View Full Version : Gedmatch results of a Saami from Norway
Zanzibar
02-24-2021, 09:35 AM
Here is what he look like.
https://i.imgur.com/Z7c0Ery.jpg
https://i.imgur.com/SK3UxpB.jpg
https://i.imgur.com/aNs8sqH.jpg
Eurogenes K13: He has at least 22% East Eurasian (Siberian+Amerindian) ancestry. I'm not sure is the South Asian that he is scoring genuine or some other type of East Eurasian or West Eurasian ancestry.
Admix Results (sorted):
# Population Percent
1 Baltic 42.9
2 North_Atlantic 29.64
3 Siberian 18.55
4 Amerindian 3.88
5 South_Asian 3.18
6 West_Asian 1.64
7 Oceanian 0.19
8 Sub-Saharan 0.02
Single Population Sharing:
# Population (source) Distance
1 East_Finnish 13.19
2 Chuvash 14.8
3 Finnish 14.94
4 Kargopol_Russian 15.97
5 Tatar 16.71
6 Mari 16.95
7 Southwest_Finnish 17.62
8 Erzya 17.68
9 Estonian 18.53
10 Southwest_Russian 20.73
11 Estonian_Polish 20.93
12 Belorussian 20.96
13 Russian_Smolensk 21.52
14 Ukrainian_Belgorod 21.9
15 Polish 22.02
16 Ukrainian 22.06
17 Lithuanian 22.14
18 Ukrainian_Lviv 22.24
19 La_Brana-1 22.28
20 South_Polish 22.29
Mixed Mode Population Sharing:
# Primary Population (source) Secondary Population (source) Distance
1 78.1% Finnish + 21.9% Ket @ 5.02
2 78.3% Finnish + 21.7% Selkup @ 5.08
3 85.1% East_Finnish + 14.9% Koryak @ 5.68
4 84.8% East_Finnish + 15.2% Chukchi @ 5.79
5 83.2% Finnish + 16.8% Koryak @ 5.92
6 81% East_Finnish + 19% Ket @ 5.94
7 83.9% Finnish + 16.1% Dolgan @ 6.16
8 81.3% East_Finnish + 18.7% Selkup @ 6.18
9 85.2% Finnish + 14.8% Evens @ 6.25
10 87.1% East_Finnish + 12.9% Evens @ 6.27
11 83% Finnish + 17% Chukchi @ 6.3
12 85.9% East_Finnish + 14.1% Dolgan @ 6.31
13 85% Finnish + 15% Evenki @ 6.41
14 86.9% East_Finnish + 13.1% Evenki @ 6.44
15 75.5% Southwest_Finnish + 24.5% Selkup @ 6.53
16 74.3% Estonian + 25.7% Ket @ 6.55
17 51.1% Mari + 48.9% Southwest_Finnish @ 6.59
18 74.5% Estonian + 25.5% Selkup @ 6.72
19 58.3% Mari + 41.7% North_Swedish @ 6.79
20 75.5% Southwest_Finnish + 24.5% Ket @ 6.8
PuntDNAL K12 Modern: He has very low Neolithic Farmer compared to most European results it seems. He is approximately 21-22% East Eurasian (Siberian+Beringian+Amerindian+Oceanian). Once again not sure if the minor South Asian he possess is East or West Eurasian. But if it is East Eurasian, he could be up to 23% Mongoloid.
Admix Results (sorted):
# Population Percent
1 European_HG 45.61
2 Caucasus_HG 17.28
3 Siberian 14.45
4 Anatolian_NF 13.37
5 Beringian 5.19
6 South_Asian 1.91
7 Amerindian 1.47
8 Oceanian 0.7
Single Population Sharing:
# Population (source) Distance
1 Chuvash 5.16
2 Russian 11.16
3 Mordovian 11.78
4 Finnish 14.31
5 Belarusian 18.89
6 Estonian 19.67
7 Lithuanian 20.48
8 Icelandic 21.63
9 Czech 22.11
10 Scottish_West 23.02
11 German_North 23.19
12 Dutch_North 23.32
13 Swedish 23.49
14 Hungarian 23.72
15 Norwegian 23.9
16 Irish 24.57
17 English_South 25.38
18 Dutch_South 25.71
19 Croatian 25.97
20 Utahn_European 26.79
Mixed Mode Population Sharing:
# Primary Population (source) Secondary Population (source) Distance
1 82.5% Russian + 17.5% Selkup @ 3.52
2 77.9% Chuvash + 22.1% Russian @ 4.25
3 79.8% Chuvash + 20.2% Mordovian @ 4.36
4 97.3% Chuvash + 2.7% Chukchi @ 4.42
5 87.8% Chuvash + 12.2% Belarusian @ 4.49
6 97.5% Chuvash + 2.5% Koryak @ 4.5
7 88.4% Chuvash + 11.6% Estonian @ 4.51
8 89.1% Chuvash + 10.9% Lithuanian @ 4.54
9 90.6% Chuvash + 9.4% Czech @ 4.64
10 85.9% Chuvash + 14.1% Finnish @ 4.66
11 90.7% Chuvash + 9.3% Icelandic @ 4.69
12 95.8% Chuvash + 4.2% Punjabi_Jatt_Sikh @ 4.69
13 91.4% Chuvash + 8.6% Dutch_North @ 4.69
14 91.4% Chuvash + 8.6% Scottish_West @ 4.7
15 94.1% Chuvash + 5.9% Tajik_Pomiri @ 4.7
16 91.4% Chuvash + 8.6% German_North @ 4.7
17 95.7% Chuvash + 4.3% Haryana_Jatt @ 4.71
18 91.7% Chuvash + 8.3% Hungarian @ 4.71
19 96.1% Chuvash + 3.9% Punjabi_Jatt_Muslim @ 4.71
20 95.9% Chuvash + 4.1% Pakistan_Pashtun @ 4.73
Gedrosia K12: He seems to have much lower EEF than other European results that I saw. Also he is around 20-21% Mongoloid (W_Siberian+E_Siberian+SE Asian+Indo-Tibetan).
Admix Results (sorted):
# Population Percent
1 SINTASHTA_STEPPE_HERDERS 47.17
2 EARLY_EUROPEAN_FARMERS 18.11
3 W_SIBERIAN 10.32
4 BALOCHI 5.97
5 E_SIBERIAN 5.69
6 CAUCASUS 5.05
7 SE_ASIAN 4.27
8 S_INDIAN 2.26
9 INDO_TIBETAN 1.16
Single Population Sharing:
# Population (source) Distance
1 Russian 16.83
2 Finnish 20.87
3 Norwegian 22.63
4 Estonian 26.13
5 Lithuanian 27.75
6 Turkmen_Afghan 38.05
7 Uzbek 38.39
8 Tajik_Pomiri 38.93
9 Greek 41.04
10 Tajik_Afghan 45.09
11 Uzbek_Afghan 45.21
12 Turks_Istanbul 45.88
13 Sicilian 46.62
14 Turks_Aydin 46.99
15 Turks_Balikesir 47.99
16 Pashtun_Afghan 49.24
17 Kurds_C 50.64
18 Kurds_N 51.82
19 Kurds_SE 52.35
20 Pathan 53.07
Mixed Mode Population Sharing:
# Primary Population (source) Secondary Population (source) Distance
1 65.3% Finnish + 34.7% Uzbek @ 5.25
2 65.1% Finnish + 34.9% Turkmen_Afghan @ 5.36
3 70.8% Russian + 29.2% Uzbek @ 6.23
4 70.7% Russian + 29.3% Turkmen_Afghan @ 6.54
5 60% Estonian + 40% Uzbek @ 6.85
6 79.9% Russian + 20.1% Yukagir @ 7.19
7 59.8% Estonian + 40.2% Turkmen_Afghan @ 7.25
8 58.5% Lithuanian + 41.5% Uzbek @ 7.36
9 82.7% Russian + 17.3% Ulchi @ 7.52
10 58.3% Lithuanian + 41.7% Turkmen_Afghan @ 7.83
11 69.7% Finnish + 30.3% Tajik_Afghan @ 8
12 69.8% Finnish + 30.2% Uzbek_Afghan @ 8.05
13 75.4% Russian + 24.6% Uzbek_Afghan @ 8.59
14 75.4% Russian + 24.6% Tajik_Afghan @ 8.65
15 83.7% Russian + 16.3% Mongola @ 9.56
16 69.8% Lithuanian + 30.2% Yukagir @ 9.83
17 71.3% Estonian + 28.7% Yukagir @ 9.98
18 79.6% Finnish + 20.4% Ulchi @ 10.04
19 79.4% Russian + 20.6% Kurds_SE @ 10.25
20 76.8% Finnish + 23.2% Yukagir @ 10.28
MDLP K23b: Not sure if the Ancestral Altaic is hiding some Mongoloid, but he is also approximately 21-22% Mongoloid here.
