Hun, Avar and conquering Hungarian results [Vahaduo K13]

[Lucas]

Y-chromosome haplogroups from Hun, Avar and conquering Hungarian period nomadic people of the Carpathian Basin

https://www.nature.com/articles/s41598-019-53105-5

But autosomal snps we have too.



Hun period



HUNper3_GE_S8_R1_001,23.42,24.22,6.14,19.72,14.36, 2.32,0,0,5.07,3,0,1.77,0
HUNper2_GE_S15_R1_001,24.84,21.48,0,14.54,4.76,20. 88,1.6,4.85,0,0,7.05,0,0
HUNper1_GE_S32_R1_001,18.04,19.81,9.43,26.32,0.5,0 ,3.83,0.7,6.58,8.89,2.02,3.88,0



early Avar



Filename,North_Atlantic,Baltic,West_Med,West_Asian ,East_Med,Red_Sea,South_Asian,East_Asian,Siberian, Amerindian,Oceanian,Northeast_African,Sub-Saharan
DKper701_GE_S1_R1_001,35.93,33.66,10.87,7.62,0,0,0 ,0,0,0,4.68,4.91,2.32
FGDper4_GE_S4_R1_001,6.64,21.46,0,10.06,0,7.52,0,1 3.81,39.29,1.22,0,0,0
KBper300_GE_S5_R1_001,0,24.79,15.39,23.92,2.51,13. 21,0,3.33,6.89,8.73,1.23,0,0
KFPper6_GE_S2_R1_001,17.39,32.15,16.82,2.12,0,3.98 ,5.52,0,12.09,1.81,0,0,8.13
KFPper31_GE_S3_R1_001,22.38,5.76,13.58,9.82,24.43, 0.22,4.86,0,10.18,2.87,5.9,0,0
MMper58_GE_S30_R1_001,22.52,26.96,0,26.53,0,0,3.26 ,0,15.71,0,5.01,0,0
MMper227_GE_S31_R1_001,25.6,14.57,14.43,14.78,11.6 ,12.8,0,2.82,0,0,3.41,0,0
PSZper1_GE_S33_R1_001,30.32,11.98,10.99,0,25.84,1. 81,0,0,0,16.1,2.96,0,0
SzKper51_GE_S27_R1_001,0.16,41.6,4.24,14.76,7.7,11 .82,5.89,0,12.56,0,1.26,0,0
SzOper81_GE_S25_R1_001,33.38,0,0,3.02,35.99,6.5,8. 45,0,7.4,5.26,0,0,0
SzOper540_GE_S26_R1_001,7.94,8.9,0,26.58,6.84,4.31 ,0,5.27,28.78,4.17,0,0,7.2



late avar


KVper3369_GE_S6_R1_001,13.84,39.6,6.53,0,11.51,0,1 5.71,0,12.41,0,0.4,0,0
PVper72_GE_S29_R1_001,16.35,54.48,16.33,0,0,0,0,0, 2.35,2.75,0,7.74,0
SzKper239_GE_S28_R1_001,26.98,3.86,20.85,15.36,27. 13,3.71,0,0,0,2.11,0,0,0


Conqueror


KVper3369_GE_S6_R1_001,13.84,39.6,6.53,0,11.51,0,1 5.71,0,12.41,0,0.4,0,0
PVper72_GE_S29_R1_001,16.35,54.48,16.33,0,0,0,0,0, 2.35,2.75,0,7.74,0
SzKper239_GE_S28_R1_001,26.98,3.86,20.85,15.36,27. 13,3.71,0,0,0,2.11,0,0,0
K1per1_GE_S4_L001_R1_001,0,16.29,9.22,17.08,20.75, 15.05,0,8.25,13.37,0,0,0,0
K1per10_GE_S5_L001_R1_001,55.97,0,2.76,0,0,19.73,0 .05,1.38,5.89,0,0,4.51,9.71
K1per13_GE_S21_R1_001,34.51,39.29,17.18,0,5.67,0,0 ,0.3,0,1.1,0,1.96,0
K1per1438_GE_S17_R1_001,0,38.41,5.3,0,43.25,3.95,0 ,0,0,7.46,0,0,1.63
K1per3286_GE_S14_R1_001_merged,44.22,0,0.88,0,0,9. 66,14.43,13.53,11.48,1.69,0,4.11,0
K2per6_GE_S16_R1_001,32.41,22.71,13.93,12.73,7.57, 6.16,0,0,0,1.61,2.88,0,0
K2per16_GE_S7_L001_R1_001,29.21,0,7.81,23.48,6.21, 0,33.28,0,0,0,0,0,0
K2per18_GE_S13_R1_001,22.01,4.14,28.75,0,19.55,0,1 2.05,0,0.87,12.62,0,0,0
K2per26_GE_S9_R1_001,31,9.44,1.46,6.44,43.89,0,0,0 .16,0,6.18,0,0.3,1.12
K2per29_GE_S10_L001_R1_001,20.37,27.54,0,0,29.94,1 .66,12.21,0,6.49,0,1.78,0,0
K2per33_GE_S2_L001_R1_001,0,57.17,26.7,4.35,0,0,0, 0,0,0.52,0,11.27,0
K2per36_GE_S19_R1_001,21.58,10.21,15.63,0,26.73,3. 99,14.44,1.06,0,6.36,0,0,0
K2per41_GE_S20_R1_001,36.05,17.4,19.1,13,7.63,0,3. 53,0,0.92,0.71,1.65,0,0
K2per51_GE_S7_R1_001,0,0,18.36,0,0,0,34.17,0,41.39 ,0,1.38,4.7,0
K2per52_GE_S1_R1_001_merged,15.26,25.34,0,36.13,15 .71,0,0,2.07,0,0,2.08,1.53,1.88
K2per61_GE_S9_L001_R1_001,36.61,0,15.16,12.12,4.48 ,6.9,0,6.33,15.02,3.38,0,0,0
K3per1_GE_S18_R1_001,0,56.04,0,15.59,13.08,0,2.93, 1.26,11.11,0,0,0,0
K3per3_GE_S6_R1_001,28.09,39.83,2.38,0,10.71,0,0,0 ,0,0.11,13.04,5.83,0
K3per6_GE_S10_R1_001,2.84,41.57,0,0,0,0,8.79,0,28. 31,0,0,18.48,0
K3per12_GE_S3_L001_R1_001,30.28,18.34,0,23.78,0,0, 7.88,0,0,18.52,1.22,0,0
K3per13_GE_S2_R1_001,17.8,27.15,13.49,16.04,0,3.75 ,0,5.32,13.01,3.45,0,0,0
KeF2per2_GE_S3_R1_001_merged,35.53,21.81,4.94,13.2 5,7.78,0.7,4.24,2.3,8.73,0.3,0.42,0,0
KeF2per3_GE_S2_R1_001,41.39,13.37,0,22.88,6.79,2.9 4,2.65,0,5.54,4.44,0,0,0
KeF2per14_GE_S8_R1_001,28.27,0,0,6.06,0,0,23.76,0, 29.81,5.46,0,6.63,0
KeF2per15_GE_S5_R1_001,0,37.8,0,10.53,0,0.55,7.68, 3.02,35.12,4.92,0,0,0.37
KVper3450_GE_S7_R1_001,24.65,31.05,19.4,0,8.65,1.3 1,0,1.88,5.84,7.21,0,0,0
MHper9_GE_S10_R1_001_merged,4.83,26.25,0,10.23,28. 9,0,0,20.37,2.27,5.18,0.58,0,1.39
MHper15_GE_S11_R1_001,21.81,31.68,1.44,20.68,8.08, 0,0,5.55,0,5.88,0,4.87,0
MHper16_GE_S12_R1_001,29.6,34.56,6.32,21.36,0,0,0, 0,0.65,7.51,0,0,0
SHper2_GE_S3_R1_001,22.16,31.94,20.91,18.19,0,0,0, 0,0,3.02,3.77,0,0
SHper3_GE_S4_R1_001,7.06,18.58,14.39,0,12.64,16.6, 0,0,23.82,4.42,2.48,0,0
SHper15_GE_S1_R1_001,37.47,33.81,0,0,0,9.6,0,10.63 ,0,0,4.1,2.99,1.4

