and Hungarians (if this took FST into account, I think Chuvashes would cluster with Nogais based on their level of Mongoloid admixture):

https://i.ibb.co/4tLk3B5/a.png



Here:


t=read.csv("https://pastebin.com/raw/2TdwA3Le",row.names=1,check.names=F) # Dodecad K12b updated
t=t/100

fst=as.matrix(as.dist(read.csv(text="0,,,,,,,,,,,
121,0,,,,,,,,,,
074,144,0,,,,,,,,,
123,072,142,0,,,,,,,,
062,139,056,142,0,,,,,,,
048,123,067,129,041,0,,,,,,
081,101,099,091,098,086,0,,,,,
132,181,097,173,136,140,135,0,,,,
066,146,060,145,052,063,099,124,0,,,
118,052,137,032,137,123,085,170,139,0,,
041,129,052,130,033,041,082,123,047,125,0,
173,218,129,209,185,183,172,051,169,206,171,0",header=F)))
fst=fst/mean(fst)
t=as.matrix(t)%*%fst

d=as.matrix(dist(t))
s=sort(d["Mari",])
cat(paste(sprintf("%.3f",s),names(s)),sep="\n")

I still don't know if this is the right way to account for FST.

Maris ended up being closer to many South Asian populations than to Karelians, and they're closer to Turkmens and Uzbeks than to Komis.

Also Maris are closer to Bashkir_Central than to Bashkir_North, because the combined proportion of the Siberian, East_Asian, and Southeast_Asian components is 30% in Maris, 31% in central Bashkirs, 25% in northern Bashkirs, and 41% in southern Bashkirs. The Maris who live in Bashkortostan mostly live in northern Bashkortostan, so if they mix with the local Bashkirs, maybe it only makes them less Mongoloid.

0.000 Mari
0.070 Bashkir_Central
0.114 Udmurt
0.140 Bashkir_North
0.142 Chuvash
0.162 Crimean_Tatar_Steppe
0.174 Besermyan_Udmurtia
0.206 Lipka_Tatar
0.238 Turkmen_Uzbekistan
0.266 Tatar_Kazan
0.280 Uzbek
0.300 Turkmen_Afghanistan
0.312 Nogai
0.319 Bashkir_South
0.326 Komi
0.328 Turkmen_Iran
0.345 Uzbeki
0.397 Tatar_Mishar
0.401 Turkmen_TM
0.404 Tajik_Mountain
0.420 Tajik_Lowland
0.449 Tatar_Siberia
0.452 Burusho
0.470 Tajik_Kabul
0.483 Pamiri_Ishkashim
0.489 Nepali_Khas_Brahmin
0.492 Brahmin_Uttaranchal
0.505 Kho
0.522 PAK_Kohistani
0.522 Pamiri_Shughnan
0.522 Russian_Ural
0.526 Tajik_Herat
0.530 Kashmiri
0.539 Haryana_Ror
0.543 Veps
0.544 Punjabi_Tarkhan
0.548 Pamiri_Rushan
0.550 Punjabi_Jatt
0.551 West_Bengal_Brahmin
0.552 Nepali_Khas_Kshatriya
0.555 Punjabi_Khatri
0.556 Pashtun_Yusafzai
0.558 Gujarati_Brahmin
0.561 Tatar_Zabolotniye
0.563 Pashtun_Uthmankhel
0.565 Sindhi_Hindu
0.567 Tajik_Panjshir&Kapisa
0.569 Kalash
0.571 Russian_Northern_Dvina
0.572 Finnish_East
0.574 Pashtun_Tarkalani
0.578 Nogai_Stavropol
0.584 Turk_Northwest
0.586 Pashtun_Kandahar
0.586 Nuristani
0.587 Meena
0.589 Cochin_Jews
0.593 Kshatriya
0.595 Karelian
0.599 Turk_Southwest
0.608 Brahmins_from_Tamil_Nadu
0.616 Bnei_Menashe_Jews
0.617 Turk_Central_Black_Sea
0.617 Malayali
0.619 Yaghnobi_Tajikistan
0.620 North_Russian
0.620 Iyer
0.621 Mordovian
0.628 Russian_Kostroma
0.629 Iyengar
0.635 Uyghur
0.635 Balkan_Gypsy
0.635 Turk_South
0.635 Nogai_Astrakhan
0.636 Bangladeshi
0.640 Lambadi
0.642 Karakalpak
0.646 Finnish_West
0.648 Hazara
0.651 Tharus
0.652 Meghawal
0.654 Dharkars
0.657 Kurmi
0.661 Abazin
0.663 Kanjars
0.667 Turk_West_BlackSea
0.668 Crimean_Tatar_Mountain
0.669 Kabardin
0.679 Parsi_India
0.681 Russian
0.683 Turk_Central_West
0.683 Karachay
0.684 Balkar
0.690 Iranian_Khorasan
0.691 Velamas
0.701 Circassian
0.705 Uttar_Pradesh_Scheduled_Caste
0.707 Tamil_Nadu_Scheduled_Caste
0.709 Balochi
0.713 Turk_Trakya
0.715 Turk_Central_East
0.717 Russian_Ryazan
0.718 Dusadh
0.719 Azerbaijani_Iran
0.723 Azerbaijani_Turkey
0.725 Kurumba
0.727 Kumyk
0.728 Turk_Deliorman
0.735 Russian_Tver
0.736 Turk_Southeast
0.741 Estonian
0.741 Kol
0.746 Piramalai_Kallars
0.747 Iranian_Bandari
0.747 Ossetian
0.749 Azerbaijani_Republic
0.762 Ingush
0.764 Azerbaijani_Dagestan
0.765 Chenchus
0.767 Tubalar
0.773 Russian_Kursk
0.776 Iranian_Fars
0.777 Iranian_Kerman
0.778 Adyghe
0.779 Russian_Oryol
0.780 Chamar
0.782 Lak
0.782 Chechen
0.786 Altaian_Chelkan
0.787 Ossetian_South
0.788 Tabasaran
0.789 SAKILLI
0.790 Dargin
0.792 Dargin_Kaitag
0.792 Hungarian_Transylvania+Székely
0.796 Russian_Voronezh
0.798 Lezgin
0.799 Turkmen_Iraq
0.802 Ukrainian
0.802 Russian_Smolensk
0.803 Belarusian_Minsk
0.806 Dargin_Kubachi
0.809 Latvian
0.814 Hakkipikki
0.814 Belorussian
0.815 Lithuanian
0.822 Polish_Mazovia
0.823 Talysh_Azerbaijan
0.823 Polish_Warmia-Masuria
0.823 Ukrainian_Ivano-Frankivsk
0.824 Moldovan_North
0.825 Iranian_Lur
0.826 North_Kannadi
0.827 Hungarian_Alföld
0.828 Hungarian_North
0.829 Turk_Makedonya
0.830 Iranian_Mazandaran
0.830 Moldovan_Central
0.831 Norwegian
0.831 Hungarian
0.834 Slovak
0.835 Polish
0.838 Kurd_Sorani
0.840 Swedish
0.841 Hungarian_Transdanubia+Budapest
0.842 Kurd_Feyli
0.844 Turk_East
0.845 Yazidi_Kurd
0.845 Kurd_Kurmanji
0.845 Sorb_Lusatia
0.849 Icelandic
0.849 Czech
0.850 Shor
0.852 German
0.852 Dutch
0.857 Danish
0.858 Moldovan_South
0.858 Gond
0.859 Kazakh
0.859 Croat
0.861 French_North
0.862 German_Northwest
0.862 Irish
0.862 Moldovan_Gagauz
0.863 Scottish
0.863 Slovenian
0.863 Romanian
0.864 Bosnian
0.865 Serb
0.866 English_North
0.866 Croat_South
0.866 Pomak_Greece
0.866 English_South
0.868 French_Northwest
0.869 Iraqi_Baghdad
0.870 English
0.875 Abkhazian
0.875 Belgian
0.878 Bulgarian_West
0.879 French_Northeast
0.880 Pomak_Bulgaria
0.884 Bavarian_German
0.884 Arab_Iran
0.885 Bulgarian_Central
0.886 Bulgarian_East
0.886 Montenegrin
0.887 Georgian_Svan
0.891 Greek_Macedonia
0.892 Iraqi_Arab
0.900 Macedonian_East
0.901 Udi_Azerbaijan
0.904 Macedonian_Vardar
0.905 Macedonian_Northeast&Skopje
0.905 Macedonian_Polog
0.906 Spanish_Galicia
0.906 Bulgarian_Thrace
0.913 French_Southwest
0.914 Spanish_Baleares
0.914 Spanish_Canarias
0.914 Turk_Cyprus
0.915 Macedonian_South
0.915 Nihali
0.915 Greek_Thessaloniki
0.916 Portuguese
0.917 Greek_Lemnos
0.918 Italian_Aosta_Valley
0.918 Greek_Thessaly
0.918 Albanian_Kosovo
0.919 Greek_Peloponnese
0.920 Syrian_Muslim
0.920 Turk_East_Black_Sea
0.921 Italian_Friuli_VG
0.921 Spanish_Cantabria
0.922 Greek_Thrace
0.923 Italian_Apulia
0.923 Greek_Athens
0.923 Georgian
0.924 Spanish_Catalonia
0.924 Spanish_Andalusia
0.925 Turk_Ahiska
0.925 Ashkenazi_Jews
0.926 Spanish_Valencia
0.926 Spanish_Asturias
0.926 Italian_Trentino
0.926 Albanian
0.926 Italian_Veneto
0.929 Georgian_Mingrelian
0.929 Spanish_Castilla-Leon
0.930 Greek_Central
0.930 Italian_Piedmont
0.932 Moldovan_Jewish
0.932 Lebanese_Muslim
0.933 Italian_Emilia
0.934 Spanish_Aragon
0.935 Spanish_La_Rioja
0.936 Greek_Foca
0.936 Swiss_Italian
0.936 Spanish_Basque
0.937 Georgian_Gurian
0.940 Italian_Lombardy
0.941 Greek_Fournoi
0.942 Italian_Liguria
0.943 Italian_Sicily
0.943 Italian_Tuscany
0.943 Georgian_Adjara
0.943 Italian_Lazio
0.944 Georgian_Imereti
0.946 Mandean
0.948 Italian_Romagna
0.948 Kyrgyz_Pamir
0.949 Azeri_Jew
0.949 Italian_Marche
0.949 Armenian_East
0.950 Greek_Icaria
0.951 Italian_Abruzzo
0.952 Greek_Crete
0.954 Nusayri_Turkey
0.955 Greek_Izmir
0.957 Assyrian_South
0.960 Assyrian_North
0.960 Greek_Kos
0.961 Kurdish_Jew
0.962 Italian_Calabria
0.963 Italian_Campania
0.964 Greek_Rhodes
0.965 Palestinian
0.966 Assyrian_West
0.966 Hemshin
0.966 Armenian_West
0.966 Jordanian_Muslim
0.967 Laz
0.967 French_Corsica
0.967 Iraqi_Jew
0.969 Greek_Cappadocia
0.969 Italian_Jews
0.971 Nepali_Newar_Shrestha
0.979 Greek_Pontus
0.984 Greek_Cypriot
0.992 Lebanese_Christian
0.994 Sephardic_Jews
0.996 Kuwait1
1.002 Jordanian_Christian
1.002 Morocco_Jews
1.003 Kyrgyz
1.004 Syrian_SW_Christian
1.004 Palestinian_Christian
1.032 Sardinian
1.034 Saudi
1.052 Santhal
1.054 Khakass
1.058 Mawasi
1.059 Yemenite_Mahra
1.060 Bedouin
1.061 Kuwait2
1.062 Egyptian
1.071 Coptic
1.099 Bhunjia
1.107 Dhurwa
1.122 Ho
1.128 Kharia
1.128 Savara
1.156 Altaian_Telengit
1.162 Gadaba
1.166 Altaian_Kizhi
1.170 Yemenite_mixed
1.177 Juang
1.179 BONDA
1.186 Algerian
1.197 Moroccan
1.325 Khasi
1.382 Kalmyk
1.426 Tuvan
1.452 Mongol_Uuld
1.516 Mongol_Khalkh
1.518 Malay_Malaysia
1.528 Buryat
1.570 Burmanese
1.576 Western_Indonesian
1.602 Nepali_Gurung
1.608 PANIYA
1.616 Khamnigan
1.640 Garo
1.674 Dungan
1.675 Sakha_Yakutia
1.724 Tibetan
1.731 Tu
1.734 Ethiopian
1.750 Yukagir
1.757 Evenk
1.760 Cambodians
1.761 Nepali_Kirant_Rai
1.823 Xibo
1.845 Nivh
1.855 Negidal
1.856 Nanai
1.860 Oroqen
1.866 Daur
1.867 Naga
1.882 Hezhen
1.884 Yizu
1.885 Naxi
1.896 Han_north
1.906 Japanese
1.914 Korean
1.931 Lahu
1.934 Han_central
1.942 Han_south
1.945 Vietnamese
1.946 Tujia
1.952 She
1.954 Miaozu
1.969 ZHUANG
1.987 Dai
2.108 Somali
2.956 Sandawe_He
3.516 Luhya
3.535 Bantu_N.E.
3.645 Bantu_S.E._Tswana
3.647 Bantu_S.E._Pedi
3.666 Bantu_S.E._Zulu
3.671 Bantu_S.E._S.Sotho
3.686 Bantu_S.W._Herero
3.701 Mandenka
3.713 Bantu_S.W._Ovambo
3.785 Yoruba