Admix Results (sorted):
# Population Percent
1 European_Hunters_Gatherers 45.99
2 East_Siberian 14.4
3 Ancestral_Altaic 13.29
4 Caucasian 12.9
5 South_Central_Asian 3.34
6 Tungus-Altaic 2.83
7 European_Early_Farmers 2.35
8 Amerindian 1.69
9 Paleo_Siberian 1.05
10 Arctic 1.02
11 South_Indian 0.57
12 Austronesian 0.25
13 Australoid 0.18
14 Archaic_Human 0.13
Single Population Sharing:
# Population (source) Distance
1 Saami_Finland ( ) 4.84
2 Mari ( ) 7.58
3 Saami_Kola ( ) 8.64
4 Bashkir ( ) 9.19
5 Chuvash ( ) 10.07
6 Komi ( ) 10.95
7 Udmurd ( ) 11.28
8 Saami ( ) 11.32
9 Chuvashs ( ) 11.5
10 Karelian ( ) 13.52
11 Finn ( ) 14.5
12 Tatar ( ) 14.66
13 Finn_East ( ) 15.5
14 Vepsa ( ) 15.88
15 Finnish-East ( ) 15.9
16 Tatar-Siberian ( ) 16.06
17 Tatar_Kryashen ( ) 16.14
18 Russian-Ural ( ) 16.42
19 Finnish_FIN ( ) 16.67
20 Tatar_Mishar ( ) 17.28
Mixed Mode Population Sharing:
# Primary Population (source) Secondary Population (source) Distance
1 89.2% Saami_Finland ( ) + 10.8% Tajik_Pomiri_Rushan ( ) @ 2.47
2 60.8% Saami ( ) + 39.2% Tatar_Mishar ( ) @ 2.49
3 89.4% Saami_Finland ( ) + 10.6% Tajik_Pomiri_Shugnan ( ) @ 2.56
4 88.6% Saami_Finland ( ) + 11.4% Tajik_Afghan ( ) @ 2.58
5 90.3% Saami_Finland ( ) + 9.7% Tajik_Yagnobi ( ) @ 2.68
6 89.3% Saami_Finland ( ) + 10.7% Uzbek_Afghan ( ) @ 2.68
7 64.3% Saami ( ) + 35.7% Tatar-Kazan ( ) @ 2.68
8 65.6% Saami ( ) + 34.4% Erzya ( ) @ 2.69
9 69.9% Saami ( ) + 30.1% Moksha ( ) @ 2.69
10 71.3% Saami ( ) + 28.7% Mordovian ( ) @ 2.76
11 90.1% Saami_Finland ( ) + 9.9% Tajik_Pomiri_Ishkashim ( ) @ 2.77
12 91% Saami_Finland ( ) + 9% Afghan_Pushtun ( ) @ 2.81
13 64.3% Saami ( ) + 35.7% Russian-North ( ) @ 2.83
14 91.1% Saami_Finland ( ) + 8.9% Pashtun_Afghani ( ) @ 2.88
15 87% Saami_Finland ( ) + 13% Turkmen_Uzbekistan ( ) @ 2.89
16 74.6% Saami ( ) + 25.4% Don_cossack ( ) @ 2.92
17 73.6% Saami ( ) + 26.4% Belarusian_South ( ) @ 2.93
18 66.9% Saami ( ) + 33.1% Russian_Vologda ( ) @ 2.94
19 73.3% Saami ( ) + 26.7% Russian_Center ( ) @ 2.95
20 70.5% Saami ( ) + 29.5% Russian_Meshtchyora ( ) @ 2.95
Thoughts? I would like to see his G25 results. I wonder would he be genetically closer to the Saami or Saami_Kola samples. And its fascinating that he doesn't show any Siberian influence in his pheno despite being at least 20% Mongoloid.
I made a classification thread for him: https://www.theapricity.com/forum/showthread.php?342915-Guess-and-classify-this-man-Can-he-pass-anywhere-in-Northern-Europe
And its fascinating to here several people think he looks Bavarian lol.
He looks Northern European. Wouldn't stand out among Germanic Scandinavians at all.
Please post his Dod K12b components.
Zanzibar
02-24-2021, 09:52 AM
He looks Northern European. Wouldn't stand out as a Germanic Scandinavian at all.
Please post his Dod K12b components.
Are you a bit flabbergasted he didn't show any Siberian influence in his pheno despite being more than 20% Mongoloid?
Wait a bit. On my phone right now so hard to post.
Yes and no. I'm aware of the fact that many Sami look barely different from other Scandinavians and Finns. On the other hand sometimes even a smaller East Eurasian percentage will be manifest in the phenotype.
Zanzibar
02-24-2021, 10:20 AM
Yes and no. I'm aware of the fact that many Sami look barely different from other Scandinavians and Finns. On the other hand sometimes even a smaller East Eurasian percentage will be manifest in the phenotype.
Interesting. I wonder is that due to recent Germanic admixture? But OP results seem to prove that Saamis can look like othernNorthern European without recent Nordic ancestry
Btw do you think the S Asian is scoring is authentic or some type of East or West Eurasian affinity?
Blondie
02-24-2021, 10:22 AM
What is "Archaic_Human"?
Peterski
02-24-2021, 10:29 AM
Can you post his Eurogenes K36 Admixture Percentages?
Zanzibar
02-24-2021, 10:30 AM
What is "Archaic_Human"?
Probably Neanderthal or some type of ancient hominid.
I've yet to see his Dod K12b...
Zanzibar
02-24-2021, 10:36 AM
I've yet to see his Dod K12b...
I will post. Right now still on my phone.
Zanzibar
02-24-2021, 11:06 AM
I've yet to see his Dod K12b...