[Lucas]

Generally very poor quality. I will upload samples to Google Drive later.

[andre]

Generally very poor quality. I will upload samples to Google Drive later.

How many many snps?

[Lucas]

How many many snps?

You will see when I upload.

[Altaylı]

nice stuff:thumb001:

[andre]

You will see when I upload.

Ok boss

[Leto]

What's the East Eurasian/Mongoloid range for the conquerors?

[Lucas]

Ok boss

https://drive.google.com/file/d/1vXzjzt60zr6EvKsXD19kz6a9dAxr3rSn/view?usp=sharing

[Lucas]

What's the East Eurasian/Mongoloid range for the conquerors?

Check, it is in first post:)

[bained]

Oh no, 4 of them have Bulgarian as top distance.

[Leto]

Check, it is in first post:)
There was no range in the OP, so I had to calculate it myself. The average is

2.24 East_Asian
8.33 Siberian
3.20 Amerindian

East_Asian varies from zero to 20.37%
Siberian varies from zero to 41.39%
Amerindian varies from zero to 18.42%

But a third of them are basically full Europeans, nothing Altaic/Uralic about 'em.

[andre]

Based on this k13 coordinates, in ca 900 AD, around 50% had roman-like ancestry, 45% nomadic (uralic,altaic and iranic/caucasian), 30% slavic and 20% germanic.

We can see roman+Slavic mix, Germanic+Roman, Roman+Nomadic etc.. a lot of mixtures of course.

[Mejgusu]

Very interesting results, so it seems there was a big diversity. There are even some very southern samples. Some look already mixed(clustering with Balkan Turks), some are more Ugric shifted, but some are clearly Central Asian shifted. But overwhelming majority was basically Central/North/East European.

[Kaspias]

Almost no proper samples over here, snp numbers must be very low. However, based on these results one can say that samples include Europeans(Italian/Greek-like, German-like, Slav-like) and Eurasians who has a varying amount of East Eurasian in the line of Altay. Also, some turn out be to be mixed already.

Early Avar and Hun period samples seem to have the Turkic characteristic even though a great majority of them mixed. In addition, Early Avar samples are also including European-like individuals. Late Avar samples include one Eastern Mediterranean, one in the same parallel with Early Avars, and one in the same parallel with the Ugric group of Conquerors. Conquerors, on the other hand, have great diversity and include European groups densely. Samples that have Eastern Eurasian occasionally come out as mixed with European groups. To point out, 4 samples are Ugric-like, 12 samples are in the Turkic cluster, 12 samples in the European cluster, 9 samples are mixed in between Turkic and European. In this sense, populations who are mainly Western Eurasian but also having Eastern Eurasian admixture as well show up as the closest proxies.


https://i.ibb.co/YZsFHYg/m.png

[Jana]

One of the conquerors is closest to Balkan Gypsies (with gigantic distance though), but in mixed mode it obviously has big south Asian admixture.

Target: K2per16_GE_S7_L001_R1_001
Distance: 10.6423% / 10.64231256 | ADC: 0.25x RC

41.4 Sindhi
27.8 French_Basque
18.0 Velamas
12.8 Irish_Ulster

So that could mean what we already speculated, some south Asian arrived from steppe and that's why Volga-Ural populations score minor south Asian too (central Asians score it too ofc but that we already know)

[Jana]

Some other samples have Chamar like DNA too.

[bained]

Target: K2per52_GE_S1_R1_001_merged
Distance: 6.5768% / 6.57681633 | ADC: 0.25x RC
68.9 Lezgin
27.0 Ukrainian_Belgorod
2.6 Lebanese_Druze
1.5 Sandawe


Imagine not having the same Y-haploshit and mtDNA as the glorious leader.


"The Karos samples’ STR data are 1 genetic distance on 17 loci in the Balkans to a Bulgarian from Montana and 2 mutation steps to a Bulgarian from Sofia, a Bulgarian from Plovdiv, and a Tuscan Albanian (see Fig. 7)."

https://link.springer.com/article/10.1007/s12520-019-00996-0

[Leto]

One of the conquerors is closest to Balkan Gypsies (with gigantic distance though), but in mixed mode it obviously has big south Asian admixture.

Target: K2per16_GE_S7_L001_R1_001
Distance: 10.6423% / 10.64231256 | ADC: 0.25x RC

41.4 Sindhi
27.8 French_Basque
18.0 Velamas
12.8 Irish_Ulster

So that could mean what we already speculated, some south Asian arrived from steppe and that's why Volga-Ural populations score minor south Asian too (central Asians score it too ofc but that we already know)
What South Asian? A full-blown Indian? The South Asian in modern Central Asians is BMAC, maybe unless it's deep Afghanistan.

[cakmir7y]

Just for fun, Ive checked those data against me.

Distance to: cakmir7y(czech)
8.02718506 K1per13_GE_S21_R1_001
13.10847436 DKper701_GE_S1_R1_001
14.34024058 KVper3450_GE_S7_R1_001
17.15278986 K2per6_GE_S16_R1_001
19.71218151 K3per3_GE_S6_R1_001
20.94599007 SHper2_GE_S3_R1_001
21.26221531 MHper16_GE_S12_R1_001
22.07166056 KeF2per2_GE_S3_R1_001_merged
22.60834802 SHper15_GE_S1_R1_001
22.90684396 K2per41_GE_S20_R1_001

This K1per13_GE_S21_R1_001 conqueror is one of the two of the whole dataset with E-V13 YDNA.


The same sample using updated K13 on vahaduo. I find it pretty interesting that one of the 9/10th century
Hungarian conquerors is closest to the modern Czechs.