The HG in Europe depends on how the Pontic–Caspian steppe is defined. Fst is a weak indicator for the origin of mixed populations. Think where would be someone with Finnish-Ashkenazi admixture. Same fits for all people with European-North Asian ancestry. We should know the admixture age.

[Komintasavalta]

The HG in Europe depends on how the Pontic–Caspian steppe is defined. Fst is a weak indicator for the origin of mixed populations. Think where would be someone with Finnish-Ashkenazi admixture. Same fits for all people with European-North Asian ancestry. We should know the admixture age.

So as an old-timer genetics pro, what other method do you recommend?

Table S1 of Khvorykh et al. 2020 contains a table for the number of shared IBD segments between populations (normalized to account for differences between sequencing protocols): https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7696950/.

The list below shows the normalized number of shared IBD fragments with Maris. The highest-ranking Central Asian population is Yaghnobi_Tajikistan (8.27), which comes before any Western European population:


$ curl https://pastebin.com/raw/4XZcCrpP|tr -d \\r>ibd
$ tp(){ awk '{for(i=1;i<=NF;i++)a[i][NR]=$i}END{for(i in a)for(j in a[i])printf"%s"(j==NR?"\n":FS),a[i][j]}' "FS=${1-$'\t'}";}
$ grep Maris ibd|cat <(sed -n 2p ibd) -|tp ,|sed 1,3d|head -n-4|awk -F, 'NR==FNR{a[$2]=$3" "$2" "$1;next}{print$2,a[$1]}' ibd -|sort -rn
54.71 Chuvashes_Russia Chu_EUR 3e
21.72 Mishar-Tatars Mis_EUR 1e
20.71 Tatars Tat_EUR 3e
20.07 Udmurds Udm_EUR 4e
16.56 Khantys Kha_SIB 7ev
15.2 Mansi:Russia Man_SIB 8sev
14.9 Kryashen-Tatars_Russia Kry_EUR 3e
14.67 Bashkirs_Russia BSh_EUR 5e
14.15 Saami:Finland Saa_EUR 5se
13.98 Latvians Lat_EUR 3e
13.43 Komis_Russia Kom_EUR 6ev
13.1 Mordvins_Russia Mor_EUR 3e
13.02 Vepsas_Russia Vep_EUR 6ev
12.57 Russian:Russia Rus_EUR 15sev
12.1 Ingrians_Russia_North Ing_EUR 3e
11.5 Nenets Nen_SIB 1v
11.44 Cossacks_Ukraine Cos_EUR 4e
11.27 Finnish:Finland Fin_EUR 6se
11.18 Karelians Kar_EUR 4ev
11.07 Tundra-Nenets Tun_SIB 3e
10.96 Polish:Poland Pol_EUR 5se
10.96 Estonian:Estonia Est_EUR 8se
10.78 Selkups_Russia Sel_SIB 3e
10.14 Forest-Nenets For_SIB 3e
9.9 Belarusians Bel_EUR 4e
9.53 Kets_Russia Ket_SIB 3e
9.47 Lithuanians Lit_EUR 3e
8.29 Moldavians Mol_EUR 2e
8.27 Yaghnobi_Tajikistan Yag_CAS 1e
8.25 Bulgarian:Bulgaria Bul_EUR 2s
8.22 Ukrainians Ukr_EUR 7e
8.19 Tlingit:Russia Tli_ARC 2s
8.16 Swedes_Sweden Swe_EUR 2e
8.1 Croats_Bosnia-Herzegovina Cro_EUR 4e
8.02 Finnish_in_Finland FIN_EUR 99
7.95 Hungarian:Hungary Hun_EUR 4se
7.92 Icelandic:Iceland Ice_EUR 2s
6.99 Utah_(CEPH)_NW_Eur_Ancestry CEU_EUR 91
6.99 British_in_England_and_Scotland GBR_EUR 88
6.38 English:England Eng_EUR 1s
6.38 Aleut:Russia Ale_ARC 2s
6.19 Orcadian:OrkneyIslands Orc_EUR 4s
6.13 Albanian:Albania Alb_EUR 4se
6.07 Rushan-Vanch_Tajikistan Rus_CAS 2e
6.07 French:France Fre_EUR 3s
5.82 Tubalar:Russia Tub_SIB 2s
5.53 Norwegian:Norway Nor_EUR 1s
5.48 Spanish:Spain Spa_EUR 2s
5.43 Greek:Greece Gre_EUR 2s
5.33 Chukchi:Russia Chu_ARC 6se
5.24 Kazakhs_Kazakhstan Kaz_CAS 3e
5.22 Denisova5 Alt_XXX 1
5.09 Avars_Russia_Caucaz Ava_CAU 3e
5.08 Loschbour Los_XXX 1
4.96 Tajiks Taj_CAS 3se
4.95 Chagyrskaya Cha_XXX 1
4.9 Ishkasim_Tajikistan Ish_CAS 2e
4.89 Balkars_Russia_Caucaz Bal_CAU 3e
4.74 Nganasans Nga_SIB 2e
4.71 Kabardins_Russia_Caucaz Kab_CAU 4e
4.64 Shor_Russia Sho_SIB 2e
4.6 Turkish:Turkey Tur_MDE 2s
4.49 Turkmens_Uzbekistan TKm_CAS 3e
4.46 Germans Ger_EUR 3e
4.39 Adygei:Russia(Caucasus) Ady_CAU 2s
4.35 Azerbaijanis Aze_MDE 3e
4.27 Iberian_Population_in_Spain IBS_EUR 107
4.25 Uzbek Uzb_CAS 3e
4.25 Lezgin:Russia Lez_CAU 6se
4.23 Basque:France Bas_EUR 2s
4.2 Burusho:Pakistan Bur_SAS 2s
4.18 Pathan:Pakistan Pat_SAS 2s
4.12 North_Ossetian:Russia NOc_CAU 4se
4.11 Shugnan_Tajikistan Shu_CAS 1e
4.1 Toscani_Italia TSI_EUR 106
4.06 Bergamo:Italy Ber_EUR 2s
3.93 Tabasarans_Russia_Caucaz Tab_CAU 3e
3.93 Altaian Alt_CAS 8sev
3.75 Circassians_Russia_Caucaz Cir_CAU 3e
3.63 Kumyks_Russia Kum_CAU 3e
3.62 Uygurs_Kazakhstan Uyg_CAS 3se
3.62 Georgian:Georgia Geo_CAU 4se
3.61 Oroqen:China Oro_EAS 2s
3.56 Kyrgyz:Kyrgyzystan Kyr_CAS 9se
3.51 Chechen:Russia Che_CAU 1s
3.37 Roma_Bosnia-Herzegovina Rom_EUR 3e
3.33 Kshatriya_India_ Ksh_SAS 1e
3.26 Abkhasian:Abkhazia Abk_CAU 5se
3.23 Puerto_Ricans_from_Puerto_Rico PUR_AMR 104
3.23 Crete:Greece Cre_EUR 2s
3.16 Tuscan:Italy Tus_EUR 2s
3.16 Makrani:Pakistan Mak_SAS 2s
3.16 Brahmin:India Bra_SAS 7se
3.14 BedouinB:Israel(Negev) Bed_MDE 2s
3.06 Sakha Sak_SIB 7e
3.05 Colombians_Medellin_Colombia CLM_AMR 93
3 Buryats Bur_SIB 18ev
2.92 Sindhi:Pakistan Sin_SAS 2s
2.9 Even:Russia Eve_SIB 12sev
2.88 Yakuts Yak_SIB 4sev
2.85 Hazara:Pakistan Haz_SAS 2s
2.8 Palestinian:Israel(Central) Pal_MDE 3s
2.8 Balochi:Pakistan Bal_SAS 2s
2.79 Shtuttgart Lbk_XXX 1
2.72 Itelman:Russia Ite_ARC 1s
2.68 Evenks EVk_SIB 14ev
2.67 Druze:Israel(Carmel) Dru_MDE 5se
2.62 Mongola:China Mon_EAS 8se
2.62 Kalash:Pakistan Kal_SAS 2s
2.6 Mexican_Ancestry_Los_Angeles MXL_AMR 58