Here it is:
Admix Results (sorted):
# Population Percent
1 North_European 59.37
2 Siberian 18.29
3 Atlantic_Med 11.62
4 Gedrosia 6.72
5 East_Asian 3.48
6 South_Asian 0.52
Single Population Sharing:
# Population (source) Distance
1 Chuvashs (Behar) 12.17
2 Russian (HGDP) 16.31
3 Mordovians (Yunusbayev) 18.06
4 FIN30 (1000Genomes) 19.01
5 Finnish (Dodecad) 20.76
6 Russian (Dodecad) 21.26
7 Russian_B (Behar) 22.96
8 Mixed_Slav (Dodecad) 23.4
9 Polish (Dodecad) 25.14
10 Ukranians (Yunusbayev) 25.34
11 Belorussian (Behar) 25.36
12 Lithuanian (Dodecad) 26.35
13 Lithuanians (Behar) 27.51
14 Swedish (Dodecad) 27.84
15 Hungarians (Behar) 29.88
16 Norwegian (Dodecad) 29.9
17 German (Dodecad) 31.28
18 Dutch (Dodecad) 35.23
19 Mixed_Germanic (Dodecad) 35.53
20 Orkney (1000Genomes) 36.79
Mixed Mode Population Sharing:
# Primary Population (source) Secondary Population (source) Distance
1 82.5% FIN30 (1000Genomes) + 17.5% Yakut (HGDP) @ 5.91
2 82.7% FIN30 (1000Genomes) + 17.3% Yukagir (Rasmussen) @ 6.25
3 83.5% FIN30 (1000Genomes) + 16.5% Evenk (Rasmussen) @ 6.38
4 81.4% FIN30 (1000Genomes) + 18.6% Dolgan (Rasmussen) @ 6.52
5 77.5% FIN30 (1000Genomes) + 22.5% Ket (Rasmussen) @ 6.57
6 76.1% FIN30 (1000Genomes) + 23.9% Selkup (Rasmussen) @ 6.65
7 81.2% Finnish (Dodecad) + 18.8% Yakut (HGDP) @ 6.67
8 79.4% FIN30 (1000Genomes) + 20.6% Tuva (Rasmussen) @ 6.72
9 77% FIN30 (1000Genomes) + 23% Altai (Rasmussen) @ 6.86
10 81.5% Finnish (Dodecad) + 18.5% Yukagir (Rasmussen) @ 7.03
11 82.3% Finnish (Dodecad) + 17.7% Evenk (Rasmussen) @ 7.23
12 80.1% Finnish (Dodecad) + 19.9% Dolgan (Rasmussen) @ 7.3
13 75.4% Finnish (Dodecad) + 24.6% Altai (Rasmussen) @ 7.39
14 77.9% Finnish (Dodecad) + 22.1% Tuva (Rasmussen) @ 7.39
15 76% Finnish (Dodecad) + 24% Ket (Rasmussen) @ 7.44
16 74.5% Finnish (Dodecad) + 25.5% Selkup (Rasmussen) @ 7.52
17 80.7% FIN30 (1000Genomes) + 19.3% Buryat (Rasmussen) @ 7.73
18 68.2% Lithuanians (Behar) + 31.8% Selkup (Rasmussen) @ 7.85
19 69.9% Lithuanians (Behar) + 30.1% Ket (Rasmussen) @ 7.86
20 85.7% FIN30 (1000Genomes) + 14.3% Nganassan (Rasmussen) @ 7.96
His PuntDNA K13 Modern in case you are interested:
Admix Results (sorted):
# Population Percent
1 NE_Europe 63.99
2 Siberia 17.36
3 SW_Europe 6.53
4 West_Asia 3.63
5 NE_Asia 2.63
6 Americas 2.25
7 South_Asia 1.3
8 South_Africa 0.61
9 East_Africa 0.53
10 SW_Asia 0.48
11 SE_Asia 0.28
12 Oceania 0.28
13 West_Africa 0.13
Single Population Sharing:
# Population (source) Distance
1 Finnish 14
2 Chuvash 18.36
3 Mordovian 18.58
4 Russian 19.21
5 Aluet 20.51
6 Latvian 21.53
7 Lithuanian 22
8 Estonian 22.39
9 Polish 23.64
10 Tatar 24.43
11 Belarusian 25.15
12 Ukrainian 28.97
13 Swedish 29.71
14 Norwegian 31.17
15 German_North 31.83
16 Slovak 32.59
17 Slovene 34.27
18 Utahn_European 34.51
19 Irish 35.02
20 Moldavian 35.34
Mixed Mode Population Sharing:
# Primary Population (source) Secondary Population (source) Distance
1 79.8% Finnish + 20.2% Selkup @ 5.86
2 86.1% Finnish + 13.9% Koryak @ 6.48
3 85.3% Finnish + 14.7% Dolgan @ 6.72
4 86.7% Finnish + 13.3% Yakut @ 6.76
5 86.5% Finnish + 13.5% Chukchi @ 6.78
6 88.4% Finnish + 11.6% Nganasan @ 6.98
7 85% Finnish + 15% Tuvinian @ 7.65
8 86.9% Finnish + 13.1% Eskimo @ 7.83
9 83.8% Finnish + 16.2% Altaian @ 8.21
10 85.7% Finnish + 14.3% Mongolian @ 8.72
11 87.5% Finnish + 12.5% Oroqen @ 8.89
12 59.9% Finnish + 40.1% Chuvash @ 9.04
13 63.5% Finnish + 36.5% Aluet @ 9.25
14 88.6% Finnish + 11.4% Daur @ 9.77
15 89.8% Finnish + 10.2% Xibo @ 10.53
16 85.7% Finnish + 14.3% Afghan_Hazara @ 10.6
17 72.7% Latvian + 27.3% Selkup @ 11.07
18 72% Finnish + 28% Tatar @ 11.16
19 91.5% Finnish + 8.5% Naxi @ 11.61
20 92.1% Finnish + 7.9% Japanese @ 11.67
Here is what he look like.
Eurogenes K13: He has at least 22% East Eurasian (Siberian+Amerindian) ancestry. I'm not sure is the South Asian that he is scoring genuine or some other type of East Eurasian or West Eurasian ancestry.
Admix Results (sorted):
# Population Percent
1 Baltic 42.9
2 North_Atlantic 29.64
3 Siberian 18.55
4 Amerindian 3.88
5 South_Asian 3.18
6 West_Asian 1.64
7 Oceanian 0.19
8 Sub-Saharan 0.02
[spoiler]
Single Population Sharing:
# Population (source) Distance
1 East_Finnish 13.19
2 Chuvash 14.8
3 Finnish 14.94
4 Kargopol_Russian 15.97
5 Tatar 16.71
6 Mari 16.95
7 Southwest_Finnish 17.62
8 Erzya 17.68
9 Estonian 18.53
10 Southwest_Russian 20.73
11 Estonian_Polish 20.93
12 Belorussian 20.96
13 Russian_Smolensk 21.52
14 Ukrainian_Belgorod 21.9
15 Polish 22.02
16 Ukrainian 22.06
17 Lithuanian 22.14
18 Ukrainian_Lviv 22.24
19 La_Brana-1 22.28
20 South_Polish 22.29
Mixed Mode Population Sharing:
# Primary Population (source) Secondary Population (source) Distance
1 78.1% Finnish + 21.9% Ket @ 5.02
2 78.3% Finnish + 21.7% Selkup @ 5.08
3 85.1% East_Finnish + 14.9% Koryak @ 5.68
4 84.8% East_Finnish + 15.2% Chukchi @ 5.79
5 83.2% Finnish + 16.8% Koryak @ 5.92
6 81% East_Finnish + 19% Ket @ 5.94
7 83.9% Finnish + 16.1% Dolgan @ 6.16
8 81.3% East_Finnish + 18.7% Selkup @ 6.18
9 85.2% Finnish + 14.8% Evens @ 6.25
10 87.1% East_Finnish + 12.9% Evens @ 6.27
11 83% Finnish + 17% Chukchi @ 6.3
12 85.9% East_Finnish + 14.1% Dolgan @ 6.31
13 85% Finnish + 15% Evenki @ 6.41
14 86.9% East_Finnish + 13.1% Evenki @ 6.44
15 75.5% Southwest_Finnish + 24.5% Selkup @ 6.53
16 74.3% Estonian + 25.7% Ket @ 6.55
17 51.1% Mari + 48.9% Southwest_Finnish @ 6.59
18 74.5% Estonian + 25.5% Selkup @ 6.72
19 58.3% Mari + 41.7% North_Swedish @ 6.79
20 75.5% Southwest_Finnish + 24.5% Ket @ 6.8
PuntDNAL K12 Modern: He has very low Neolithic Farmer compared to most European results it seems. He is approximately 21-22% East Eurasian (Siberian+Beringian+Amerindian+Oceanian). Once again not sure if the minor South Asian he possess is East or West Eurasian. But if it is East Eurasian, he could be up to 23% Mongoloid.