Distance to: K1per13_GE_S21_R1_001
8.44624177 Czech
8.97092526 Sorb_Lusatia
9.18524904 German_East
9.32349184 Slovak
9.93049848 Polish_Masuria
10.18789969 Slovenian
10.46708651 South_Polish
10.62888517 Hungarian_North
11.27571727 Croat_North
11.33444749 Ukrainian_Galicia
11.78513046 Polish
11.87415260 Polish_Kielce
12.02045756 Hungarian_Transdanubia+Budapest
12.31556738 Hungarian
12.51479524 Ukrainian_Carpathian
12.52525848 Hungarian_Alföld
12.99195135 Moldova_Ukrainian
13.01068791 Austrian
13.74664686 Southwest_Finnish
13.81222285 Croat
13.84139444 Ukrainian
14.48467466 Croat_East
14.87906247 Croat_West
15.05897407 Bosniak_Bosnia
15.58171364 Russian_Smolensk

[Dunai]

Really amazing to see so many Magyar Conqueror autosomal results, I believe it's a first to have so many. Even the conqueror elite seems to have been heavily heterogenous, with a great variety of multiple Eurasian regions, which makes you to conclude that the Magyar Conquerors were most probably a multiethnic steppe confederation, an alliance of multiple steppe people with a common political goal: to be united against eastern attacks, but also to live freely and independently from any other empire, thus they agreed that best way to survive is to find a suitable area to live under their own terms, which became the Carpathian Basin.

[oszkar07]

Just for fun, Ive checked those data against me.

Distance to: cakmir7y(czech)
8.02718506 K1per13_GE_S21_R1_001
13.10847436 DKper701_GE_S1_R1_001
14.34024058 KVper3450_GE_S7_R1_001
17.15278986 K2per6_GE_S16_R1_001
19.71218151 K3per3_GE_S6_R1_001
20.94599007 SHper2_GE_S3_R1_001
21.26221531 MHper16_GE_S12_R1_001
22.07166056 KeF2per2_GE_S3_R1_001_merged
22.60834802 SHper15_GE_S1_R1_001
22.90684396 K2per41_GE_S20_R1_001

This K1per13_GE_S21_R1_001 conqueror is one of the two of the whole dataset with E-V13 YDNA.


The same sample using updated K13 on vahaduo. I find it pretty interesting that one of the 9/10th century
Hungarian conquerors is closest to the modern Czechs.

Distance to: K1per13_GE_S21_R1_001
8.44624177 Czech
8.97092526 Sorb_Lusatia
9.18524904 German_East
9.32349184 Slovak
9.93049848 Polish_Masuria
10.18789969 Slovenian
10.46708651 South_Polish
10.62888517 Hungarian_North
11.27571727 Croat_North
11.33444749 Ukrainian_Galicia
11.78513046 Polish
11.87415260 Polish_Kielce
12.02045756 Hungarian_Transdanubia+Budapest
12.31556738 Hungarian
12.51479524 Ukrainian_Carpathian
12.52525848 Hungarian_Alföld
12.99195135 Moldova_Ukrainian
13.01068791 Austrian
13.74664686 Southwest_Finnish
13.81222285 Croat
13.84139444 Ukrainian
14.48467466 Croat_East
14.87906247 Croat_West
15.05897407 Bosniak_Bosnia
15.58171364 Russian_Smolensk

Such diversity amongst the conquerors
just for fun tried it and got him too.

Target: Oszkar
Distance: 3.2219% / 3.22194133 | ADC: 0.25x RC
66.2 K1per13_GE_S21_R1_001
15.0 KeF2per3_GE_S2_R1_001
8.5 K2per6_GE_S16_R1_001
6.9 K1per10_GE_S5_L001_R1_001
3.4 K2per26_GE_S9_R1_001

[Lucas]

Really amazing to see so many Magyar Conqueror autosomal results, I believe it's a first to have so many. Even the conqueror elite seems to have been heavily heterogenous, with a great variety of multiple Eurasian regions, which makes you to conclude that the Magyar Conquerors were most probably a multiethnic steppe confederation, an alliance of multiple steppe people with a common political goal: to be united against eastern attacks, but also to live freely and independently from any other empire, thus they agreed that best way to survive is to find a suitable area to live under their own terms, which became the Carpathian Basin.

Simply modern Hungarians:)

[someonenotyou]

Just for fun, Ive checked those data against me.

Distance to: cakmir7y(czech)
8.02718506 K1per13_GE_S21_R1_001
13.10847436 DKper701_GE_S1_R1_001
14.34024058 KVper3450_GE_S7_R1_001
17.15278986 K2per6_GE_S16_R1_001
19.71218151 K3per3_GE_S6_R1_001
20.94599007 SHper2_GE_S3_R1_001
21.26221531 MHper16_GE_S12_R1_001
22.07166056 KeF2per2_GE_S3_R1_001_merged
22.60834802 SHper15_GE_S1_R1_001
22.90684396 K2per41_GE_S20_R1_001

This K1per13_GE_S21_R1_001 conqueror is one of the two of the whole dataset with E-V13 YDNA.


The same sample using updated K13 on vahaduo. I find it pretty interesting that one of the 9/10th century
Hungarian conquerors is closest to the modern Czechs.

Distance to: K1per13_GE_S21_R1_001
8.44624177 Czech
8.97092526 Sorb_Lusatia
9.18524904 German_East
9.32349184 Slovak
9.93049848 Polish_Masuria
10.18789969 Slovenian
10.46708651 South_Polish
10.62888517 Hungarian_North
11.27571727 Croat_North
11.33444749 Ukrainian_Galicia
11.78513046 Polish
11.87415260 Polish_Kielce
12.02045756 Hungarian_Transdanubia+Budapest
12.31556738 Hungarian
12.51479524 Ukrainian_Carpathian
12.52525848 Hungarian_Alföld
12.99195135 Moldova_Ukrainian
13.01068791 Austrian
13.74664686 Southwest_Finnish
13.81222285 Croat
13.84139444 Ukrainian
14.48467466 Croat_East
14.87906247 Croat_West
15.05897407 Bosniak_Bosnia
15.58171364 Russian_Smolensk

Distance to:
10.27084222 K2per6_GE_S16_R1_001
11.92485220 K2per41_GE_S20_R1_001
15.33089365 KVper3450_GE_S7_R1_001
17.00336143 SHper2_GE_S3_R1_001
17.05856676 K1per13_GE_S21_R1_001
17.22604424 KeF2per2_GE_S3_R1_001_merged
21.74378992 MHper16_GE_S12_R1_001
22.29018842 K3per13_GE_S2_R1_001
24.28562332 MHper15_GE_S11_R1_001
27.05096117 K3per3_GE_S6_R1_001
29.06525417 KeF2per3_GE_S2_R1_001
29.08734089 SHper15_GE_S1_R1_001
30.54716026 SzKper239_GE_S28_R1_001
31.24128679 KVper3369_GE_S6_R1_001
31.46254917 K2per36_GE_S19_R1_001
32.59804289 K3per12_GE_S3_L001_R1_001
32.98714750 K2per29_GE_S10_L001_R1_001
32.98734000 K2per61_GE_S9_L001_R1_001
34.39166905 K2per18_GE_S13_R1_001
34.90955170 PVper72_GE_S29_R1_001
36.21224102 K2per52_GE_S1_R1_001_merged
39.34545336 SHper3_GE_S4_R1_001
41.82728894 K1per1_GE_S4_L001_R1_001
42.79850231 MHper9_GE_S10_R1_001_merged
42.94825608 K2per26_GE_S9_R1_001

The one I'm closest to is closest to Swiss French.