2.59 Daur:China Dau_EAS 1s
2.58 Samaritan:Israel Sam_MDE 1s
2.54 Tuvinians Tuv_SIB 3e
2.54 Armenian:Armenia Arm_MDE 8se
2.33 Punjabi_Lahore_Pakistan PJL_SAS 88
2.08 Iranian:Iran Ira_MDE 8se
2.07 Maori:NewZealand Mao_OCE 1s
2.05 Hezhen:China Hez_EAS 2s
2.05 Assyrians_Armenia Ass_MDE 3e
1.99 Gupta_India Gup_SAS 1e
1.87 Ulchi:Russia Ulc_ARC 2s
1.85 Saharawi:WesternSahara(Morocco) Sah_AFR 2s
1.84 Gujarati_Indian_Houston_Texas GIH_SAS 98
1.79 Punjabi:Pakistan Pun_SAS 5se
1.76 Arabs-Israel Ara_MDE 5e
1.75 Koryaks Kor_ARC 16e
1.72 Relli:India Rel_SAS 2s
1.71 Eskimo_Sireniki:Russia Esk_ARC 9se
1.69 Sardinian:Italy Sar_EUR 3s
1.58 Jordanian:Jordan Jor_MDE 5se
1.55 Bengali:Bangladesh Ben_SAS 4se
1.52 Kol_India Kol_SAS 1e
1.51 Yemenite_Jew:Yemen Yem_MDE 2s
1.5 Kalmyk Kal_CAS 1v
1.49 Lebanese_Lebanon_ Leb_MDE 1e
1.43 Peruvians_Lima_Peru PEL_AMR 83
1.39 Kusunda:Nepal Kus_SAS 2s
1.34 Ustishim Ust_XXX 1
1.34 Mozabite:Algeria Moz_AFR 2s
1.29 Bengali_from_Bangladesh BEB_SAS 86
1.27 Tu:China TuX_EAS 2s
1.22 Marwadi_India Mar_SAS 1e
1.2 Saudi-Arabians Sau_MDE 2e
1.19 Indian_Telugu_from_the_UK ITU_SAS 102
1.11 Asur_India Asu_SAS 1e
1.07 Xibo:China Xib_EAS 2s
1.07 Kapu:India Kap_SAS 3se
1.07 Dhaka_Bangladesh_ Dha_SAS 3e
1.03 Sri_Lankan_Tamil_from_UK STU_SAS 101
1.02 DenisovaPinky Den_XXX 1
1.01 Madiga:India Mad_SAS 2s
0.9 Korean:Korea Kor_EAS 2s
0.85 Yi:China YiX_EAS 2s
0.85 Miao:China Mia_EAS 2s
0.81 Thakur_India Tha_SAS 1e
0.81 Americans_of_African_Ancestry_USA ASW_AFR 53
0.77 Kurmi_India Kur_SAS 1e
0.75 Madhya-Pradesh_India MAd_SAS 1e
0.72 Japanese:Japan Jap_EAS 3s
0.71 Tujia:China Tuj_EAS 2s
0.71 Naxi:China Nax_EAS 2s
0.68 Mala:India Mal_SAS 2s
0.67 Zapotec:Mexico Zap_AMR 2s
0.67 Burmese:Myanmar BUm_SAS 8e
0.63 Han_Chinese_Beijing CHB_EAS 103
0.61 Japanese_Tokyo JPT_EAS 104
0.55 Lahu:China Lah_EAS 2s
0.54 Burmese_Myanmar Bur_EAS 2s
0.51 Cambodian:Cambodia Cam_EAS 2s
0.46 African_Caribbeans_in_Barbados ACB_AFR 94
0.45 Piapoco:Colombia Pia_AMR 2s
0.45 Mayan:Mexico May_AMR 2s
0.41 Tamang_Nepal Tam_SAS 1e
0.39 Balija_India BAj_SAS 1e
0.38 Orissa_India Ori_SAS 1e
0.38 Colla_Argentina Col_AMR 4e
0.37 Santhal_India San_SAS 1e
0.36 She:China She_EAS 2s
0.35 Yadava:India Yad_SAS 2s
0.35 Thai:Thailand Tha_EAS 2s
0.35 Ho_India Ho_SAS 1e
0.34 Southern_Han_Chinese CHS_EAS 100
0.32 Khonda_Dora:India Kho_SAS 1s
0.31 Kinh_Ho_Chi_Minh_City_Vietnam KHV_EAS 98
0.29 Hawaiian:USA Haw_OCE 1s
0.27 Gambian:Gambia Gam_AFR 2s
0.26 Mixe:Mexico Mix_AMR 5s
0.25 Chinese_Dai_Xishuangbanna CDX_EAS 86
0.24 Somali:Kenya Som_AFR 1s
0.21 Aeta_Philippines Aet_OCE 3e
0.2 Vietnamese_central Vie_EAS 10e
0.2 Pima:Mexico Pim_AMR 2s
0.2 Luzon_Philippines Luz_OCE 2e
0.19 Vizayan_Philippines Viz_OCE 2e
0.18 Kinh:Vietnam Kin_EAS 2s
0.17 Dai:China Dai_EAS 4s
0.16 Irula:India Iru_SAS 2s
0.15 Quechua:Peru Que_AMR 3s
0.14 Karitiana:Brazil Kar_AMR 3s
0.12 Wichi_Argentina Wic_AMR 4e
0.12 Luhya:Kenya Luh_AFR 2s
0.12 Dusun:Brunei Dus_OCE 10se
0.11 Papuan:PapuaNewGuinea Pap_OCE 15s
0.11 Murut_Brunei Mur_OCE 8e
0.11 Masai:Kenya Mas_AFR 2s
0.11 Han:China Han_EAS 3s
0.11 Batak_Philippines Bat_OCE 3e
0.1 Luhya_in_Webuye_Kenya LWK_AFR 87
0.1 Ju_hoan_North:Namibia JuX_AFR 4s
0.07 BantuTswana:BotswanaOrNamibia Ban_AFR 6s
0.05 Gambian_in_Western_Divisions_Gambia GWD_AFR 110
0.04 Mende_in_Sierra_Leone MSL_AFR 73
0.03 Yoruba_in_Ibadan_Nigeria YRI_AFR 101
0.03 Esan_in_Nigeria ESN_AFR 92
0 Yoruba:Nigeria Yor_AFR 3s
0 Surui:Brazil Sur_AMR 2s
0 Mende:SierraLeone Men_AFR 2s
0 Mbuti:Congo Mbu_AFR 4s
0 Mandenka:Senegal Man_AFR 3s
0 Malayan_India MAy_SAS 1e
0 Luo:Kenya Luo_AFR 2s
0 Lebbo_Indonesia Leb_OCE 4e
0 Kosipe_Papua_New_Guinea Kos_OCE 3e
0 Koinanbe_Papua_New_Guinea Koi_OCE 3e
0 Khomani_San:SouthAfrica Kho_AFR 2s
0 Igorot:Philippines Igo_OCE 10se
0 Gond_India Gon_SAS 1e
0 Esan:Nigeria Esa_AFR 2s
0 Dinka:Sudan Din_AFR 3s
0 Congo-pygmies Con_AFR 3e
0 Chane:Argentina Cha_AMR 1s
0 Cachi_Argentina Cac_AMR 5e
0 Bougainville:PapuaNewGuinea Bou_OCE 2s
0 Biaka:CentralAfricanRepublic Bia_AFR 2s
0 Bajo_Indonesia Baj_OCE 4e
0 Australian:Australia Aus_OCE 2s
0 Atayal:Taiwan Ata_EAS 1s
0 Ami:Taiwan Ami_EAS 2s
0 Agta_Philippines Agt_OCE 3e

[Leto]

Table S1 of Khvorykh et al. 2020 contains a table for the number of shared IBD segments between populations (normalized to account for differences between sequencing protocols): https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7696950/.

Does that study use older datasets? Tajiks, Lezgins, etc.

[Lemminkäinen]

So as an old-timer genetics pro, what other method do you recommend?

Table S1 of Khvorykh et al. 2020 contains a table for the number of shared IBD segments between populations (normalized to account for differences between sequencing protocols): https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7696950/.

The list below shows the normalized number of shared IBD fragments with Maris. The highest-ranking Central Asian population is Yaghnobi_Tajikistan (8.27), which comes before any Western European population:


$ curl https://pastebin.com/raw/4XZcCrpP|tr -d \\r>ibd
$ tp(){ awk '{for(i=1;i<=NF;i++)a[i][NR]=$i}END{for(i in a)for(j in a[i])printf"%s"(j==NR?"\n":FS),a[i][j]}' "FS=${1-$'\t'}";}
$ grep Maris ibd|cat <(sed -n 2p ibd) -|tp ,|sed 1,3d|head -n-4|awk -F, 'NR==FNR{a[$2]=$3" "$2" "$1;next}{print$2,a[$1]}' ibd -|sort -rn
54.71 Chuvashes_Russia Chu_EUR 3e
21.72 Mishar-Tatars Mis_EUR 1e
20.71 Tatars Tat_EUR 3e
20.07 Udmurds Udm_EUR 4e
16.56 Khantys Kha_SIB 7ev
15.2 Mansi:Russia Man_SIB 8sev
14.9 Kryashen-Tatars_Russia Kry_EUR 3e
14.67 Bashkirs_Russia BSh_EUR 5e
14.15 Saami:Finland Saa_EUR 5se
13.98 Latvians Lat_EUR 3e
13.43 Komis_Russia Kom_EUR 6ev
13.1 Mordvins_Russia Mor_EUR 3e
13.02 Vepsas_Russia Vep_EUR 6ev
12.57 Russian:Russia Rus_EUR 15sev
12.1 Ingrians_Russia_North Ing_EUR 3e
11.5 Nenets Nen_SIB 1v
11.44 Cossacks_Ukraine Cos_EUR 4e
11.27 Finnish:Finland Fin_EUR 6se
11.18 Karelians Kar_EUR 4ev
11.07 Tundra-Nenets Tun_SIB 3e
10.96 Polish:Poland Pol_EUR 5se
10.96 Estonian:Estonia Est_EUR 8se
10.78 Selkups_Russia Sel_SIB 3e
10.14 Forest-Nenets For_SIB 3e
9.9 Belarusians Bel_EUR 4e
9.53 Kets_Russia Ket_SIB 3e
9.47 Lithuanians Lit_EUR 3e
8.29 Moldavians Mol_EUR 2e
8.27 Yaghnobi_Tajikistan Yag_CAS 1e
8.25 Bulgarian:Bulgaria Bul_EUR 2s
8.22 Ukrainians Ukr_EUR 7e
8.19 Tlingit:Russia Tli_ARC 2s
8.16 Swedes_Sweden Swe_EUR 2e
8.1 Croats_Bosnia-Herzegovina Cro_EUR 4e
8.02 Finnish_in_Finland FIN_EUR 99
7.95 Hungarian:Hungary Hun_EUR 4se
7.92 Icelandic:Iceland Ice_EUR 2s
6.99 Utah_(CEPH)_NW_Eur_Ancestry CEU_EUR 91
6.99 British_in_England_and_Scotland GBR_EUR 88
6.38 English:England Eng_EUR 1s
6.38 Aleut:Russia Ale_ARC 2s
6.19 Orcadian:OrkneyIslands Orc_EUR 4s
6.13 Albanian:Albania Alb_EUR 4se
6.07 Rushan-Vanch_Tajikistan Rus_CAS 2e
6.07 French:France Fre_EUR 3s
5.82 Tubalar:Russia Tub_SIB 2s
5.53 Norwegian:Norway Nor_EUR 1s
5.48 Spanish:Spain Spa_EUR 2s
5.43 Greek:Greece Gre_EUR 2s
5.33 Chukchi:Russia Chu_ARC 6se
5.24 Kazakhs_Kazakhstan Kaz_CAS 3e
5.22 Denisova5 Alt_XXX 1
5.09 Avars_Russia_Caucaz Ava_CAU 3e
5.08 Loschbour Los_XXX 1
4.96 Tajiks Taj_CAS 3se
4.95 Chagyrskaya Cha_XXX 1
4.9 Ishkasim_Tajikistan Ish_CAS 2e
4.89 Balkars_Russia_Caucaz Bal_CAU 3e
4.74 Nganasans Nga_SIB 2e
4.71 Kabardins_Russia_Caucaz Kab_CAU 4e
4.64 Shor_Russia Sho_SIB 2e
4.6 Turkish:Turkey Tur_MDE 2s
4.49 Turkmens_Uzbekistan TKm_CAS 3e
4.46 Germans Ger_EUR 3e
4.39 Adygei:Russia(Caucasus) Ady_CAU 2s
4.35 Azerbaijanis Aze_MDE 3e
4.27 Iberian_Population_in_Spain IBS_EUR 107
4.25 Uzbek Uzb_CAS 3e
4.25 Lezgin:Russia Lez_CAU 6se
4.23 Basque:France Bas_EUR 2s
4.2 Burusho:Pakistan Bur_SAS 2s
4.18 Pathan:Pakistan Pat_SAS 2s
4.12 North_Ossetian:Russia NOc_CAU 4se
4.11 Shugnan_Tajikistan Shu_CAS 1e
4.1 Toscani_Italia TSI_EUR 106
4.06 Bergamo:Italy Ber_EUR 2s
3.93 Tabasarans_Russia_Caucaz Tab_CAU 3e
3.93 Altaian Alt_CAS 8sev
3.75 Circassians_Russia_Caucaz Cir_CAU 3e
3.63 Kumyks_Russia Kum_CAU 3e
3.62 Uygurs_Kazakhstan Uyg_CAS 3se
3.62 Georgian:Georgia Geo_CAU 4se
3.61 Oroqen:China Oro_EAS 2s
3.56 Kyrgyz:Kyrgyzystan Kyr_CAS 9se
3.51 Chechen:Russia Che_CAU 1s
3.37 Roma_Bosnia-Herzegovina Rom_EUR 3e
3.33 Kshatriya_India_ Ksh_SAS 1e
3.26 Abkhasian:Abkhazia Abk_CAU 5se
3.23 Puerto_Ricans_from_Puerto_Rico PUR_AMR 104
3.23 Crete:Greece Cre_EUR 2s
3.16 Tuscan:Italy Tus_EUR 2s
3.16 Makrani:Pakistan Mak_SAS 2s
3.16 Brahmin:India Bra_SAS 7se
3.14 BedouinB:Israel(Negev) Bed_MDE 2s
3.06 Sakha Sak_SIB 7e
3.05 Colombians_Medellin_Colombia CLM_AMR 93
3 Buryats Bur_SIB 18ev
2.92 Sindhi:Pakistan Sin_SAS 2s
2.9 Even:Russia Eve_SIB 12sev
2.88 Yakuts Yak_SIB 4sev
2.85 Hazara:Pakistan Haz_SAS 2s
2.8 Palestinian:Israel(Central) Pal_MDE 3s
2.8 Balochi:Pakistan Bal_SAS 2s
2.79 Shtuttgart Lbk_XXX 1
2.72 Itelman:Russia Ite_ARC 1s
2.68 Evenks EVk_SIB 14ev
2.67 Druze:Israel(Carmel) Dru_MDE 5se
2.62 Mongola:China Mon_EAS 8se
2.62 Kalash:Pakistan Kal_SAS 2s
2.6 Mexican_Ancestry_Los_Angeles MXL_AMR 58
2.59 Daur:China Dau_EAS 1s
2.58 Samaritan:Israel Sam_MDE 1s
2.54 Tuvinians Tuv_SIB 3e
2.54 Armenian:Armenia Arm_MDE 8se
2.33 Punjabi_Lahore_Pakistan PJL_SAS 88
2.08 Iranian:Iran Ira_MDE 8se
2.07 Maori:NewZealand Mao_OCE 1s
2.05 Hezhen:China Hez_EAS 2s
2.05 Assyrians_Armenia Ass_MDE 3e
1.99 Gupta_India Gup_SAS 1e
1.87 Ulchi:Russia Ulc_ARC 2s
1.85 Saharawi:WesternSahara(Morocco) Sah_AFR 2s
1.84 Gujarati_Indian_Houston_Texas GIH_SAS 98
1.79 Punjabi:Pakistan Pun_SAS 5se
1.76 Arabs-Israel Ara_MDE 5e
1.75 Koryaks Kor_ARC 16e
1.72 Relli:India Rel_SAS 2s
1.71 Eskimo_Sireniki:Russia Esk_ARC 9se
1.69 Sardinian:Italy Sar_EUR 3s
1.58 Jordanian:Jordan Jor_MDE 5se
1.55 Bengali:Bangladesh Ben_SAS 4se
1.52 Kol_India Kol_SAS 1e
1.51 Yemenite_Jew:Yemen Yem_MDE 2s
1.5 Kalmyk Kal_CAS 1v
1.49 Lebanese_Lebanon_ Leb_MDE 1e
1.43 Peruvians_Lima_Peru PEL_AMR 83
1.39 Kusunda:Nepal Kus_SAS 2s
1.34 Ustishim Ust_XXX 1
1.34 Mozabite:Algeria Moz_AFR 2s
1.29 Bengali_from_Bangladesh BEB_SAS 86
1.27 Tu:China TuX_EAS 2s
1.22 Marwadi_India Mar_SAS 1e
1.2 Saudi-Arabians Sau_MDE 2e
1.19 Indian_Telugu_from_the_UK ITU_SAS 102
1.11 Asur_India Asu_SAS 1e
1.07 Xibo:China Xib_EAS 2s
1.07 Kapu:India Kap_SAS 3se
1.07 Dhaka_Bangladesh_ Dha_SAS 3e
1.03 Sri_Lankan_Tamil_from_UK STU_SAS 101
1.02 DenisovaPinky Den_XXX 1
1.01 Madiga:India Mad_SAS 2s
0.9 Korean:Korea Kor_EAS 2s
0.85 Yi:China YiX_EAS 2s
0.85 Miao:China Mia_EAS 2s
0.81 Thakur_India Tha_SAS 1e
0.81 Americans_of_African_Ancestry_USA ASW_AFR 53
0.77 Kurmi_India Kur_SAS 1e
0.75 Madhya-Pradesh_India MAd_SAS 1e
0.72 Japanese:Japan Jap_EAS 3s
0.71 Tujia:China Tuj_EAS 2s
0.71 Naxi:China Nax_EAS 2s
0.68 Mala:India Mal_SAS 2s
0.67 Zapotec:Mexico Zap_AMR 2s
0.67 Burmese:Myanmar BUm_SAS 8e
0.63 Han_Chinese_Beijing CHB_EAS 103
0.61 Japanese_Tokyo JPT_EAS 104
0.55 Lahu:China Lah_EAS 2s
0.54 Burmese_Myanmar Bur_EAS 2s
0.51 Cambodian:Cambodia Cam_EAS 2s
0.46 African_Caribbeans_in_Barbados ACB_AFR 94
0.45 Piapoco:Colombia Pia_AMR 2s
0.45 Mayan:Mexico May_AMR 2s
0.41 Tamang_Nepal Tam_SAS 1e
0.39 Balija_India BAj_SAS 1e
0.38 Orissa_India Ori_SAS 1e
0.38 Colla_Argentina Col_AMR 4e
0.37 Santhal_India San_SAS 1e
0.36 She:China She_EAS 2s
0.35 Yadava:India Yad_SAS 2s
0.35 Thai:Thailand Tha_EAS 2s
0.35 Ho_India Ho_SAS 1e
0.34 Southern_Han_Chinese CHS_EAS 100
0.32 Khonda_Dora:India Kho_SAS 1s
0.31 Kinh_Ho_Chi_Minh_City_Vietnam KHV_EAS 98
0.29 Hawaiian:USA Haw_OCE 1s
0.27 Gambian:Gambia Gam_AFR 2s
0.26 Mixe:Mexico Mix_AMR 5s
0.25 Chinese_Dai_Xishuangbanna CDX_EAS 86
0.24 Somali:Kenya Som_AFR 1s
0.21 Aeta_Philippines Aet_OCE 3e
0.2 Vietnamese_central Vie_EAS 10e
0.2 Pima:Mexico Pim_AMR 2s
0.2 Luzon_Philippines Luz_OCE 2e
0.19 Vizayan_Philippines Viz_OCE 2e
0.18 Kinh:Vietnam Kin_EAS 2s
0.17 Dai:China Dai_EAS 4s
0.16 Irula:India Iru_SAS 2s
0.15 Quechua:Peru Que_AMR 3s
0.14 Karitiana:Brazil Kar_AMR 3s
0.12 Wichi_Argentina Wic_AMR 4e
0.12 Luhya:Kenya Luh_AFR 2s
0.12 Dusun:Brunei Dus_OCE 10se
0.11 Papuan:PapuaNewGuinea Pap_OCE 15s
0.11 Murut_Brunei Mur_OCE 8e
0.11 Masai:Kenya Mas_AFR 2s
0.11 Han:China Han_EAS 3s
0.11 Batak_Philippines Bat_OCE 3e
0.1 Luhya_in_Webuye_Kenya LWK_AFR 87
0.1 Ju_hoan_North:Namibia JuX_AFR 4s
0.07 BantuTswana:BotswanaOrNamibia Ban_AFR 6s
0.05 Gambian_in_Western_Divisions_Gambia GWD_AFR 110
0.04 Mende_in_Sierra_Leone MSL_AFR 73
0.03 Yoruba_in_Ibadan_Nigeria YRI_AFR 101
0.03 Esan_in_Nigeria ESN_AFR 92
0 Yoruba:Nigeria Yor_AFR 3s
0 Surui:Brazil Sur_AMR 2s
0 Mende:SierraLeone Men_AFR 2s
0 Mbuti:Congo Mbu_AFR 4s
0 Mandenka:Senegal Man_AFR 3s
0 Malayan_India MAy_SAS 1e
0 Luo:Kenya Luo_AFR 2s
0 Lebbo_Indonesia Leb_OCE 4e
0 Kosipe_Papua_New_Guinea Kos_OCE 3e
0 Koinanbe_Papua_New_Guinea Koi_OCE 3e
0 Khomani_San:SouthAfrica Kho_AFR 2s
0 Igorot:Philippines Igo_OCE 10se
0 Gond_India Gon_SAS 1e
0 Esan:Nigeria Esa_AFR 2s
0 Dinka:Sudan Din_AFR 3s
0 Congo-pygmies Con_AFR 3e
0 Chane:Argentina Cha_AMR 1s
0 Cachi_Argentina Cac_AMR 5e
0 Bougainville:PapuaNewGuinea Bou_OCE 2s
0 Biaka:CentralAfricanRepublic Bia_AFR 2s
0 Bajo_Indonesia Baj_OCE 4e
0 Australian:Australia Aus_OCE 2s
0 Atayal:Taiwan Ata_EAS 1s
0 Ami:Taiwan Ami_EAS 2s
0 Agta_Philippines Agt_OCE 3e