Admix Results (sorted):
# Population Percent
1 European_HG 45.61
2 Caucasus_HG 17.28
3 Siberian 14.45
4 Anatolian_NF 13.37
5 Beringian 5.19
6 South_Asian 1.91
7 Amerindian 1.47
8 Oceanian 0.7
Single Population Sharing:
# Population (source) Distance
1 Chuvash 5.16
2 Russian 11.16
3 Mordovian 11.78
4 Finnish 14.31
5 Belarusian 18.89
6 Estonian 19.67
7 Lithuanian 20.48
8 Icelandic 21.63
9 Czech 22.11
10 Scottish_West 23.02
11 German_North 23.19
12 Dutch_North 23.32
13 Swedish 23.49
14 Hungarian 23.72
15 Norwegian 23.9
16 Irish 24.57
17 English_South 25.38
18 Dutch_South 25.71
19 Croatian 25.97
20 Utahn_European 26.79
Mixed Mode Population Sharing:
# Primary Population (source) Secondary Population (source) Distance
1 82.5% Russian + 17.5% Selkup @ 3.52
2 77.9% Chuvash + 22.1% Russian @ 4.25
3 79.8% Chuvash + 20.2% Mordovian @ 4.36
4 97.3% Chuvash + 2.7% Chukchi @ 4.42
5 87.8% Chuvash + 12.2% Belarusian @ 4.49
6 97.5% Chuvash + 2.5% Koryak @ 4.5
7 88.4% Chuvash + 11.6% Estonian @ 4.51
8 89.1% Chuvash + 10.9% Lithuanian @ 4.54
9 90.6% Chuvash + 9.4% Czech @ 4.64
10 85.9% Chuvash + 14.1% Finnish @ 4.66
11 90.7% Chuvash + 9.3% Icelandic @ 4.69
12 95.8% Chuvash + 4.2% Punjabi_Jatt_Sikh @ 4.69
13 91.4% Chuvash + 8.6% Dutch_North @ 4.69
14 91.4% Chuvash + 8.6% Scottish_West @ 4.7
15 94.1% Chuvash + 5.9% Tajik_Pomiri @ 4.7
16 91.4% Chuvash + 8.6% German_North @ 4.7
17 95.7% Chuvash + 4.3% Haryana_Jatt @ 4.71
18 91.7% Chuvash + 8.3% Hungarian @ 4.71
19 96.1% Chuvash + 3.9% Punjabi_Jatt_Muslim @ 4.71
20 95.9% Chuvash + 4.1% Pakistan_Pashtun @ 4.73
Gedrosia K12: He seems to have much lower EEF than other European results that I saw. Also he is around 20-21% Mongoloid (W_Siberian+E_Siberian+SE Asian+Indo-Tibetan).
Admix Results (sorted):
# Population Percent
1 SINTASHTA_STEPPE_HERDERS 47.17
2 EARLY_EUROPEAN_FARMERS 18.11
3 W_SIBERIAN 10.32
4 BALOCHI 5.97
5 E_SIBERIAN 5.69
6 CAUCASUS 5.05
7 SE_ASIAN 4.27
8 S_INDIAN 2.26
9 INDO_TIBETAN 1.16
Single Population Sharing:
# Population (source) Distance
1 Russian 16.83
2 Finnish 20.87
3 Norwegian 22.63
4 Estonian 26.13
5 Lithuanian 27.75
6 Turkmen_Afghan 38.05
7 Uzbek 38.39
8 Tajik_Pomiri 38.93
9 Greek 41.04
10 Tajik_Afghan 45.09
11 Uzbek_Afghan 45.21
12 Turks_Istanbul 45.88
13 Sicilian 46.62
14 Turks_Aydin 46.99
15 Turks_Balikesir 47.99
16 Pashtun_Afghan 49.24
17 Kurds_C 50.64
18 Kurds_N 51.82
19 Kurds_SE 52.35
20 Pathan 53.07
Mixed Mode Population Sharing:
# Primary Population (source) Secondary Population (source) Distance
1 65.3% Finnish + 34.7% Uzbek @ 5.25
2 65.1% Finnish + 34.9% Turkmen_Afghan @ 5.36
3 70.8% Russian + 29.2% Uzbek @ 6.23
4 70.7% Russian + 29.3% Turkmen_Afghan @ 6.54
5 60% Estonian + 40% Uzbek @ 6.85
6 79.9% Russian + 20.1% Yukagir @ 7.19
7 59.8% Estonian + 40.2% Turkmen_Afghan @ 7.25
8 58.5% Lithuanian + 41.5% Uzbek @ 7.36
9 82.7% Russian + 17.3% Ulchi @ 7.52
10 58.3% Lithuanian + 41.7% Turkmen_Afghan @ 7.83
11 69.7% Finnish + 30.3% Tajik_Afghan @ 8
12 69.8% Finnish + 30.2% Uzbek_Afghan @ 8.05
13 75.4% Russian + 24.6% Uzbek_Afghan @ 8.59
14 75.4% Russian + 24.6% Tajik_Afghan @ 8.65
15 83.7% Russian + 16.3% Mongola @ 9.56
16 69.8% Lithuanian + 30.2% Yukagir @ 9.83
17 71.3% Estonian + 28.7% Yukagir @ 9.98
18 79.6% Finnish + 20.4% Ulchi @ 10.04
19 79.4% Russian + 20.6% Kurds_SE @ 10.25
20 76.8% Finnish + 23.2% Yukagir @ 10.28
MDLP K23b: Not sure if the Ancestral Altaic is hiding some Mongoloid, but he is also approximately 21-22% Mongoloid here.
Admix Results (sorted):
# Population Percent
1 European_Hunters_Gatherers 45.99
2 East_Siberian 14.4
3 Ancestral_Altaic 13.29
4 Caucasian 12.9
5 South_Central_Asian 3.34
6 Tungus-Altaic 2.83
7 European_Early_Farmers 2.35
8 Amerindian 1.69
9 Paleo_Siberian 1.05
10 Arctic 1.02
11 South_Indian 0.57
12 Austronesian 0.25
13 Australoid 0.18
14 Archaic_Human 0.13
Single Population Sharing:
# Population (source) Distance
1 Saami_Finland ( ) 4.84
2 Mari ( ) 7.58
3 Saami_Kola ( ) 8.64
4 Bashkir ( ) 9.19
5 Chuvash ( ) 10.07
6 Komi ( ) 10.95
7 Udmurd ( ) 11.28
8 Saami ( ) 11.32
9 Chuvashs ( ) 11.5
10 Karelian ( ) 13.52
11 Finn ( ) 14.5
12 Tatar ( ) 14.66
13 Finn_East ( ) 15.5
14 Vepsa ( ) 15.88
15 Finnish-East ( ) 15.9
16 Tatar-Siberian ( ) 16.06
17 Tatar_Kryashen ( ) 16.14
18 Russian-Ural ( ) 16.42
19 Finnish_FIN ( ) 16.67
20 Tatar_Mishar ( ) 17.28
Mixed Mode Population Sharing:
# Primary Population (source) Secondary Population (source) Distance
1 89.2% Saami_Finland ( ) + 10.8% Tajik_Pomiri_Rushan ( ) @ 2.47
2 60.8% Saami ( ) + 39.2% Tatar_Mishar ( ) @ 2.49
3 89.4% Saami_Finland ( ) + 10.6% Tajik_Pomiri_Shugnan ( ) @ 2.56
4 88.6% Saami_Finland ( ) + 11.4% Tajik_Afghan ( ) @ 2.58
5 90.3% Saami_Finland ( ) + 9.7% Tajik_Yagnobi ( ) @ 2.68
6 89.3% Saami_Finland ( ) + 10.7% Uzbek_Afghan ( ) @ 2.68
7 64.3% Saami ( ) + 35.7% Tatar-Kazan ( ) @ 2.68
8 65.6% Saami ( ) + 34.4% Erzya ( ) @ 2.69
9 69.9% Saami ( ) + 30.1% Moksha ( ) @ 2.69
10 71.3% Saami ( ) + 28.7% Mordovian ( ) @ 2.76
11 90.1% Saami_Finland ( ) + 9.9% Tajik_Pomiri_Ishkashim ( ) @ 2.77
12 91% Saami_Finland ( ) + 9% Afghan_Pushtun ( ) @ 2.81
13 64.3% Saami ( ) + 35.7% Russian-North ( ) @ 2.83
14 91.1% Saami_Finland ( ) + 8.9% Pashtun_Afghani ( ) @ 2.88
15 87% Saami_Finland ( ) + 13% Turkmen_Uzbekistan ( ) @ 2.89
16 74.6% Saami ( ) + 25.4% Don_cossack ( ) @ 2.92
17 73.6% Saami ( ) + 26.4% Belarusian_South ( ) @ 2.93
18 66.9% Saami ( ) + 33.1% Russian_Vologda ( ) @ 2.94
19 73.3% Saami ( ) + 26.7% Russian_Center ( ) @ 2.95
20 70.5% Saami ( ) + 29.5% Russian_Meshtchyora ( ) @ 2.95
Thoughts? I would like to see his G25 results. I wonder would he be genetically closer to the Saami or Saami_Kola samples. And its fascinating that he doesn't show any Siberian influence in his pheno despite being at least 20% Mongoloid.