Distance to: K2per6_GE_S16_R1_001
11.38848980 Swiss_French
11.58908970 Csángó-Ceangău
11.69741424 Hungarian_Transylvania+Székely
11.70941929 Austrian
11.96522461 Swiss_German
12.20621153 France_Alsace
12.80619772 Hungarian_Transdanubia+Budapest
12.90855143 Swiss_German2
13.15615445 German_South
13.21002271 Hungarian
13.64346730 Croat_West
13.77091137 Hungarian_Alföld
13.96306199 Romania_Crisana
14.08001065 Romania_Moldavia_North
14.08724600 Pennsylvania_Dutch
14.14315736 Serb_Serbia_West
14.29239658 Croat
14.46667550 Croat_South
14.48639707 France_north-east
14.50255839 Romania_Maramures
14.52921540 Croat_North
14.55025773 Romania_Transylvania
14.55405785 German_West
14.62759379 Romania_Moldavia_South
14.65004437 Slovenian

[Dunai]

Simply modern Hungarians:)

Modern Hungarians actually are way more homegenous compared to Hungarian Conquerors. You will rarely see such large regional distances among us then among them, since most Modern Hungarians simply fit among other East Central and Souteastern Europeans. Of course if you also consider Hungarian nationals of Jewish or Romani ethnic background then Modern Hungarians can be as heterogenous as Hungarian Conquerors.

Someone should do an average for Hungarian Conquerors, curious what distance their average would get and to which populations are they closest.

[vbnetkhio]

I re-run all the files. the percentages are 1-2% off compared to Lucas' version.
in column 3 i added the quality (percentage of k13's SNPs present in the file)

__qualityNorth_AtlanticBalticWest_MedWest_AsianEas t_MedRed_SeaSouth_AsianEast_AsianSiberianAmerindia nOceanianNortheast_AfricanSub-Saharan
MMper227_GE_S31_R1_001early_avar0.02614625.7413.27 15.8614.9710.7912.860.012.360.530.003.620.000.00
KFPper6_GE_S2_R1_001early_avar0.02084818.3031.9517 .081.450.003.955.170.0012.251.700.000.008.15
KFPper31_GE_S3_R1_001early_avar0.01861522.925.3813 .259.7624.720.064.720.0010.502.765.930.000.00
FGDper4_GE_S4_R1_001early_avar0.0151285.0122.110.0 010.630.178.430.0013.6238.851.170.000.000.00
KBper300_GE_S5_R1_001early_avar0.0125890.0424.8515 .0024.970.9313.810.003.827.318.051.220.000.00
SzOper540_GE_S26_R1_001early_avar0.0106627.818.970 .0025.727.584.530.024.9229.114.220.000.007.14
PSZper1_GE_S33_R1_001early_avar0.00853832.739.9810 .500.0025.881.840.020.010.0015.563.490.000.00
SzOper81_GE_S25_R1_001early_avar0.00792533.940.010 .003.3035.785.738.500.007.205.550.000.000.00
MMper58_GE_S30_R1_001early_avar0.00740521.8128.110 .0126.580.000.002.560.0015.790.005.150.000.00
SzKper51_GE_S27_R1_001early_avar0.0053420.8541.213 .3215.518.4311.146.070.0012.480.001.010.000.00
DKper701_GE_S1_R1_001early_avar0.00450534.3230.671 0.8410.740.000.000.000.001.290.294.225.701.94
HUNper3_GE_S8_R1_001Hun0.0215724.3923.455.0520.121 4.522.850.010.004.853.190.001.580.00
HUNper1_GE_S32_R1_001Hun0.01043818.9419.179.4626.6 60.050.003.571.066.078.942.034.060.00
HUNper2_GE_S15_R1_001Hun0.00636527.5620.270.0012.7 85.5420.402.993.950.000.006.510.000.00
SzKper239_GE_S28_R1_001late_avar0.0255625.864.7219 .3215.3928.973.200.000.000.002.530.000.000.00
KVper3369_GE_S6_R1_001late_avar0.01216716.0238.166 .800.0010.700.0115.600.0012.330.000.360.000.00
PVper72_GE_S29_R1_001late_avar0.00779916.5453.9016 .720.000.110.000.000.002.252.840.007.640.00
SHper2_GE_S3_R1_001magyar0.02042121.3032.3819.9416 .792.720.000.000.000.003.123.770.000.00
MHper9_GE_S10_R1_001magyar0.0198525.2326.190.009.9 828.350.020.0020.332.734.490.630.002.06
K3per13_GE_S2_R1_001magyar0.01945215.8426.5415.081 6.510.053.630.016.8212.303.240.000.000.00
KeF2per15_GE_S5_R1_001magyar0.0187190.0236.040.001 1.670.000.887.363.9834.415.170.000.000.45
K2per52_GE_S1_R1_001magyar0.01735614.8325.580.0436 .7315.120.000.002.220.000.002.131.781.56
KVper3450_GE_S7_R1_001magyar0.01733423.9030.8220.0 90.079.180.830.001.975.657.480.000.000.00
KeF2per2_GE_S3_R1_001magyar0.01732836.6921.963.331 3.128.010.983.742.748.260.670.490.000.00
K2per36_GE_S19_R1_001magyar0.01680322.9610.1814.85 0.0125.844.4114.071.110.006.560.000.000.00
KeF2per3_GE_S2_R1_001magyar0.01539644.309.640.0121 .546.444.213.820.005.294.740.000.000.00
K1per13_GE_S21_R1_001magyar0.0152632.4940.9616.620 .006.230.920.000.160.000.800.001.820.00
K2per41_GE_S20_R1_001magyar0.01337734.0317.6020.96 12.778.050.003.170.000.770.831.810.000.00
MHper15_GE_S11_R1_001magyar0.01304323.0430.911.292 1.326.910.000.005.810.005.490.005.220.00
K2per6_GE_S16_R1_001magyar0.01157131.7821.7814.631 4.097.375.630.010.000.001.393.300.000.00
K2per26_GE_S9_R1_001magyar0.01154331.258.502.386.4 643.600.000.000.520.005.940.001.140.22
SHper3_GE_S4_R1_001magyar0.0084846.0820.9414.090.0 012.4316.470.000.0023.853.522.600.010.00
K1per1438_GE_S17_R1_001magyar0.0081990.9336.916.59 0.0042.733.260.000.000.007.820.000.001.76
SHper15_GE_S1_R1_001magyar0.00686936.5034.110.000. 000.0010.150.0010.300.000.004.333.401.20
MHper16_GE_S12_R1_001magyar0.00631132.5735.083.971 9.800.000.310.000.040.797.440.000.010.00
K2per18_GE_S13_R1_001magyar0.0058421.794.8728.850. 0018.770.0012.190.000.8412.690.000.000.00
K1per1_GE_S4_L001_R1_001magyar0.0056650.0016.2710. 7513.2823.0214.240.008.4813.970.000.000.000.00
K3per1_GE_S18_R1_001magyar0.0050240.0056.360.0116. 6712.430.002.840.8910.800.000.000.000.00
K1per3286_GE_S14_R1_001magyar0.00500842.990.002.39 0.520.008.6714.2713.6211.242.000.004.300.00
K2per61_GE_S9_L001_R1_001magyar0.00475135.800.0216 .1014.174.095.230.006.7014.273.620.000.000.00
K1per10_GE_S5_L001_R1_001magyar0.00474555.980.003. 450.000.0019.450.021.345.660.000.005.039.07
KeF2per14_GE_S8_R1_001magyar0.00460329.630.000.004 .150.000.0024.030.0030.905.020.006.260.00
K2per29_GE_S10_L001_R1_001magyar0.00394620.8827.81 0.000.0030.400.6611.690.106.670.001.810.000.00
K2per16_GE_S7_L001_R1_001magyar0.00333328.730.007. 8023.806.590.0033.080.000.000.000.000.000.00
K3per3_GE_S6_R1_001magyar0.00272627.5340.301.620.0 011.640.000.000.000.000.0113.125.790.00
K2per33_GE_S2_L001_R1_001magyar0.0026870.0156.8026 .534.600.000.000.000.000.000.610.0011.450.00
K3per12_GE_S3_L001_R1_001magyar0.0025427.8217.830. 0224.181.300.006.610.000.0020.222.010.000.00
K2per51_GE_S7_R1_001magyar0.0016910.000.0018.370.0 00.000.0033.750.0041.820.001.444.610.00
K3per6_GE_S10_R1_001magyar0.0016911.6143.490.000.0 00.000.009.690.0028.130.000.0017.080.00