Hey younster, allele distribution is a good method to find out admixtures, because admixing, based on alleles, doesn't destroy the history. IBD as a genomewide statistics reach only 1000 years. F.ex. Roll-Off analyses give seemongly roght results to 2ky, but practically not reliably. Everything that old-fashion geneticists have published using Roll-Off can be thrown to a your computer's recycle bin, among other similar IBD statistics. Dating and so also connected population are too vague. The best method, after you have determined using alleles whether your populations are not mixed in the time frame you assume, are methods based on drift.

[Zanzibar]

Hey younster, allele distribution is a good method to find out admixtures, because admixing, based on alleles, doesn't destroy the history. IBD as a genomewide statistics reach only 1000 years. F.ex. Roll-Off analyses give seemongly roght results to 2ky, but practically not reliably. Everything that old-fashion geneticists have published using Roll-Off can be thrown to a your computer's recycle bin, among other similar IBD statistics. Dating and so also connected population are too vague. The best method, after you have determined using alleles whether your populations are not mixed in the time frame you assume, are methods based on drift.

Can you confirm whether the G25 distance run which shows Volga Ural folks such as Maris, Udmurts, etc. being genetically closer to Khanty, Mansi and Turkics/Central Asians such as Siberian Tatar, Uzbek, Turkmen, Karakalpak, etc. than to most Euros (with the exception of Finns, Finnic admixed Northern Russians and maybe Estonians), is accurate or not?

[Lemminkäinen]

I browsed the Khvorykh 2020. Komintasavalta how would you guess, would the Finns share slightly more IBDs with Yoruba than with Chimp. Your best guess without deeper analyses :)

[vbnetkhio]

Hey younster, allele distribution is a good method to find out admixtures, because admixing, based on alleles, doesn't destroy the history. IBD as a genomewide statistics reach only 1000 years. F.ex. Roll-Off analyses give seemongly roght results to 2ky, but practically not reliably. Everything that old-fashion geneticists have published using Roll-Off can be thrown to a your computer's recycle bin, among other similar IBD statistics. Dating and so also connected population are too vague. The best method, after you have determined using alleles whether your populations are not mixed in the time frame you assume, are methods based on drift.

could you list some professional drift measuring methods? most studies do just PCA, admixture, IBD, etc.

[Lemminkäinen]

Can you confirm whether the G25 distance run which shows Volga Ural folks such as Maris, Udmurts, etc. being genetically closer to Khanty, Mansi and Turkics/Central Asians such as Siberian Tatar, Uzbek, Turkmen, Karakalpak, etc. than to most Euros (with the exception of Finns, Finnic admixed Northern Russians), is accurate or not?

No. PCA is based on selected allelic components and the result depends on many selections made by the author, such as populations, population groups, population sizes etc. Of course the author sees that his choices are good, but how can I confirm it? Another question is that even in the case the g25 is excellent, the distances will never tell the history. What would you guess in a case of a half Chinese half Irish person, would he be closer Irish than you and me? Or would he be closer Chinese or Mongolian?

[Lemminkäinen]

could you list some professional drift measuring methods? most studies do just PCA, admixture, IBD, etc.

QpAdm, qpDstat, qp3Pop.

[Lemminkäinen]

Using haplotypes gives quite reliable results, with exception of Finestructure heat maps. Heat maps are vulnerable for the timing of selected populations. It doesn't make difference between roots and posterities. So mixed populations act like roots and are seen as equals with roots in generating bridges botween roots. The result is that for instance in case of three populations, South Sahara Africans, Europeans and Afro-Americans, SSA will get European admixture and Europe SSA admixture.

[Zanzibar]

So as an old-timer genetics pro, what other method do you recommend?

Table S1 of Khvorykh et al. 2020 contains a table for the number of shared IBD segments between populations (normalized to account for differences between sequencing protocols): https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7696950/.

The list below shows the normalized number of shared IBD fragments with Maris. The highest-ranking Central Asian population is Yaghnobi_Tajikistan (8.27), which comes before any Western European population:


$ curl https://pastebin.com/raw/4XZcCrpP|tr -d \\r>ibd
$ tp(){ awk '{for(i=1;i<=NF;i++)a[i][NR]=$i}END{for(i in a)for(j in a[i])printf"%s"(j==NR?"\n":FS),a[i][j]}' "FS=${1-$'\t'}";}
$ grep Maris ibd|cat <(sed -n 2p ibd) -|tp ,|sed 1,3d|head -n-4|awk -F, 'NR==FNR{a[$2]=$3" "$2" "$1;next}{print$2,a[$1]}' ibd -|sort -rn
54.71 Chuvashes_Russia Chu_EUR 3e
21.72 Mishar-Tatars Mis_EUR 1e
20.71 Tatars Tat_EUR 3e
20.07 Udmurds Udm_EUR 4e
16.56 Khantys Kha_SIB 7ev
15.2 Mansi:Russia Man_SIB 8sev
14.9 Kryashen-Tatars_Russia Kry_EUR 3e
14.67 Bashkirs_Russia BSh_EUR 5e
14.15 Saami:Finland Saa_EUR 5se
13.98 Latvians Lat_EUR 3e
13.43 Komis_Russia Kom_EUR 6ev
13.1 Mordvins_Russia Mor_EUR 3e
13.02 Vepsas_Russia Vep_EUR 6ev
12.57 Russian:Russia Rus_EUR 15sev
12.1 Ingrians_Russia_North Ing_EUR 3e
11.5 Nenets Nen_SIB 1v
11.44 Cossacks_Ukraine Cos_EUR 4e
11.27 Finnish:Finland Fin_EUR 6se
11.18 Karelians Kar_EUR 4ev
11.07 Tundra-Nenets Tun_SIB 3e
10.96 Polish:Poland Pol_EUR 5se
10.96 Estonian:Estonia Est_EUR 8se
10.78 Selkups_Russia Sel_SIB 3e
10.14 Forest-Nenets For_SIB 3e
9.9 Belarusians Bel_EUR 4e
9.53 Kets_Russia Ket_SIB 3e
9.47 Lithuanians Lit_EUR 3e
8.29 Moldavians Mol_EUR 2e
8.27 Yaghnobi_Tajikistan Yag_CAS 1e
8.25 Bulgarian:Bulgaria Bul_EUR 2s
8.22 Ukrainians Ukr_EUR 7e
8.19 Tlingit:Russia Tli_ARC 2s
8.16 Swedes_Sweden Swe_EUR 2e
8.1 Croats_Bosnia-Herzegovina Cro_EUR 4e
8.02 Finnish_in_Finland FIN_EUR 99
7.95 Hungarian:Hungary Hun_EUR 4se
7.92 Icelandic:Iceland Ice_EUR 2s
6.99 Utah_(CEPH)_NW_Eur_Ancestry CEU_EUR 91
6.99 British_in_England_and_Scotland GBR_EUR 88
6.38 English:England Eng_EUR 1s
6.38 Aleut:Russia Ale_ARC 2s
6.19 Orcadian:OrkneyIslands Orc_EUR 4s
6.13 Albanian:Albania Alb_EUR 4se
6.07 Rushan-Vanch_Tajikistan Rus_CAS 2e
6.07 French:France Fre_EUR 3s
5.82 Tubalar:Russia Tub_SIB 2s
5.53 Norwegian:Norway Nor_EUR 1s
5.48 Spanish:Spain Spa_EUR 2s
5.43 Greek:Greece Gre_EUR 2s
5.33 Chukchi:Russia Chu_ARC 6se
5.24 Kazakhs_Kazakhstan Kaz_CAS 3e
5.22 Denisova5 Alt_XXX 1
5.09 Avars_Russia_Caucaz Ava_CAU 3e
5.08 Loschbour Los_XXX 1
4.96 Tajiks Taj_CAS 3se
4.95 Chagyrskaya Cha_XXX 1
4.9 Ishkasim_Tajikistan Ish_CAS 2e
4.89 Balkars_Russia_Caucaz Bal_CAU 3e
4.74 Nganasans Nga_SIB 2e
4.71 Kabardins_Russia_Caucaz Kab_CAU 4e
4.64 Shor_Russia Sho_SIB 2e
4.6 Turkish:Turkey Tur_MDE 2s
4.49 Turkmens_Uzbekistan TKm_CAS 3e
4.46 Germans Ger_EUR 3e
4.39 Adygei:Russia(Caucasus) Ady_CAU 2s
4.35 Azerbaijanis Aze_MDE 3e
4.27 Iberian_Population_in_Spain IBS_EUR 107
4.25 Uzbek Uzb_CAS 3e
4.25 Lezgin:Russia Lez_CAU 6se
4.23 Basque:France Bas_EUR 2s
4.2 Burusho:Pakistan Bur_SAS 2s
4.18 Pathan:Pakistan Pat_SAS 2s
4.12 North_Ossetian:Russia NOc_CAU 4se
4.11 Shugnan_Tajikistan Shu_CAS 1e
4.1 Toscani_Italia TSI_EUR 106
4.06 Bergamo:Italy Ber_EUR 2s
3.93 Tabasarans_Russia_Caucaz Tab_CAU 3e
3.93 Altaian Alt_CAS 8sev
3.75 Circassians_Russia_Caucaz Cir_CAU 3e
3.63 Kumyks_Russia Kum_CAU 3e
3.62 Uygurs_Kazakhstan Uyg_CAS 3se
3.62 Georgian:Georgia Geo_CAU 4se
3.61 Oroqen:China Oro_EAS 2s
3.56 Kyrgyz:Kyrgyzystan Kyr_CAS 9se
3.51 Chechen:Russia Che_CAU 1s
3.37 Roma_Bosnia-Herzegovina Rom_EUR 3e
3.33 Kshatriya_India_ Ksh_SAS 1e
3.26 Abkhasian:Abkhazia Abk_CAU 5se
3.23 Puerto_Ricans_from_Puerto_Rico PUR_AMR 104
3.23 Crete:Greece Cre_EUR 2s
3.16 Tuscan:Italy Tus_EUR 2s
3.16 Makrani:Pakistan Mak_SAS 2s
3.16 Brahmin:India Bra_SAS 7se
3.14 BedouinB:Israel(Negev) Bed_MDE 2s
3.06 Sakha Sak_SIB 7e
3.05 Colombians_Medellin_Colombia CLM_AMR 93
3 Buryats Bur_SIB 18ev
2.92 Sindhi:Pakistan Sin_SAS 2s
2.9 Even:Russia Eve_SIB 12sev
2.88 Yakuts Yak_SIB 4sev
2.85 Hazara:Pakistan Haz_SAS 2s
2.8 Palestinian:Israel(Central) Pal_MDE 3s
2.8 Balochi:Pakistan Bal_SAS 2s
2.79 Shtuttgart Lbk_XXX 1
2.72 Itelman:Russia Ite_ARC 1s
2.68 Evenks EVk_SIB 14ev
2.67 Druze:Israel(Carmel) Dru_MDE 5se
2.62 Mongola:China Mon_EAS 8se
2.62 Kalash:Pakistan Kal_SAS 2s
2.6 Mexican_Ancestry_Los_Angeles MXL_AMR 58
2.59 Daur:China Dau_EAS 1s
2.58 Samaritan:Israel Sam_MDE 1s
2.54 Tuvinians Tuv_SIB 3e
2.54 Armenian:Armenia Arm_MDE 8se
2.33 Punjabi_Lahore_Pakistan PJL_SAS 88
2.08 Iranian:Iran Ira_MDE 8se
2.07 Maori:NewZealand Mao_OCE 1s
2.05 Hezhen:China Hez_EAS 2s
2.05 Assyrians_Armenia Ass_MDE 3e
1.99 Gupta_India Gup_SAS 1e
1.87 Ulchi:Russia Ulc_ARC 2s
1.85 Saharawi:WesternSahara(Morocco) Sah_AFR 2s
1.84 Gujarati_Indian_Houston_Texas GIH_SAS 98
1.79 Punjabi:Pakistan Pun_SAS 5se
1.76 Arabs-Israel Ara_MDE 5e
1.75 Koryaks Kor_ARC 16e
1.72 Relli:India Rel_SAS 2s
1.71 Eskimo_Sireniki:Russia Esk_ARC 9se
1.69 Sardinian:Italy Sar_EUR 3s
1.58 Jordanian:Jordan Jor_MDE 5se
1.55 Bengali:Bangladesh Ben_SAS 4se
1.52 Kol_India Kol_SAS 1e
1.51 Yemenite_Jew:Yemen Yem_MDE 2s
1.5 Kalmyk Kal_CAS 1v
1.49 Lebanese_Lebanon_ Leb_MDE 1e
1.43 Peruvians_Lima_Peru PEL_AMR 83
1.39 Kusunda:Nepal Kus_SAS 2s
1.34 Ustishim Ust_XXX 1
1.34 Mozabite:Algeria Moz_AFR 2s
1.29 Bengali_from_Bangladesh BEB_SAS 86
1.27 Tu:China TuX_EAS 2s
1.22 Marwadi_India Mar_SAS 1e
1.2 Saudi-Arabians Sau_MDE 2e
1.19 Indian_Telugu_from_the_UK ITU_SAS 102
1.11 Asur_India Asu_SAS 1e
1.07 Xibo:China Xib_EAS 2s
1.07 Kapu:India Kap_SAS 3se
1.07 Dhaka_Bangladesh_ Dha_SAS 3e
1.03 Sri_Lankan_Tamil_from_UK STU_SAS 101
1.02 DenisovaPinky Den_XXX 1
1.01 Madiga:India Mad_SAS 2s
0.9 Korean:Korea Kor_EAS 2s
0.85 Yi:China YiX_EAS 2s
0.85 Miao:China Mia_EAS 2s
0.81 Thakur_India Tha_SAS 1e
0.81 Americans_of_African_Ancestry_USA ASW_AFR 53
0.77 Kurmi_India Kur_SAS 1e
0.75 Madhya-Pradesh_India MAd_SAS 1e
0.72 Japanese:Japan Jap_EAS 3s
0.71 Tujia:China Tuj_EAS 2s
0.71 Naxi:China Nax_EAS 2s
0.68 Mala:India Mal_SAS 2s
0.67 Zapotec:Mexico Zap_AMR 2s
0.67 Burmese:Myanmar BUm_SAS 8e
0.63 Han_Chinese_Beijing CHB_EAS 103
0.61 Japanese_Tokyo JPT_EAS 104
0.55 Lahu:China Lah_EAS 2s
0.54 Burmese_Myanmar Bur_EAS 2s
0.51 Cambodian:Cambodia Cam_EAS 2s
0.46 African_Caribbeans_in_Barbados ACB_AFR 94
0.45 Piapoco:Colombia Pia_AMR 2s
0.45 Mayan:Mexico May_AMR 2s
0.41 Tamang_Nepal Tam_SAS 1e
0.39 Balija_India BAj_SAS 1e
0.38 Orissa_India Ori_SAS 1e
0.38 Colla_Argentina Col_AMR 4e
0.37 Santhal_India San_SAS 1e
0.36 She:China She_EAS 2s
0.35 Yadava:India Yad_SAS 2s
0.35 Thai:Thailand Tha_EAS 2s
0.35 Ho_India Ho_SAS 1e
0.34 Southern_Han_Chinese CHS_EAS 100
0.32 Khonda_Dora:India Kho_SAS 1s
0.31 Kinh_Ho_Chi_Minh_City_Vietnam KHV_EAS 98
0.29 Hawaiian:USA Haw_OCE 1s
0.27 Gambian:Gambia Gam_AFR 2s
0.26 Mixe:Mexico Mix_AMR 5s
0.25 Chinese_Dai_Xishuangbanna CDX_EAS 86
0.24 Somali:Kenya Som_AFR 1s
0.21 Aeta_Philippines Aet_OCE 3e
0.2 Vietnamese_central Vie_EAS 10e
0.2 Pima:Mexico Pim_AMR 2s
0.2 Luzon_Philippines Luz_OCE 2e
0.19 Vizayan_Philippines Viz_OCE 2e
0.18 Kinh:Vietnam Kin_EAS 2s
0.17 Dai:China Dai_EAS 4s
0.16 Irula:India Iru_SAS 2s
0.15 Quechua:Peru Que_AMR 3s
0.14 Karitiana:Brazil Kar_AMR 3s
0.12 Wichi_Argentina Wic_AMR 4e
0.12 Luhya:Kenya Luh_AFR 2s
0.12 Dusun:Brunei Dus_OCE 10se
0.11 Papuan:PapuaNewGuinea Pap_OCE 15s
0.11 Murut_Brunei Mur_OCE 8e
0.11 Masai:Kenya Mas_AFR 2s
0.11 Han:China Han_EAS 3s
0.11 Batak_Philippines Bat_OCE 3e
0.1 Luhya_in_Webuye_Kenya LWK_AFR 87
0.1 Ju_hoan_North:Namibia JuX_AFR 4s
0.07 BantuTswana:BotswanaOrNamibia Ban_AFR 6s
0.05 Gambian_in_Western_Divisions_Gambia GWD_AFR 110
0.04 Mende_in_Sierra_Leone MSL_AFR 73
0.03 Yoruba_in_Ibadan_Nigeria YRI_AFR 101
0.03 Esan_in_Nigeria ESN_AFR 92
0 Yoruba:Nigeria Yor_AFR 3s
0 Surui:Brazil Sur_AMR 2s
0 Mende:SierraLeone Men_AFR 2s
0 Mbuti:Congo Mbu_AFR 4s
0 Mandenka:Senegal Man_AFR 3s
0 Malayan_India MAy_SAS 1e
0 Luo:Kenya Luo_AFR 2s
0 Lebbo_Indonesia Leb_OCE 4e
0 Kosipe_Papua_New_Guinea Kos_OCE 3e
0 Koinanbe_Papua_New_Guinea Koi_OCE 3e
0 Khomani_San:SouthAfrica Kho_AFR 2s
0 Igorot:Philippines Igo_OCE 10se
0 Gond_India Gon_SAS 1e
0 Esan:Nigeria Esa_AFR 2s
0 Dinka:Sudan Din_AFR 3s
0 Congo-pygmies Con_AFR 3e
0 Chane:Argentina Cha_AMR 1s
0 Cachi_Argentina Cac_AMR 5e
0 Bougainville:PapuaNewGuinea Bou_OCE 2s
0 Biaka:CentralAfricanRepublic Bia_AFR 2s
0 Bajo_Indonesia Baj_OCE 4e
0 Australian:Australia Aus_OCE 2s
0 Atayal:Taiwan Ata_EAS 1s
0 Ami:Taiwan Ami_EAS 2s
0 Agta_Philippines Agt_OCE 3e

Hey is it ok if I post some of the FST tables and PCA datas you made on genetic forums/blogs like Anthrogenica or Eurogenes? There seems to be some genetic experts there and I want to ask them more about the genetic distances between VURers and their neighbors.