I made a classification thread for him: https://www.theapricity.com/forum/showthread.php?342915-Guess-and-classify-this-man-Can-he-pass-anywhere-in-Northern-Europe
And its fascinating to here several people think he looks Bavarian lol.
When are you guys going to learn that calculator Siberian is relative Siberian NOT ABSOLUTE Siberian.We can make the same person 0% Siberian or 20% Siberian just by carefully picking the calculator references or components. 23andme and Ancestry dna do it to also
For example if I wanted to reduce his Siberian I would have add alot of calculator components or references from Finland, Estonia, Norway etc. I mean we do the same thing with W. Asians. We reduce their Siberian or E. Asian by having alot of references from Georgia, Armenia, Arabs etc.
So I’m not surprised at all. If you want to measure his ABSOLUTE Siberian do FST or IBS between him , a bunch of Europeans and W. Asians vs some Siberian pop and show me how far down the list he ranks. That would better explain someone’s looks.
Mopi The Dire Wolf
02-24-2021, 11:07 AM
is the siberian/east asian admix in saami far enough back that it predates "classic" mongoloid phenotype ?
Just ignore fucking Zoro here, he's a fucking tireless campagner against admixture calculators.
Zanzibar
02-24-2021, 11:10 AM
When are you guys going to learn that calculator Siberian is relative Siberian NOT ABSOLUTE Siberian.We can make the same person 0% Siberian or 20% Siberian just by carefully picking the calculator references or components. 23andme and Ancestry dna do it to also
For example if I wanted to reduce his Siberian I would have add alot of calculator components or references from Finland, Estonia, Norway etc. I mean we do the same thing with W. Asians. We reduce their Siberian or E. Asian by having alot of references from Georgia, Armenia, Arabs etc.
So I’m not surprised at all. If you want to measure his ABSOLUTE Siberian do FST or IBS between him , a bunch of Europeans and W. Asians vs some Siberian pop and show me how far down the list he ranks. That would better explain someone’s looks.
Ok. How to do an FST or IBS of his results then?
Btw can you please unquote his pics in the spoiler please? Plan to delete them later.
Here it is:
Admix Results (sorted):
# Population Percent
1 North_European 59.37
2 Siberian 18.29
3 Atlantic_Med 11.62
4 Gedrosia 6.72
5 East_Asian 3.48
6 South_Asian 0.52
His South Asian from EU K13 doesn't seem genuine. It's below 1% on Dodecad. Yep, the guy is like 21-22% East Eurasian, quite a lot. Very archaic genetic profile, no apparent Norwegian ancestry.
Zanzibar
02-24-2021, 11:14 AM
Can you post his Eurogenes K36 Admixture Percentages?
Here is OP's result:
Population
Amerindian 1.93 Pct
Arabian -
Armenian -
Basque -
Central_African -
Central_Euro 0.09 Pct
East_African -
East_Asian -
East_Balkan -
East_Central_Asian -
East_Central_Euro 3.13 Pct
East_Med -
Eastern_Euro 9.6 Pct
Fennoscandian 57.12 Pct
French -
Iberian -
Indo-Chinese -
Italian -
Malayan -
Near_Eastern -
North_African -
North_Atlantic 2.59 Pct
North_Caucasian -
North_Sea 3.03 Pct
Northeast_African -
Oceanian -
Omotic -
Pygmy -
Siberian 14.75 Pct
South_Asian -
South_Central_Asian 0.63 Pct
South_Chinese -
Volga-Ural 7.12 Pct
West_African -
West_Caucasian -
West_Med -
Also his MDLP K16 in case you are interested. Interesting how OP is genetically closer to Uralics than to his fellow Scandinavians (except for Finns).
Admix Results (sorted):
# Population Percent
1 NorthEastEuropean 33.43
2 Steppe 21.18
3 Siberian 15.52
4 Neolithic 12.5
5 Caucasian 8.34
6 Indian 3.55
7 Arctic 3.14
8 Amerindian 1.69
9 Australian 0.53
10 Oceanic 0.12
Single Population Sharing:
# Population (source) Distance
1 Saami (Finnmark) 7
2 Saami_WGA (Lapland) 8.45
3 Komi (Komi_Republic) 8.98
4 Russian (NorthRussia) 9.53
5 Chuvash (Chuvashia) 10.45
6 Russian (Pinega) 10.75
7 Vepsa (Russia) 10.93
8 Finn (NorthFinland) 11.49
9 Mari (Mari_El) 11.57
10 Finn (EastFinland) 11.77
11 Karelian (Karelia) 11.8
12 Finn (Kuusamo) 12.32
13 Udmurd (Udmurtia) 12.48
14 Finn (SouthFinland) 13.13
15 Finn (Finland) 13.4
16 Russian (Russia) 13.85
17 Mishar-Tatar (Mordovia) 14.19
18 Kryashen (Bashkortostan) 14.28
19 Ingrians (Ingermanland) 14.45
20 Russian (Kostroma) 14.57
Mixed Mode Population Sharing:
# Primary Population (source) Secondary Population (source) Distance
1 62.6% Latvian_Dobele (Dobele) + 37.4% Mansi (Khanty–Mansi) @ 3.33
2 63.6% Estonian (Estonia) + 36.4% Mansi (Khanty–Mansi) @ 3.96
3 72.4% Finn (EastFinland) + 27.6% Mansi (Khanty–Mansi) @ 4.12
4 62.1% Latvian (Latvia) + 37.9% Mansi (Khanty–Mansi) @ 4.23
5 66.5% Saami (Finnmark) + 33.5% Finn (EastFinland) @ 4.31
6 66.6% Latvian_Dobele (Dobele) + 33.4% Selkup ((Yamalo_Nenets_okrug)) @ 4.47
7 75.4% Saami (Finnmark) + 24.6% Latvian_Cesis (Cesis) @ 4.49
8 67.7% Ingrians (Ingermanland) + 32.3% Mansi (Khanty–Mansi) @ 4.5
9 61% Saami (Finnmark) + 39% Russian (NorthRussia) @ 4.51
10 77.5% Russian (NorthRussia) + 22.5% Mansi (Khanty–Mansi) @ 4.53
11 63.6% Latvian_Cesis (Cesis) + 36.4% Mansi (Khanty–Mansi) @ 4.58
12 76.3% Saami (Finnmark) + 23.7% Latvian_Dobele (Dobele) @ 4.6
13 72.6% Karelian (Karelia) + 27.4% Mansi (Khanty–Mansi) @ 4.67
14 63.6% Latvian_Dobele (Dobele) + 36.4% Khanty (Khanty–Mansi) @ 4.69
15 74.4% Vepsa (Russia) + 25.6% Mansi (Khanty–Mansi) @ 4.69
16 72.6% Saami (Finnmark) + 27.4% Ingrians (Ingermanland) @ 4.73
17 76.1% Saami (Finnmark) + 23.9% Estonian (Estonia) @ 4.76
18 65.6% Saami (Finnmark) + 34.4% Russian (Pinega) @ 4.87
19 76% Finn (EastFinland) + 24% Selkup ((Yamalo_Nenets_okrug)) @ 4.88
20 68.7% Latvian_Dobele (Dobele) + 31.3% Ket (Krasnoyarski_Krai) @ 4.9
Just ignore fucking Zoro here, he's a fucking tireless campagner against admixture calculators.
Did you even fucking read what i said you moron ??
I didn’t say I’m against calculators I said we can make someone 0% or 20% Siberian by carefully picking calculator references and if you want to see how much Absolute Siberian he has do some fucking FST or IBS him/Europeans/W Asians VS Siberians and fucking show me the results. This would explain his caucasian looks better
Read before opening your trap !!
Did you even fucking read what i said you moron ??
I didn’t say I’m against calculators I said we can make someone 0% or 20% Siberian by carefully picking calculator references and if you want to see how much Absolute Siberian he has do some fucking FST or IBS him/Europeans/W Asians VS Siberians and fucking show me the results. This would explain his caucasian looks better
Read before opening your trap !!