[vbnetkhio]

the 12 highest quality/most reliable results:

early_avar:KFPper31_GE_S3_R1_001,22.92,5.38,13.25, 9.76,24.72,0.06,4.72,0.00,10.50,2.76,5.93,0.00,0.0 0
early_avar:KFPper6_GE_S2_R1_001,18.30,31.95,17.08, 1.45,0.00,3.95,5.17,0.00,12.25,1.70,0.00,0.00,8.15
early_avar:MMper227_GE_S31_R1_001,25.74,13.27,15.8 6,14.97,10.79,12.86,0.01,2.36,0.53,0.00,3.62,0.00, 0.00
Hun:HUNper3_GE_S8_R1_001,24.39,23.45,5.05,20.12,14 .52,2.85,0.01,0.00,4.85,3.19,0.00,1.58,0.00
late_avar:SzKper239_GE_S28_R1_001,25.86,4.72,19.32 ,15.39,28.97,3.20,0.00,0.00,0.00,2.53,0.00,0.00,0. 00
magyar:K2per52_GE_S1_R1_001,14.83,25.58,0.04,36.73 ,15.12,0.00,0.00,2.22,0.00,0.00,2.13,1.78,1.56
magyar:K3per13_GE_S2_R1_001,15.84,26.54,15.08,16.5 1,0.05,3.63,0.01,6.82,12.30,3.24,0.00,0.00,0.00
magyar:KeF2per15_GE_S5_R1_001,0.02,36.04,0.00,11.6 7,0.00,0.88,7.36,3.98,34.41,5.17,0.00,0.00,0.45
magyar:KeF2per2_GE_S3_R1_001,36.69,21.96,3.33,13.1 2,8.01,0.98,3.74,2.74,8.26,0.67,0.49,0.00,0.00
magyar:KVper3450_GE_S7_R1_001,23.90,30.82,20.09,0. 07,9.18,0.83,0.00,1.97,5.65,7.48,0.00,0.00,0.00
magyar:MHper9_GE_S10_R1_001,5.23,26.19,0.00,9.98,2 8.35,0.02,0.00,20.33,2.73,4.49,0.63,0.00,2.06
magyar:SHper2_GE_S3_R1_001,21.30,32.38,19.94,16.79 ,2.72,0.00,0.00,0.00,0.00,3.12,3.77,0.00,0.00

[vbnetkhio]

all files merged into one, k13 results:


Component %
North_Atlantic 23,08%
Baltic 22,66%
West_Med 8,81%
West_Asian 11,48%
East_Med 13,46%
Red_Sea 3,50%
South_Asian 2,44%
East_Asian 2,78%
Siberian 8,99%
Amerindian 2,26%
Oceanian 0,55%

Oracle Calculator by www.dnagenics.com
v1.9 01/08/2020

Finished reading population data. 369 populations found.
13 components mode.

A distance calculation method.

--------------------------------


Mixed Mode:
1 68,36% Turk_Kardzhali-South-Plain + 31,64% North-Swedish @ 4,504
2 72,27% Szekely + 27,73% Afghan_Turkmen @ 4,816
3 69,92% Csango_Gymes + 30,08% Turkmen_Uzbekistan @ 4,871
4 62,89% Turk_Kardzhali-East + 37,11% Tatar @ 4,871
5 62,89% Turk_Stara-Zagora + 37,11% Tatar @ 4,874
6 72,27% Szekely + 27,73% Turkmen_Uzbekistan @ 5,015
7 51,95% Turk_Alexandroupoli + 48,05% Tatar @ 5,158
8 50,39% Tatar + 49,61% Turk_Alexandroupoli @ 5,210
9 58,98% Tatar + 41,02% Marche @ 5,230
10 58,98% Tatar + 41,02% Umbria @ 5,243

Least-squares method.

Using 1 populations approximation
1 100% Turk_Stara-Zagora @ 11,173
2 100% Turk_Razgrad @ 11,176
3 100% Turk_Kardzhali-East @ 11,292
4 100% Turk_N-Macedonia @ 11,724
5 100% Szekely @ 12,173
6 100% Turk_Kardzhali-West @ 12,356
7 100% Romanian_South_Central_Moldova @ 12,390
8 100% Turk_Sliven-Alevi @ 12,397
9 100% Bulgarian_Dupnitsa @ 12,748
10 100% Turk_Targovishte @ 12,770

Using 2 populations approximation
1 50% Turk_Alexandroupoli + 50% Tatar @ 5,193
2 50% Southwest_Finnish + 50% Turk_South @ 5,321
3 50% Greek_Central-Macedonia + 50% Tatar @ 5,679
4 50% Turk_Central_West + 50% Southwest_Finnish @ 5,813
5 50% Turk_North_West + 50% Southwest_Finnish @ 5,871
6 50% Southwest_Finnish + 50% Turk_Anatolia @ 5,905
7 50% Turk_Kardzhali-East + 50% Tatar @ 5,940
8 50% Turk_Stara-Zagora + 50% Tatar @ 5,981
9 50% Szekely + 50% Crimean_Tatar @ 5,997
10 50% Turk_Targovishte + 50% Tatar @ 6,035