[Komintasavalta]

Hey is it ok if I post some of the FST tables and PCA datas you made on genetic forums/blogs like Anthrogenica or Eurogenes? There seems to be some genetic experts there and I want to ask them more about the genetic distances between VURers and their neighbors.

No, because some members of the Finnish anthroforum are on AG, and I don't want them to know that I post here.

The Finnish forum is mostly dead, but it's an even higher-quality forum than AG, and in 9 out of 10 alternative universes I probably ended posting there or on AG and not here.

[Zanzibar]

No, because some members of the Finnish anthroforum are on AG, and I don't want them to know that I post here.

The Finnish forum is mostly dead, but it's an even higher-quality forum than AG, and in 9 out of 10 alternative universes I probably ended posting there or on AG and not here.

Why don't you want them to know that you posted here?

Eurogenes blog doesn't seem to have Finnish forum members though unlike AG.

[XenophobicPrussian]

You asked me to comment on this thread twice so I'll comment, I don't really know what you want me to say though lol.

Not really surprising at all? You're acting like all these populations(West Siberians, Uzbeks, Hazaras, etc) are on the other side of the continent, these are all extremely intermediary(both geographically and genetically) and mixed populations. There's literally a fully Corded Ware/East Ukrainian clustering Andronovo sample in Tajikistan dated to 1200 BC, there's dozens of fully Yamnaya clustering samples as far east as the Bronze Age Altai, that shows you what with and how these people are an admixture of many different things. You're treating it like as soon as you leave the geographic boundary of Europe you encounter a a hard wall and a completely different race from the side you just left. That's not how it works. I'd be surprised if they wind up being closer to a population like Oroqen, Evenks, Han Chinese, Nganasan, etc, not people a few hundred KMs away in Central Asia or West Siberia. Do you also think Siberian Tatars are completely unrelated to VUR Tatars? The only thing that surprises me a little is the Saami(guessing it's Finnish or Kola Saami), as they along with Nenets have the least southern Eurasian admixture in West Eurasia(but still present in Saami), while it's plentiful in Central Asia, but I guess the Mongoloid link is just that strong. Keep in mind while G25 is great and a very useful tool it isn't the end be it all in every case, most PCAs I see definitely don't have Chuvash, Mari, Tatars closer to Hazara(the most surprising of them all, but still really surprising, Mansi/Khanti, Kazakh, Siberian Tatar is not surprising at all) than to say, Smolensk Russians, but they're still around the middle point anyway so it doesn't matter either way.

Weird thread, if you want to try an interesting comparison, I'd be curious to see whether Nenets are closer to Irish or Ulchi/Oroqen/Manchurian Evenks. Would also be interesting in seeing the same thing for Mansi/Khanty instead of Nenets, and also replacing Irish with Basque for both.

[Zanzibar]

You asked me to comment on this thread twice so I'll comment, I don't really know what you want me to say though lol.

Not really surprising at all? You're acting like all these populations(West Siberians, Uzbeks, Hazaras, etc) are on the other side of the continent, these are all extremely intermediary(both geographically and genetically) and mixed populations. There's literally a fully Corded Ware/East Ukrainian clustering Andronovo sample in Tajikistan dated to 1200 BC, there's dozens of fully Yamnaya clustering samples as far east as the Bronze Age Altai, that shows you what with and how these people are an admixture of many different things. You're treating it like as soon as you leave the geographic boundary of Europe you encounter a a hard wall and a completely different race from the side you just left. That's not how it works. I'd be surprised if they wind up being closer to a population like Oroqen, Evenks, Han Chinese, Nganasan, etc, not people a few hundred KMs away in Central Asia or West Siberia. Do you also think Siberian Tatars are completely unrelated to VUR Tatars? The only thing that surprises me a little is the Saami(guessing it's Finnish or Kola Saami), as they along with Nenets have the least southern Eurasian admixture in West Eurasia(but still present in Saami), while it's plentiful in Central Asia, but I guess the Mongoloid link is just that strong. Keep in mind while G25 is great and a very useful tool it isn't the end be it all in every case, most PCAs I see definitely don't have Chuvash, Mari, Tatars closer to Hazara(the most surprising of them all, but still really surprising, Mansi/Khanti, Kazakh, Siberian Tatar is not surprising at all) than to say, Smolensk Russians, but they're still around the middle point anyway so it doesn't matter either way.

Weird thread, if you want to try an interesting comparison, I'd be curious to see whether Nenets are closer to Irish or Ulchi/Oroqen/Manchurian Evenks. Would also be interesting in seeing the same thing for Mansi/Khanty instead of Nenets, and also replacing Irish with Basque for both.

I see your point. Sorry you can you elaborate more on how the Corded Ware clustering Andronovo sample and Yamnaya clustering samples have to do this subject? Well those are pure Mongoloids, so I’m not certain. Well Siberian Tatars (also the Zabolotniye individuals which seems to be predominantly Khanty-like), seem much more Mongoloid than VUR Tatars so I thought they would be distantly related. The Saamis are not Kola Saamis, I think the samples are either from Norway or Finland. Kola Saamis are labelled as Saami_Kola in G25, they seem much less Mong and have more Euro than the Saami. You are a little surprised about the Saamis by how they are closer to some Central Asians e.g. Uzbeks, Turkmens, Pamiris than to mainstream Euros considering how they have the lowest southern Eurasian admixture in West Eurasia? (along with Nenets you mentioned) By southern Eurasian admixture, are you referring to Neolithic Farmer ancestry (Anatolian, Iranian, Natufian)? You mean the Mongoloid links with Central Asians and Turkics?

By Tatars, you are referring to Volga Tatars and not Lipka or Crimean Tatars? Why do you find them being closer to Hazara to be the most surprising than Kazakhs?
Well could it be that the Hazara have a lot of drift make them farther away from these Volga Ural folks in most PCAs or that the VURer samples in those PCAs are less Mongoloid than the ones in G25? I noticed this likely drift phenomenon also happens to Mansi and Saami in some FST Udmurt distance to other pops:


[quoting=Komintasavalta]:

FST distance to Udmurt:
.0000 Udmurt
.0064 Besermyan
.0096 Tatar_Kazan
.0099 Bashkir
.0120 Chuvash
.0146 Tatar_Mishar
.0148 Nogai_Karachay_Cherkessia
.0150 Tatar_Siberian
.0158 Uzbek
.0160 Russian_Archangelsk_Krasnoborsky
.0168 Tajik
.0174 Nogai_Stavropol
.0179 Russian
.0181 Turkmen
.0187 Russian_Archangelsk_Pinezhsky
.0188 Finnish
.0196 Russian_Archangelsk_Leshukonsky
.0196 Karelian
.0196 Uyghur.DG
.0207 Estonian
.0209 Hungarian
.0217 Uyghur
.0218 Karakalpak
.0221 Nogai_Astrakhan
.0221 Circassian
.0229 English
.0231 Norwegian
.0236 Icelandic
.0237 Romanian
.0242 Mansi
.0247 Azeri
.0261 Iranian
.0264 Italian_North
.0277 Kazakh
.0286 Tatar_Siberian_Zabolotniye
.0288 Canary_Islander
.0300 Kyrgyz_Tajikistan
.0314 Lebanese
.0321 Saami.DG
.0323 Khakass
.0359 Yemeni
.0370 Altaian_Chelkan
.0385 Tubalar
.0391 Altaian
.0398 Shor_Mountain
.0422 Khakass_Kachin
.0428 Saudi
.0434 Moroccan
.0508 Mongol
.0511 Ket
.0513 Shor_Khakassia
.0577 Enets
.0688 Xibo
.0726 Tibetan
.0795 Han
[/quote]


When actually Saami, Mansi are a lot closer to Udmurt when using G25.

Also I think it depends on the particular VUR group and how much Mongoloid ancestry they have. For example, random Udmurt, Mari and Saami individuals: Hazaras are closer to them than most Euros.

Distance to: Udmurt:udmurd8

0.09484060 Bashkir
0.09771282 Scythian_Aldy_Bel_IA
0.11499101 Tatar_Siberian
0.12768661 Turkmen
0.13030726 Tatar_Siberian_Zabolotniye
0.13430221 Yukagir_Forest
0.14008865 Uzbek
0.14366467 Tajik
0.15051991 Mansi
0.15262305 Tajik_Rushan
0.15324316 RUS_Okunevo_BA
0.16433979 Khanty
0.16542659 KAZ_Karluk
0.16977493 Hazara_Afghanistan
0.17278467 KAZ_Karakhanid
0.17317202 Nogai
0.17470455 Uygur
0.17473450 Kho_Singanali
0.17977632 Hazara
0.18039907 Ket
0.18132893 Jatt_Pathak
0.18183389 Turkish_Southwest
0.18257704 Turkish_South
0.18263746 Russian_Tver
0.18291728 Karakalpak
0.18364497 Ror
0.18498196 KAZ_Nomad_MA
0.18557709 Burusho
0.18871031 Russian_Kursk
0.19037902 Turkish_North
0.19204759 Russian_Orel
0.19219383 Cossack_Ukrainian
0.19378021 Tubalar
0.19442719 Kabardin
0.19543075 Russian_Voronez
0.19648754 Ukrainian_B
0.19764225 Circassian
0.19809225 Ukrainian
0.20046634 Russian_Smolensk
0.20124156 Norwegian
0.20161450 Hungarian
0.20286088 Slovakian
0.20302204 Polish
0.20469775 Shor_Mountain
0.20477301 Dutch
0.20680134 Icelandic
0.20759156 Austrian
0.20766697 Shor_Khakassia
0.20993455 Shor
0.21127078 English
0.21358828 Kazakh
0.23881898 Italian_Lombardy


Compare to the Udmurt average:


Distance to: Udmurt_2
0.10529147 Bashkir
0.10776394 Scythian_Aldy_Bel_IA
0.12570744 Tatar_Siberian
0.13012243 Turkmen
0.14020414 Tajik
0.14270176 Tatar_Siberian_Zabolotniye
0.14451872 Yukagir_Forest
0.14584274 Tajik_Rushan
0.14672097 Uzbek
0.16164175 RUS_Okunevo_BA
0.16244942 Mansi
0.16970121 Russian_Tver
0.17172944 Kho_Singanali
0.17493170 KAZ_Karluk
0.17549334 Russian_Kursk
0.17670935 Khanty
0.17741680 Jatt_Pathak
0.17742818 Turkish_Southwest
0.17835797 Hazara_Afghanistan
0.17871420 Turkish_South
0.17915104 Russian_Orel
0.17971089 Cossack_Ukrainian
0.17996473 Ror
0.18265498 Russian_Voronez
0.18280223 Nogai
0.18325387 KAZ_Karakhanid
0.18332786 Uygur
0.18432099 Ukrainian_B
0.18541838 Ukrainian
0.18585491 Burusho
0.18612404 Turkish_North
0.18804380 Russian_Smolensk
0.18824965 Kabardin
0.18876647 Hazara
0.19024708 Slovakian
0.19052536 Polish
0.19056548 Hungarian
0.19064075 Norwegian
0.19133053 Circassian
0.19256780 Ket
0.19300535 Karakalpak
0.19404171 Dutch
0.19575177 KAZ_Nomad_MA
0.19594646 Icelandic
0.19672721 Austrian
0.20091902 English
0.20436921 Tubalar
0.21594344 Shor_Mountain
0.21890788 Shor_Khakassia
0.22136420 Shor
0.22406232 Kazakh
0.23114484 Italian_Lombardy


Random Mari sample:

Distance to: Mari:mari1

0.11855441 Bashkir
0.12378893 Scythian_Aldy_Bel_IA
0.13218886 Tatar_Siberian
0.13714602 Tatar_Siberian_Zabolotniye
0.14681540 Yukagir_Forest
0.14953210 Mansi
0.16383451 Khanty
0.16693582 Turkmen
0.16971483 Uzbek
0.17622167 RUS_Okunevo_BA
0.18445121 Nogai
0.18648667 KAZ_Karluk
0.18954934 KAZ_Karakhanid
0.19130795 Tajik
0.19206068 Hazara_Afghanistan
0.19288253 Ket
0.19424480 Karakalpak
0.19471678 Uygur
0.19608198 KAZ_Nomad_MA
0.19885824 Hazara
0.20214528 Tajik_Rushan
0.20393972 Tubalar
0.21346326 Shor_Mountain
0.21750915 Shor_Khakassia
0.21771129 Shor
0.21774718 Russian_Tver
0.22030140 Kazakh
0.22037648 Kho_Singanali
0.22170558 Turkish_Southwest
0.22267565 Turkish_South
0.22286204 Russian_Kursk
0.22559406 Burusho
0.22623169 Russian_Orel
0.22638171 Jatt_Pathak
0.22698380 Cossack_Ukrainian
0.22792117 Russian_Voronez
0.22802434 Ror
0.22879830 Turkish_North
0.22917318 Ukrainian_B
0.23218075 Ukrainian
0.23248012 Russian_Smolensk
0.23515740 Kabardin
0.23707678 Polish
0.23742470 Circassian
0.23795651 Hungarian
0.23884078 Slovakian
0.24051828 Norwegian
0.24317177 Dutch
0.24453596 Austrian
0.24458502 Icelandic
0.24910385 English
0.27362461 Italian_Lombardy


Average Mari:

Distance to: Mari
0.12468470 Bashkir
0.13081854 Scythian_Aldy_Bel_IA
0.13857526 Tatar_Siberian
0.14622919 Tatar_Siberian_Zabolotniye
0.15247870 Yukagir_Forest
0.15879922 Mansi
0.16609517 Turkmen
0.17229907 Uzbek
0.17348576 Khanty
0.18349037 RUS_Okunevo_BA
0.18790293 Tajik
0.19024225 Nogai
0.19185233 KAZ_Karluk
0.19571190 KAZ_Karakhanid
0.19586713 Hazara_Afghanistan
0.19748239 Tajik_Rushan
0.19923069 Uygur
0.20034154 Karakalpak
0.20267386 Ket
0.20295654 KAZ_Nomad_MA
0.20344348 Hazara
0.21081083 Russian_Tver
0.21182997 Tubalar
0.21549021 Russian_Kursk
0.21622425 Turkish_Southwest
0.21650129 Kho_Singanali
0.21768552 Turkish_South
0.21906474 Russian_Orel
0.21984970 Cossack_Ukrainian
0.22059257 Russian_Voronez
0.22160807 Ukrainian_B
0.22192787 Shor_Mountain
0.22200313 Jatt_Pathak
0.22317863 Burusho
0.22346587 Ror
0.22396805 Turkish_North
0.22486058 Ukrainian
0.22557314 Russian_Smolensk
0.22617737 Shor_Khakassia
0.22640049 Shor
0.22718034 Kazakh
0.22981453 Polish
0.23075128 Kabardin
0.23081106 Hungarian
0.23101851 Slovakian
0.23297099 Circassian
0.23388498 Norwegian
0.23635703 Dutch
0.23732089 Austrian
0.23796045 Icelandic
0.24241418 English
0.26721612 Italian_Lombardy


A random Saami individual:

Distance to: Saami:saami2
0.10611550 Scythian_Aldy_Bel_IA
0.10863329 Bashkir
0.12327083 Yukagir_Forest
0.12433077 Tatar_Siberian
0.13276869 Tatar_Siberian_Zabolotniye
0.15131717 Mansi
0.15442980 RUS_Okunevo_BA
0.16441909 Khanty
0.16464982 Turkmen
0.16634323 Uzbek
0.17639320 Ket
0.18152610 Nogai
0.18208172 KAZ_Karluk
0.18489029 Tajik
0.18551841 KAZ_Karakhanid
0.18752219 Russian_Tver
0.19066948 Hazara_Afghanistan
0.19091067 Karakalpak
0.19160642 Tajik_Rushan
0.19209819 KAZ_Nomad_MA
0.19294976 Uygur
0.19451723 Tubalar
0.19539126 Russian_Kursk
0.19782409 Cossack_Ukrainian
0.19811217 Hazara
0.19838505 Russian_Orel
0.20084988 Russian_Voronez
0.20440860 Ukrainian_B
0.20458057 Russian_Smolensk
0.20524660 Ukrainian
0.20557912 Shor_Mountain
0.20770330 Shor_Khakassia
0.20962900 Shor
0.20964550 Polish
0.21052913 Norwegian
0.21249220 Slovakian
0.21404769 Kho_Singanali
0.21421140 Hungarian
0.21480380 Icelandic
0.21529964 Dutch
0.21756288 Jatt_Pathak
0.21783864 Turkish_Southwest
0.21796627 Kazakh
0.21957202 Turkish_South
0.21980440 Ror
0.22066355 Austrian
0.22165108 English
0.22292527 Burusho
0.22679866 Turkish_North
0.22919164 Kabardin
0.23269938 Circassian
0.25848855 Italian_Lombardy


Compare to average Saami:

Distance to: Saami

0.12448608 Bashkir
0.12601793 Scythian_Aldy_Bel_IA
0.14160670 Yukagir_Forest
0.14216068 Tatar_Siberian
0.15607780 Tatar_Siberian_Zabolotniye
0.16075159 Russian_Tver
0.16336793 Turkmen
0.16900683 Russian_Kursk
0.17240465 Cossack_Ukrainian
0.17255108 Russian_Orel
0.17367742 Uzbek
0.17400811 Mansi
0.17518874 Russian_Voronez
0.17553305 Tajik
0.17599624 RUS_Okunevo_BA
0.17822236 Tajik_Rushan
0.17884364 Ukrainian_B
0.17927329 Ukrainian
0.17952044 Russian_Smolensk
0.18381285 Polish
0.18547941 Slovakian
0.18560255 Norwegian
0.18848438 Khanty
0.18949914 Hungarian
0.19039592 Icelandic
0.19087737 Dutch
0.19604462 Austrian
0.19640213 Nogai
0.19695641 KAZ_Karluk
0.19782542 English
0.20060210 Ket
0.20194140 Hazara_Afghanistan
0.20239142 KAZ_Karakhanid
0.20361165 Turkish_Southwest
0.20432707 Uygur
0.20693335 Turkish_South
0.20699293 Kho_Singanali
0.20735551 Karakalpak
0.20854188 Jatt_Pathak
0.21075794 KAZ_Nomad_MA
0.21102027 Hazara
0.21116963 Ror
0.21361686 Turkish_North
0.21499635 Kabardin
0.21653079 Tubalar
0.21869659 Circassian
0.22034786 Burusho
0.22888814 Shor_Mountain
0.23134900 Shor_Khakassia
0.23286304 Shor
0.23581486 Kazakh
0.23812838 Italian_Lombardy

I will conduct the Nenets or Khanty/Mansi distance runs whether they are closer to one of the aforementioned groups than the others.

[Cristiano viejo]

Mongols are Mongols. Of course they are closer to Turkics than to Europeans.
The only European thing in them is their yoke.

[Komintasavalta]

Weird thread, if you want to try an interesting comparison, I'd be curious to see whether Nenets are closer to Irish or Ulchi/Oroqen/Manchurian Evenks. Would also be interesting in seeing the same thing for Mansi/Khanty instead of Nenets, and also replacing Irish with Basque for both.

Based on FST distances between populations in the 1240K+HO dataset, Mansi are closer to Oroqens than to the English. There were no Nenets or Irish samples, but Enetses and Selkups are both much closer to Ulchis and Oroqens than to the English. Ulchis are a more drifted population than Han, so they're further from Europeans than Han are.

https://i.ibb.co/vHZHXSW/fst.jpg

[Zanzibar]

Based on FST distances between populations in the 1240K+HO dataset, Mansi are closer to Oroqens than to the English. There were no Nenets or Irish samples, but Enetses and Selkups are both much closer to Ulchis and Oroqens than to the English. Ulchis are a more drifted population than Han, so they're further from Europeans than Han are.

https://i.ibb.co/vHZHXSW/fst.jpg

Mansi seem to have a lot of drift. Because according to G25, Udmurts are genetically closer to Mansi than they are to English, Ukrainian and Russian. The Russian sample probably have a lot of Finno-Ugric ancestry it seems. Heck, even many Udmurts on G25 were genetically closer to Hazaras than to mainstream Euros.

[Leto]

There's literally a fully Corded Ware/East Ukrainian clustering Andronovo sample in Tajikistan dated to 1200 BC
Ca. 1500 BC. It's Dashti_Kozy I4258, from Penjikent, Tajikistan.

Gedrosia 19.12 Pct
Siberian 0.7 Pct
Northwest_African -
Southeast_Asian -
Atlantic_Med 17.01 Pct
North_European 52.07 Pct
South_Asian 1.83 Pct
East_African 0.92 Pct
Southwest_Asian -
East_Asian -
Caucasus 7.6 Pct
Sub_Saharan 0.75 Pct

An unmixed Aryan and indeed almost identical to some of his/her contemporaries in Poland and Czechia.