LOL, okay. I don't think Joqool is able to do that though.
Here is OP's result:
Add Harappa too. It has the Beringian component.
Ok. How to do an FST or IBS of his results then?
Btw can you please unquote his pics in the spoiler please? Plan to delete them later.
Done. Sorry don’t have time to teach but Plink has a feature using —genome flag.
You can do IBS based on older alleles as well as more recent alleles/ancestry
Hungarian_master
02-24-2021, 11:19 AM
Probably Neanderthal or some type of ancient hominid.
I think so that!
I think so that!
POST YOUR OWN GEDMATCH! IT'S LONG OVERDUE!
Immanenz
02-24-2021, 11:32 AM
Probably Neanderthal or some type of ancient hominid.
He looks a bit like Günther´s East Baltid example
( Fenno-Nordid is Günther's type which corresponds to East Baltid. Günther gave this Mordvin man as an example of the Fenno-Nordid type (https://www.theapricity.com/earlson/race/nordish.htm): )
https://www.theapricity.com/earlson/race/imgs/273a.jpghttps://www.theapricity.com/earlson/race/imgs/273b.jpg
Zanzibar
02-24-2021, 11:40 AM
Add Harappa too. It has the Beringian component.
Here. Its strange OP has quite a decent amount of Baloch though...
Admix Results (sorted):
# Population Percent
1 NE-Euro 65.25
2 Siberian 15.33
3 Baloch 6.24
4 Mediterranean 5.39
5 Beringian 3.98
6 American 2.03
7 SE-Asian 1.27
8 Papuan 0.2
9 NE-Asian 0.2
10 San 0.08
11 Pygmy 0.04
Single Population Sharing:
# Population (source) Distance
1 russian (hgdp) 12.18
2 mordovian (yunusbayev) 14.77
3 chuvash (behar) 15.73
4 finnish (1000genomes) 18.08
5 russian (behar) 18.7
6 lithuanian (behar) 19.12
7 belorussian (behar) 20.02
8 ukranian (yunusbayev) 22.21
9 slovenian (xing) 29.1
10 hungarian (behar) 30.46
11 n-european (xing) 30.53
12 utahn-white (hapmap) 31.23
13 orcadian (hgdp) 32.39
14 utahn-white (1000genomes) 33.05
15 british (1000genomes) 33.66
16 french (hgdp) 39.99
17 romanian-a (behar) 41.65
18 bulgarian (yunusbayev) 43.22
19 selkup (rasmussen) 50.11
20 spaniard (behar) 50.82
Mixed Mode Population Sharing:
# Primary Population (source) Secondary Population (source) Distance
1 74.5% finnish (1000genomes) + 25.5% selkup (rasmussen) @ 6
2 77.1% finnish (1000genomes) + 22.9% ket (rasmussen) @ 6.4
3 54.1% chuvash (behar) + 45.9% finnish (1000genomes) @ 6.7
4 78.1% finnish (1000genomes) + 21.9% yukaghir (rasmussen) @ 7.05
5 81.8% finnish (1000genomes) + 18.2% dolgan (rasmussen) @ 8.17
6 83.5% finnish (1000genomes) + 16.5% yakut (hgdp) @ 8.28
7 84.4% finnish (1000genomes) + 15.6% evenki (rasmussen) @ 8.4
8 74.3% lithuanian (behar) + 25.7% selkup (rasmussen) @ 8.53
9 85.1% finnish (1000genomes) + 14.9% nganassan (rasmussen) @ 8.55
10 76.9% lithuanian (behar) + 23.1% ket (rasmussen) @ 8.75
11 79.1% finnish (1000genomes) + 20.9% altaian (rasmussen) @ 8.8
12 81.4% finnish (1000genomes) + 18.6% tuvinian (rasmussen) @ 8.95
13 86.5% russian (hgdp) + 13.5% selkup (rasmussen) @ 9.47
14 82.8% finnish (1000genomes) + 17.2% buryat (rasmussen) @ 9.54
15 88.2% russian (hgdp) + 11.8% ket (rasmussen) @ 9.59
16 84.6% lithuanian (behar) + 15.4% nganassan (rasmussen) @ 9.71
17 92.8% russian (hgdp) + 7.2% nganassan (rasmussen) @ 9.91
18 78.5% finnish (1000genomes) + 21.5% kazakh (harappa) @ 10.02
19 92.9% russian (hgdp) + 7.1% evenki (rasmussen) @ 10.26
20 91.7% russian (hgdp) + 8.3% dolgan (rasmussen) @ 10.29
Zanzibar
02-24-2021, 11:41 AM
He looks a bit like Günther´s East Baltid example
( Fenno-Nordid is Günther's type which corresponds to East Baltid. Günther gave this Mordvin man as an example of the Fenno-Nordid type (https://www.theapricity.com/earlson/race/nordish.htm): )
https://www.theapricity.com/earlson/race/imgs/273a.jpghttps://www.theapricity.com/earlson/race/imgs/273b.jpg
Are you a bit shock OP doesn't show any Mongoloid in his pheno?
Zanzibar
02-24-2021, 11:44 AM
Done. Sorry don’t have time to teach but Plink has a feature using —genome flag.
You can do IBS based on older alleles as well as more recent alleles/ancestry
Is there a video I can watch on how to do Plink?
Also how do you conduct an IBS run?
Here. Its strange OP has quite a decent amount of Baloch though...
Admix Results (sorted):
# Population Percent
1 NE-Euro 65.25
2 Siberian 15.33
3 Baloch 6.24
4 Mediterranean 5.39
5 Beringian 3.98
6 American 2.03
7 SE-Asian 1.27
8 Papuan 0.2
9 NE-Asian 0.2
10 San 0.08
Baloch is roughly the same thing as Gedrosia. His Mediterranean is super low for a European.
Minor south Asian admix on gedmatch is very common to score for various Uralic ethnicities. Must be something ancient. It's mostly but not fully west Eurasian component.
As for phenotype, he looks East Baltid and quite common north European.
RatCat
02-24-2021, 11:49 AM
What is "Archaic_Human"?
African
Zanzibar
02-24-2021, 11:54 AM
Baloch is roughly the same thing as Gedrosia. His Mediterranean is super low for a European.
Do Europeans in general also score Baloch/Gedrosia?
Yup, I guess it is also correlated with how significant his East Eurasian ancestry is (he is almost quapa level). He probably has very high Hunter Gatherer ancestry as well so that might be why.
What do Europeans score on average in the Med category?
Zanzibar
02-24-2021, 11:57 AM
His South Asian from EU K13 doesn't seem genuine. It's below 1% on Dodecad. Yep, the guy is like 21-22% East Eurasian, quite a lot. Very archaic genetic profile, no apparent Norwegian ancestry.
Yup. He is almost like 1/4 Asian aka quapa lol.
It makes me wonder how common or typical are OP's results among modern day Samis or are most already mixed with other Scandinavians?
Also I find it pretty fascinating that OP is genetically closer to Uralics than to other Northern Euros based on the population distance oracles.
Fascinating that he looks so European despite that result.
Do Europeans in general also score Baloch/Gedrosia?
Yup, I guess it is also correlated with how significant his East Eurasian ancestry is (he is almost quapa level). He probably has a lot of Hunter Gatherer ancestry as well so that might be why.
What do Europeans score on average in the Med category?
Yes, most would score at least 1-2%, Northwestern Europeans can exceed the 10% mark in some cases. I score 5% as a Russian for example.
He sure does have a shitload of Euro HG ancestry or whatever it's called.
Altaylı
02-24-2021, 12:00 PM
I don't believe in taxonomy, it's crap
Ajeje Brazorf
02-24-2021, 12:04 PM
Saami on Global25 has about 28% East Eurasian, Saami_Kola about 20%.
Zanzibar
02-24-2021, 12:37 PM
Saami on Global25 has about 28% East Eurasian, Saami_Kola about 20%.
Hmm is that the average? From what I remember that 28% East Eurasian score was what the most Eastern-shifted Saami individual score.