Using 3 populations approximation
1 33% Mari + 33% North-Dutch + 33% Nusayri @ 2,943
2 33% Mari + 33% North-Dutch + 33% Lebanese_Muslim @ 3,089
3 33% Mari + 33% North-Dutch + 33% Syrian @ 3,407
4 33% Mari + 33% North-Dutch + 33% Turk_Cypriot @ 3,742
5 33% Mari + 33% North-Dutch + 33% Cyprian @ 3,873
6 33% Mari + 33% North-Dutch + 33% Greek_Cypriot @ 3,873
7 33% Mari + 33% North-Dutch + 33% Greek_Cappadocian @ 4,126
8 33% Malta + 33% Afghan_Turkmen + 33% Southwest_Finnish @ 4,347
9 33% Mari + 33% North-Dutch + 33% Kurdish_Jewish @ 4,539
10 33% Turk_Kardzhali-South-Plain + 33% Turk_Kardzhali-South-Plain + 33% North-Swedish @ 4,571

Using 4 populations approximation
1 25% Turk_Burgas + 25% Turk_Burgas + 25% Turk_Dobruja-Tatar + 25% Southwest_Finnish @ 3,695
2 25% Turk_Burgas + 25% Turk_Burgas + 25% Turk_Dobruja-Tatar + 25% Finnish @ 4,070
3 25% Turk_Burgas + 25% Turk_Burgas + 25% Turk_Dobruja-Tatar + 25% North-Swedish @ 4,118
4 25% Pomak_Central-Macedonia + 25% Pomak_Central-Macedonia + 25% Romanian_North_Moldova_Bukovina + 25% Shors @ 4,415
5 25% Turk_Burgas + 25% Turk_Burgas + 25% Turk_Dobruja-Tatar + 25% East_Finnish @ 4,595
6 25% Crimean_Tatar + 25% Crimean_Tatar + 25% Vlach_North-Macedonia-Highlander + 25% North_German @ 4,718
7 25% Turk_Burgas + 25% Turk_Burgas + 25% Turk_Dobruja-Tatar + 25% Estonian @ 4,727
8 25% Crimean_Tatar + 25% Crimean_Tatar + 25% Vlach_North-Macedonia-Highlander + 25% Danish @ 4,803
9 25% Crimean_Tatar + 25% Crimean_Tatar + 25% Vlach_North-Macedonia-Highlander + 25% Swedish @ 4,805
10 25% Csango_Gymes + 25% Csango_Gymes + 25% Romanian_Oltenia + 25% Afghan_Turkmen @ 4,852

^it has 40% k13 SNPs. highest individual files have only 2%.

compare it to the average of all results:


North_Atlantic 21.21
Baltic 22.57
West_Med 8.43
West_Asian 10.63
East_Med 10.32
Red_Sea 3.85
South_Asian 4.69
East_Asian 2.39
Siberian 8.55
Amerindian 3.46
Oceanian 1.45
Northeast_African 1.77
Sub-Saharan 0.68


it shows how realiable k13 is, even on a very low number of SNPs.

[Dunai]

the 12 highest quality/most reliable results:

early_avar:KFPper31_GE_S3_R1_001,22.92,5.38,13.25, 9.76,24.72,0.06,4.72,0.00,10.50,2.76,5.93,0.00,0.0 0
early_avar:KFPper6_GE_S2_R1_001,18.30,31.95,17.08, 1.45,0.00,3.95,5.17,0.00,12.25,1.70,0.00,0.00,8.15
early_avar:MMper227_GE_S31_R1_001,25.74,13.27,15.8 6,14.97,10.79,12.86,0.01,2.36,0.53,0.00,3.62,0.00, 0.00
Hun:HUNper3_GE_S8_R1_001,24.39,23.45,5.05,20.12,14 .52,2.85,0.01,0.00,4.85,3.19,0.00,1.58,0.00
late_avar:SzKper239_GE_S28_R1_001,25.86,4.72,19.32 ,15.39,28.97,3.20,0.00,0.00,0.00,2.53,0.00,0.00,0. 00
magyar:K2per52_GE_S1_R1_001,14.83,25.58,0.04,36.73 ,15.12,0.00,0.00,2.22,0.00,0.00,2.13,1.78,1.56
magyar:K3per13_GE_S2_R1_001,15.84,26.54,15.08,16.5 1,0.05,3.63,0.01,6.82,12.30,3.24,0.00,0.00,0.00
magyar:KeF2per15_GE_S5_R1_001,0.02,36.04,0.00,11.6 7,0.00,0.88,7.36,3.98,34.41,5.17,0.00,0.00,0.45
magyar:KeF2per2_GE_S3_R1_001,36.69,21.96,3.33,13.1 2,8.01,0.98,3.74,2.74,8.26,0.67,0.49,0.00,0.00
magyar:KVper3450_GE_S7_R1_001,23.90,30.82,20.09,0. 07,9.18,0.83,0.00,1.97,5.65,7.48,0.00,0.00,0.00
magyar:MHper9_GE_S10_R1_001,5.23,26.19,0.00,9.98,2 8.35,0.02,0.00,20.33,2.73,4.49,0.63,0.00,2.06
magyar:SHper2_GE_S3_R1_001,21.30,32.38,19.94,16.79 ,2.72,0.00,0.00,0.00,0.00,3.12,3.77,0.00,0.00

Great work! So can you make and add a brand new Hungarian_Conqueror average from all of the 30+ results? Even if they are of low SNP numbers, as you said, they seem to be pretty usable. I would be curious how does this new average score on K13 Updated calculator.

[vbnetkhio]

Great work! So can you make and add a brand new Hungarian_Conqueror average from all of the 30+ results? Even if they are of low SNP numbers, as you said, they seem to be pretty usable. I would be curious how does this new average score on K13 Updated calculator.

HQ-the 7 best ones


Magyar_HQ,16.83,28.50,8.35,14.98,9.06,0.91,1.59,5. 44,9.05,3.45,1.00,0.25,0.58
Magyar_all,22.08,22.81,8.43,9.44,10.35,3.12,5.64,2 .72,8.07,3.53,1.17,2.12,0.51

[Dirdepo]

I am the conqueror.

[Dunai]

HQ-the 7 best ones


Magyar_HQ,16.83,28.50,8.35,14.98,9.06,0.91,1.59,5. 44,9.05,3.45,1.00,0.25,0.58
Magyar_all,22.08,22.81,8.43,9.44,10.35,3.12,5.64,2 .72,8.07,3.53,1.17,2.12,0.51

So these are the results:

Distance to: Hungarian_ConquerorHQ
11.73344792 Tatar
13.16684093 Crimean_Tatar
15.65839072 Moldova_Centre
15.76961636 Moldova_North
15.82544154 Moldova_average
15.88991504 Turk_Deliorman
16.40407267 Romania_Moldavia_North
16.58459225 Csángó-Ceangău
17.25647415 Bosniak
17.38331384 Moldova_South
17.56439865 Serb_Bosnia
17.61708546 Romania_Maramures
17.70670212 Bosniak_Bosnia
17.71832949 Hungarian_Transylvania+Székely
17.77625101 Romania_average
17.79638727 Serb_Serbia_South
17.87412096 Romania_Moldavia_South
17.91855463 Serb
17.96137523 Romania_Banat
18.00890891 Turk_Trakya
18.05987541 Pomak_Greece
18.06217041 Romania_Dobruja
18.13988423 Croat_East
18.14063395 Serb_Serbia_West
18.16122518 Romania_Transylvania

Target: Hungarian_ConquerorHQ
Distance: 1.2410% / 1.24095167 | ADC: 0.25x RC
46.2 Crimean_Tatar
27.7 Ukrainian_Belgorod
8.8 Turk_Deliorman
5.7 Chechen
5.2 Moldova_North
3.9 Tatar
2.5 Karitiana

Distance to: Hungarian_ConquerorAll
13.87981628 Csángó-Ceangău
14.06147218 Hungarian_Transylvania+Székely
14.49503363 Romania_Moldavia_North
14.67297516 Moldova_Centre
14.97825758 Moldova_average
15.05313921 Romania_Moldavia_South
15.18746852 Turk_Deliorman
15.22876554 Romania_Maramures
15.31016329 Romania_average
15.32285548 Romania_Transylvania
15.46040103 Moldova_South
15.58040436 Romania_Banat
15.59502485 Romania_Crisana
15.75522770 Romania_Dobruja
15.87778322 Serb_Serbia_South
15.88893955 Romania_Wallachia
15.94626289 Serb_Serbia_Vojvodina
15.96135959 Romania_Oltenia
15.97829152 Serb
15.98336635 Romania_Muntenia
16.00236857 Serb_Serbia_West
16.21189070 Bulgaria_Southwestern
16.22690359 Serb_Croatia
16.24291538 Bosniak
16.25058460 Serb_Bosnia

Target: Hungarian_ConquerorAll
Distance: 1.9405% / 1.94050151 | ADC: 0.25x RC
27.5 Tatar
21.0 Afrikaner
17.1 Gypsy_Wallachia
15.2 Hungarian_Transylvania+Székely
8.4 Crimean_Tatar
5.2 Ethiopian_Amhara
4.2 West_Greenlander
1.4 North_Amerindian

[vbnetkhio]

So these are the results:

Distance to: Hungarian_ConquerorHQ
11.73344792 Tatar
13.16684093 Crimean_Tatar
15.65839072 Moldova_Centre
15.76961636 Moldova_North
15.82544154 Moldova_average
15.88991504 Turk_Deliorman
16.40407267 Romania_Moldavia_North
16.58459225 Csángó-Ceangău
17.25647415 Bosniak
17.38331384 Moldova_South
17.56439865 Serb_Bosnia
17.61708546 Romania_Maramures
17.70670212 Bosniak_Bosnia
17.71832949 Hungarian_Transylvania+Székely
17.77625101 Romania_average
17.79638727 Serb_Serbia_South
17.87412096 Romania_Moldavia_South
17.91855463 Serb
17.96137523 Romania_Banat
18.00890891 Turk_Trakya
18.05987541 Pomak_Greece
18.06217041 Romania_Dobruja
18.13988423 Croat_East
18.14063395 Serb_Serbia_West
18.16122518 Romania_Transylvania

Target: Hungarian_ConquerorHQ
Distance: 1.2410% / 1.24095167 | ADC: 0.25x RC
46.2 Crimean_Tatar
27.7 Ukrainian_Belgorod
8.8 Turk_Deliorman
5.7 Chechen
5.2 Moldova_North
3.9 Tatar
2.5 Karitiana

Distance to: Hungarian_ConquerorAll
13.87981628 Csángó-Ceangău
14.06147218 Hungarian_Transylvania+Székely
14.49503363 Romania_Moldavia_North
14.67297516 Moldova_Centre
14.97825758 Moldova_average
15.05313921 Romania_Moldavia_South
15.18746852 Turk_Deliorman
15.22876554 Romania_Maramures
15.31016329 Romania_average
15.32285548 Romania_Transylvania
15.46040103 Moldova_South
15.58040436 Romania_Banat
15.59502485 Romania_Crisana
15.75522770 Romania_Dobruja
15.87778322 Serb_Serbia_South
15.88893955 Romania_Wallachia
15.94626289 Serb_Serbia_Vojvodina
15.96135959 Romania_Oltenia
15.97829152 Serb
15.98336635 Romania_Muntenia
16.00236857 Serb_Serbia_West
16.21189070 Bulgaria_Southwestern
16.22690359 Serb_Croatia
16.24291538 Bosniak
16.25058460 Serb_Bosnia

Target: Hungarian_ConquerorAll
Distance: 1.9405% / 1.94050151 | ADC: 0.25x RC
27.5 Tatar
21.0 Afrikaner
17.1 Gypsy_Wallachia
15.2 Hungarian_Transylvania+Székely
8.4 Crimean_Tatar
5.2 Ethiopian_Amhara
4.2 West_Greenlander
1.4 North_Amerindian

I merged the cluster of conquerors with >20% Asiatic into one file:

https://i.imgur.com/k33BRYY.png

the same for Avars:
https://i.imgur.com/wxQgMAT.png

they turned out very similar to each other.

[Kaspias]

I merged the cluster of conquerors with >20% Asiatic into one file:

https://i.imgur.com/k33BRYY.png

the same for Avars:
https://i.imgur.com/wxQgMAT.png

they turned out very similar to each other.

Awesome! These are looking legit. Can you provide K12b results, too?

[vbnetkhio]

Awesome! These are looking legit. Can you provide K12b results, too?

Magyars:

15.99% Gedrosia
13.64% Siberian
0.00% Northwest_African
0.01% Southeast_Asian
13.00% Atlantic_Med
25.54% North_European
3.20% South_Asian
0.00% East_African
7.83% Southwest_Asian
16.46% East_Asian
4.33% Caucasus
0.00% Sub_Saharan

Mixed Mode:
1 63,67% Hazara + 36,33% Swedish @ 7,582
2 64,45% Hazara + 35,55% Norwegian @ 7,782
3 61,33% Hazara + 38,67% German @ 8,929
4 62,11% Hazara + 37,89% Dutch @ 9,114
5 63,67% Hazara + 36,33% Orkney @ 9,152
6 70,70% Uzbeks + 29,30% Orkney @ 9,194
7 71,48% Uzbeks + 28,52% Norwegian @ 9,239
8 70,70% Uzbeks + 29,30% Orcadian @ 9,246
9 69,92% Uzbeks + 30,08% Argyll @ 9,286
10 62,89% Hazara + 37,11% Argyll @ 9,315

Least-squares method.