Zanzibar
02-24-2021, 12:42 PM
Saami on Global25 has about 28% East Eurasian, Saami_Kola about 20%.
Hmm is that the average? From what I remember that 28% East Eurasian score was what the most Eastern-shifted Saami individual score.
.
Zanzibar
02-24-2021, 12:54 PM
Yes, most would score at least 1-2%, Northwestern Europeans can exceed the 10% mark in some cases. I score 5% as a Russian for example.
He sure does have a shitload of Euro HG ancestry or whatever it's called.
That Baloch/Gedrosia affinity is likely ANE (Balochis score loads of ANE like a lot of other South/Central Asians) or Steppe ancestry?
Its probably EHG or SHG.
Zanzibar
02-24-2021, 12:59 PM
Fascinating that he looks so European despite that result.
Ikr? It proves that genome isn't always equal to phenotype.
For example, I find it interesting that some think OP looks German (Bavarian) despite him having very high Mongoloid: https://www.theapricity.com/forum/showthread.php?342915-Guess-and-classify-this-man-Can-he-pass-anywhere-in-Northern-Europe&p=7121165&viewfull=1#post7121165
Zanzibar
02-24-2021, 01:02 PM
is the siberian/east asian admix in saami far enough back that it predates "classic" mongoloid phenotype ?
Plausibly. I was initially startled that OP look just like any regular Northern/Western Euro despite his genomes.
Peterski
02-24-2021, 01:13 PM
Here is OP's result:
His closest regional populations from my database:
[1] "1. CLOSEST SINGLE ITEM DISTANCE%"
NO_Norway-Kvalsund
0.3882795
RUS_Murmansk-Sami
0.5260637
SE_Swedish-Lapland
0.6663490
FIN_Finland-Lapland
0.8350611
(...)
Zanzibar
02-24-2021, 01:21 PM
His closest regional populations from my database:
[1] "1. CLOSEST SINGLE ITEM DISTANCE%"
NO_Norway-Kvalsund
0.3882795
RUS_Murmansk-Sami
0.5260637
SE_Swedish-Lapland
0.6663490
FIN_Finland-Lapland
0.8350611
(...)
Kvalsund from Norway are also ethnic Saamis? Can you do a run whether he is genetically closer to other Uralics or to his fellow Germanic Scandinavians?
On Dodecad he is not close to any group but the Komi come up as the closest one albeit at 10.44
Distance to: Sami_Norway
10.44483604 Komi
11.64055411 Russian_Arkhangelsk
12.78203818 Veps
13.77867918 Russian_Ural
14.65609771 Finnish_East
14.76881173 Karelian
15.59399564 Chuvash
15.90497721 Mari
15.99749355 North_Russian
16.20806281 Udmurt
16.55447976 Russian_Kostroma
17.08046252 Finnish_West
17.97422877 Mordovian
18.22346564 Besermyan_Udmurtia
19.70894721 Tatar_Mishar
20.59968932 Estonian
20.71540007 Russian_Tver
21.00283076 Russian_Ryazan
21.64232196 Bashkir_North
21.64613129 Tatar_Kazan
An ethnic Norwegian by the way
https://www.theapricity.com/forum/showthread.php?321879-Norwegian-DNA-results
Zanzibar
02-24-2021, 01:42 PM
Closest pop to the OP using MDLP K23b Vahaduo:
Distance to: Saami_Norway
5.26792179 Saami_Finland
8.53834879 Komi
8.96575708 Saami_Kola
9.35690654 Saami
12.02529002 Chuvash
12.42459255 Tatar_Kryashen
12.67366956 Russian-Ural
13.57508011 Tatar_Mishar
14.66863661 Finn_East
14.89823815 Chuvashs
14.90621682 Mari
15.07194745 Finnish-East
15.12768984 Tatar
16.34568750 Finn
16.90634792 Finnish_FIN
16.98953501 Karelian
17.24602853 Erzya
17.27058192 Russian-North
17.89743278 Tatar-Mishar
18.71911056 Tatar-Kazan
18.75427151 Russian_Vologda
18.77163019 Vepsa
19.62478790 Moksha
19.86818562 Finn_West
20.01327310 Russian-Upper-Volga
His result using MDLP K23b:
Target: Saami_Norway
Distance: 2.1333% / 2.13326690
73.5 Karelian
14.0 Mansi
8.1 Selkup
1.9 Kalash
1.7 Ulchi
0.6 Surui
0.2 Tubalar
When removing the Saami samples:
Target: Saami_Norway
Distance: 2.1333% / 2.13326690
73.5 Karelian
14.0 Mansi
8.1 Selkup
1.9 Kalash
1.7 Ulchi
0.6 Surui
0.2 Tubalar
Closest pop to OP using MDLP K16 Vahaduo:
Distance to: Saami_Norway
7.52540364 Saami
8.14402849 Saami_Kola
9.29290590 Saami_WGA
9.96212829 Komi
10.23065003 Russians-North
11.73603425 Russian_Pinega
11.76895068 Chuvash
11.83533269 Russian-Ural
12.06466742 Finland_North
12.49917197 Karelian
12.51251773 Finn-East
12.60359373 Maris
12.90173632 Vepsa
13.12140617 Chuvash-Viryal
13.13800213 Finnish
13.44244769 Chuvash-Anatri
13.73197000 Finland_South
13.77766671 Udmurd
14.31824710 Finnish_FIN
14.41581423 Finnish-Inkeri
14.93825960 Ingrians
15.28577443 Erzya
15.52125961 Russian_Kargopol
15.67784424 Russia_Archangelsk
15.70380846 Russian_Kostroma
His model using MDLP K16 vahaduo:
Target: Saami_Norway
Distance: 2.4167% / 2.41672573
41.4 Finnish-Inkeri
23.7 Mansi
16.3 Lithuanian_Aukstajtia
11.2 Saami_WGA
4.9 Tubalar
2.2 GujaratiC_GIH
0.3 Punjabi_Lahore_PJL
Peterski
02-24-2021, 01:43 PM
Kvalsund from Norway are also ethnic Saamis? Can you do a run whether he is genetically closer to other Uralics or to his fellow Germanic Scandinavians?
Yes also Saamis. He is closer to Uralics.
Zanzibar
02-24-2021, 01:47 PM
On Dodecad he is not close to any group but the Komi come up as the closest one albeit at 10.44
Distance to: Sami_Norway
10.44483604 Komi
11.64055411 Russian_Arkhangelsk
12.78203818 Veps
13.77867918 Russian_Ural
14.65609771 Finnish_East
14.76881173 Karelian
15.59399564 Chuvash
15.90497721 Mari
15.99749355 North_Russian
16.20806281 Udmurt
16.55447976 Russian_Kostroma
17.08046252 Finnish_West
17.97422877 Mordovian
18.22346564 Besermyan_Udmurtia
19.70894721 Tatar_Mishar
20.59968932 Estonian
20.71540007 Russian_Tver
21.00283076 Russian_Ryazan
21.64232196 Bashkir_North
21.64613129 Tatar_Kazan
An ethnic Norwegian by the way
https://www.theapricity.com/forum/showthread.php?321879-Norwegian-DNA-results
Thanks. I find it interesting. Here are the MDLP K16 distance run: Fascinating how OP is genetically much closer to Komi, Chuvash, Mari who live much more geographically farther away than to fellow Scandinavians (except Finns of course as they both shared East Eurasian admixture).
Distance to: Saami_Norway
9.96212829 Komi
11.73603425 Russian_Pinega
11.76895068 Chuvash
12.60359373 Maris
13.13800213 Finnish
13.77766671 Udmurd
17.93120743 Estonian
19.09442982 Latvian
20.37203291 Lithuanian
22.31627657 Norwegian
22.56370094 Swedish
23.95471561 Bashkir
Zanzibar
02-24-2021, 01:52 PM
Minor south Asian admix on gedmatch is very common to score for various Uralic ethnicities. Must be something ancient. It's mostly but not fully west Eurasian component.
As for phenotype, he looks East Baltid and quite common north European.
It could be some sort of ANE affinity since South Asians also have shitloads of ANE.