Using 1 populations approximation
1 100% Crimean_Tatar_Steppe @ 14,828
2 100% Bashkir @ 15,809
3 100% Uzbeks @ 19,754
4 100% Karakalpak @ 21,480
5 100% Turkmen_Uzbekistan @ 21,780
6 100% Uygur @ 25,064
7 100% Hazara @ 25,579
8 100% Kazakh @ 27,115
9 100% Tajiks @ 28,307
10 100% Kyrgyz @ 31,205

Using 2 populations approximation
1 50% Hazara + 50% German @ 11,355
2 50% Hazara + 50% Mixed_Germanic @ 11,873
3 50% Hazara + 50% Dutch @ 11,984
4 50% Hazara + 50% Swedish @ 12,191
5 50% Hazara + 50% Hungarians @ 12,343
6 50% Hazara + 50% Norwegian @ 12,362
7 50% Hazara + 50% Argyll @ 12,528
8 50% Hazara + 50% CEU30 @ 12,702
9 50% Hazara + 50% English @ 12,718
10 50% Hazara + 50% Orkney @ 12,799

Using 3 populations approximation
1 33% Hazara + 33% Hazara + 33% Swedish @ 7,784
2 33% Hazara + 33% Hazara + 33% Norwegian @ 7,966
3 33% Tajiks + 33% Kyrgyz + 33% Norwegian @ 9,026
4 33% Uygur + 33% Hazara + 33% Norwegian @ 9,072
5 33% Uygur + 33% Hazara + 33% Swedish @ 9,141
6 33% Tajiks + 33% Kyrgyz + 33% Swedish @ 9,164
7 33% Uzbeks + 33% Karakalpak + 33% Argyll @ 9,187
8 33% Swedish + 33% Mongol + 33% Pathan @ 9,208
9 33% Hazara + 33% Kazakh + 33% Swedish @ 9,226
10 33% Hazara + 33% Kazakh + 33% Norwegian @ 9,320

Using 4 populations approximation
1 25% Kazakh + 25% Kazakh + 25% Tajiks + 25% Norwegian @ 8,526
2 25% Kazakh + 25% Kazakh + 25% Tajiks + 25% Swedish @ 8,635
3 25% Kazakh + 25% Kazakh + 25% Tajiks + 25% Orkney @ 8,653
4 25% Kazakh + 25% Kazakh + 25% Tajiks + 25% Orcadian @ 8,715
5 25% Kazakh + 25% Kazakh + 25% Tajiks + 25% Argyll @ 8,771
6 25% Kazakh + 25% Kazakh + 25% Tajiks + 25% Irish @ 8,780
7 25% Kazakh + 25% Kazakh + 25% Tajiks + 25% British @ 9,004
8 25% Kazakh + 25% Kazakh + 25% Tajiks + 25% British_Isles @ 9,036
9 25% Kazakh + 25% Kazakh + 25% Tajiks + 25% English @ 9,170
10 25% Kazakh + 25% Kazakh + 25% Tajiks + 25% CEU30 @ 9,203

Avars:


6.74% Gedrosia
23.67% Siberian
0.00% Northwest_African
0.03% Southeast_Asian
9.79% Atlantic_Med
17.77% North_European
0.66% South_Asian
0.00% East_African
4.04% Southwest_Asian
13.25% East_Asian
24.05% Caucasus
0.00% Sub_Saharan

Mixed Mode:
1 63,67% Crimean_Tatar_Mountain + 36,33% Tuva @ 4,958
2 58,98% Crimean_Tatar_Coast + 41,02% Tuva @ 5,411
3 71,48% Crimean_Tatar_Mountain + 28,52% Yakut @ 6,780
4 66,02% Crimean_Tatar_Mountain + 33,98% Buryat @ 6,868
5 54,30% Crimean_Tatar_Coast + 45,70% Altai @ 7,399
6 59,77% Crimean_Tatar_Mountain + 40,23% Altai @ 7,442
7 72,27% Crimean_Tatar_Mountain + 27,73% Yukagir @ 7,590
8 73,83% Crimean_Tatar_Mountain + 26,17% Evenk @ 7,725
9 60,55% Crimean_Tatar_Coast + 39,45% Buryat @ 7,746
10 50,39% Altai + 49,61% Crimean_Tatar_Coast @ 7,999

Least-squares method.

Using 1 populations approximation
1 100% Crimean_Tatar_Steppe @ 15,961
2 100% Turkmen_Uzbekistan @ 18,825
3 100% Uzbeks @ 20,298
4 100% Nogais @ 20,530
5 100% Karakalpak @ 20,742
6 100% Bashkir @ 22,181
7 100% Yoruk @ 22,646
8 100% Turk_Northwest @ 23,421
9 100% Turk_Southwest @ 24,973
10 100% Crimean_Tatar_Mountain @ 25,383

Using 2 populations approximation
1 50% Crimean_Tatar_Coast + 50% Altai @ 7,905
2 50% Greek + 50% Altai @ 8,630
3 50% Crimean_Tatar_Coast + 50% Tuva @ 8,650
4 50% Crimean_Tatar_Mountain + 50% Altai @ 9,339
5 50% Greek + 50% Tuva @ 9,495
6 50% Ashkenazy_Jews + 50% Altai @ 9,532
7 50% Greek_Crete + 50% Altai @ 9,920
8 50% Altai + 50% Ashkenazi @ 10,142
9 50% Italy_Apulia + 50% Altai @ 10,170
10 50% Turk_West_BlackSea + 50% Altai @ 10,492

Using 3 populations approximation
1 33% Crimean_Tatar_Mountain + 33% Crimean_Tatar_Mountain + 33% Tuva @ 5,322
2 33% Circassian + 33% Macedonian + 33% Tuva @ 6,606
3 33% Turk_Southwest + 33% Crimean_Tatar_Mountain + 33% Tuva @ 6,851
4 33% Crimean_Tatar_Mountain + 33% Crimean_Tatar_Mountain + 33% Buryat @ 6,901
5 33% Circassian + 33% Macedonian + 33% Buryat @ 7,068
6 33% Circassian + 33% Macedonian + 33% Yakut @ 7,146
7 33% Italy_Trentino + 33% Balkars + 33% Tuva @ 7,274
8 33% North_Ossetians + 33% Swiss_Italian + 33% Tuva @ 7,307
9 33% Turk_East_Black_Sea + 33% Tuva + 33% Hungarians @ 7,414
10 33% Azerbaijani_Turkey + 33% Gagauz + 33% Tuva @ 7,490

Using 4 populations approximation
1 25% Crimean_Tatar_Coast + 25% Crimean_Tatar_Coast + 25% Kyrgyz_Bishkek + 25% Dolgan @ 5,829
2 25% Crimean_Tatar_Coast + 25% Crimean_Tatar_Coast + 25% Kyrgyz_Bishkek + 25% Ket @ 5,843
3 25% Crimean_Tatar_Coast + 25% Crimean_Tatar_Coast + 25% Kyrgyz_Bishkek + 25% Selkup @ 6,355
4 25% Crimean_Tatar_Mountain + 25% Crimean_Tatar_Mountain + 25% Kazakh + 25% Dolgan @ 6,601
5 25% Altai + 25% Altai + 25% Italy_Marche + 25% Adygei @ 6,777
6 25% Tuva + 25% Tuva + 25% Hungarians + 25% Abhkasians @ 6,808
7 25% Altai + 25% Altai + 25% Italy_Marche + 25% Balkars @ 6,821
8 25% Altai + 25% Altai + 25% Ashkenazi + 25% Adygei @ 6,833
9 25% Tuva + 25% Tuva + 25% Hungarians + 25% Georgian_Imereti @ 6,904
10 25% Tuva + 25% Tuva + 25% Hungarians + 25% Georgian_Mingrelian @ 6,922