It shows genotype doesn't equal phenotype. Makes me wonder how typical/common are his results among modern day Samis or are most already admixed with Northern Germanics? But it seems like he doesn't have any recent Norwegian ancestry.
Zanzibar
02-24-2021, 02:10 PM
Yes also Saamis. He is closer to Uralics.
Here are the closest pops to the OP using PuntDNAL K12 Modern: Seems like he is genetically much closer to Chuvash (they seem to be genetically Uralic despite speaking a Turkic language) and Balts than to other Scandinavians (once again with the exception of Finns). Probably has to do with the fact that Baltics have the lowest amount of Neolithic in Europe after Uralics. Strange though that the Russian is second closest pop to him here, probably Northern Russian with some Mongoloid ancestry?
Would be nice if there were other Uralic pops in the spreadsheet so can we can get a better picture.
Distance to: Saami_Norway
5.42724608 Chuvash
11.66640476 Russian
12.41631991 Mordovian
14.97147287 Finnish
19.76170539 Belarusian
20.54543745 Estonian
21.39147026 Lithuanian
22.68711088 Icelandic
23.21605048 Czech
24.19617738 Scottish_West
24.38288334 German_North
24.52090944 Dutch_North
24.67600049 Swedish
24.96086938 Hungarian
25.11423899 Norwegian
25.84347113 Irish
26.71151437 English_South
27.08975821 Dutch_South
27.38658431 Croatian
28.22277449 Utahn_European
29.24816234 Romanian
29.64548870 German_South
29.94920700 Belgian
32.13292704 Bulgarian
33.64736245 French
Btw here is the model of him using PuntDNAL K12 Modern:
Target: Saami_Norway
Distance: 1.1231% / 1.12314402
49.4 Lithuanian
22.7 Selkup
11.7 Russian
6.2 Tajik_Pomiri
5.5 Estonian
3.0 Chukchi
0.9 Pathan
0.4 Haryana_Jatt
0.2 Papuan
The ancient version of his genomic modeling:
Target: Saami_Norway
Distance: 12.5305% / 12.53052820
59.5 Scythian_IA_I0247
17.2 Karelia_HG_I0061
10.8 Hungary_HG_I1507
6.8 Baalberge_MN_I0560
3.9 Ust_Ishim_DG
1.8 AnatolianNeolithic_I0745
While here is his model using a mix of ancient and modern pops:
Target: Saami_Norway
Distance: 226.4927% / 2.26492737
36.0 Motala12
18.0 Satsurblia_SATP
15.2 Nganasan
13.8 AnatolianNeolithic_I0745
11.6 Karelia_HG_I0061
5.4 Chukchi
And here is the closest ancient pops to him:
Distance to: Saami_Norway
17.79592650 Corded_Ware_Estonia_RISE00
18.25253407 Andronovo_SG_RISE505
19.14223080 Corded_Ware_Germany_I0103
19.81401019 Sintashta_MBA_RISE395
20.14832499 Srubnaya_I0232
20.21645369 Potapovka_I0419
20.66409930 Corded_Ware_Germany_I0104
21.75212633 BenzigerodeHeimburg_LN_I0059
21.96372009 Scythian_IA_I0247
22.35005593 Srubnaya_I0430
22.84086251 Sintashta_MBA_RISE_386
22.87957605 Bell_Beaker_Germany_I1549
22.95811403 Bell_Beaker_Czech_RISE569
23.70137127 Nordic_LN_SG_RISE97
24.94824643 Unetice_EBA_I0117
25.00709899 Afanasievo_SG_RISE511
25.07119862 Halberstadt_LBA_I0099
25.53575924 Alberstedt_LN_I0118
25.56863313 BattleAxe_Sweden_SG_RISE94
25.67459834 Yamnaya_Samara_I0443
26.03353606 Samara_Eneolithic_I0433
28.49008599 Yamnaya_Samara_I0231
31.38542655 Samara_HG_I0124
31.77617032 Vatya_SG_RISE479
31.79520404 Kostenki14_UP_SG
Would be great to see OP's G25 results. Want to see whether he is closer to the Saami or Saami_Kola from Russia.
Zanzibar
02-24-2021, 02:12 PM
On Dodecad he is not close to any group but the Komi come up as the closest one albeit at 10.44
Distance to: Sami_Norway
10.44483604 Komi
11.64055411 Russian_Arkhangelsk
12.78203818 Veps
13.77867918 Russian_Ural
14.65609771 Finnish_East
14.76881173 Karelian
15.59399564 Chuvash
15.90497721 Mari
15.99749355 North_Russian
16.20806281 Udmurt
16.55447976 Russian_Kostroma
17.08046252 Finnish_West
17.97422877 Mordovian
18.22346564 Besermyan_Udmurtia
19.70894721 Tatar_Mishar
20.59968932 Estonian
20.71540007 Russian_Tver
21.00283076 Russian_Ryazan
21.64232196 Bashkir_North
21.64613129 Tatar_Kazan
An ethnic Norwegian by the way
https://www.theapricity.com/forum/showthread.php?321879-Norwegian-DNA-results
Wow its crazy how OP is so different from an ethnic Norwegian despite living in the same country and not that geographically distant from one another. Tbh, it makes me think that Samis are Europe's genetically most unique population, maybe even more than Sardinians and Basques.
Btw do you want his Gedmatch kit? I can PM you.
Hungarian_master
02-24-2021, 02:45 PM
POST YOUR OWN GEDMATCH! IT'S LONG OVERDUE!
I don't want it, yet.
Wow its crazy how OP is so different from an ethnic Norwegian despite living in the same country and not that geographically distant from one another. Tbh, it makes me think that Samis are Europe's genetically most unique population, maybe even more than Sardinians and Basques.
Btw do you want his Gedmatch kit? I can PM you.
Nah, you've posted all the relevant calculators, maybe except for EUtest and Euro K15.
By the way, just recently I got a Russian kit, the girl looks far more ching-chong than the OP, even though she's like 5-6% Mongoloid only. I can only imagine what The Apricity would say about her... :rolleyes:
I don't want it, yet.
That's selfish of you. You're on an internet forum and multiple people including your countrymen have asked you to share your results.
Is there a video I can watch on how to do Plink?
Also how do you conduct an IBS run?
I don’t know of any video. It’ll take me alot longer to teach you than just do you a favor and run it myself. You’re in luck my database has 2 Saami samples (i’ll check where they’re from). I’ll run them and a bunch of Europeans and Asians against Chukchi and some other N Asians and post the results here in a couple of hours
Ajeje Brazorf
02-24-2021, 05:39 PM
Hmm is that the average? From what I remember that 28% East Eurasian score was what the most Eastern-shifted Saami individual score.
Yes, the average.
Ajeje Brazorf
02-24-2021, 06:15 PM
Nah, you've posted all the relevant calculators, maybe except for EUtest and Euro K15.
By the way, just recently I got a Russian kit, the girl looks far more ching-chong than the OP, even though she's like 5-6% Mongoloid only. I can only imagine what The Apricity would say about her... :rolleyes:
The East Eurasian of Russians is of local Finno-Ugric origin, different from East Asians.
<colgroup><col><col></colgroup><tbody>
Sample
% East Eurasian
Russian_Pinega
11,2
Russian_Kostroma
7,4
Russian_Tver
3,4
Russian_Kursk
2
Russian_Orel
1,6
Russian_Smolensk
1,6
Russian_Voronez
1,4
</tbody>
I don’t know of any video. It’ll take me alot longer to teach you than just do you a favor and run it myself. You’re in luck my database has 2 Saami samples (i’ll check where they’re from). I’ll run them and a bunch of Europeans and Asians against Chukchi and some other N Asians and post the results here in a couple of hours
Here's the IBS for Finland Saami and Chukchi
Plink calculates IBS as (IBS2 + 0.5*IBS1) / (IBS0 + IBS1 + IBS2) meaning the more positions where the target and the population compared match both alleles at a position (IBS2) the higher the IBS score. What this means is since you get 1 allele from each parent that if BOTH your dad's allele and mom's allele match Saami or Chukchi at every position you get a higher IBS score
The first set of results for CHUKCHI is without removing really ancient common alleles (very ancient ancestry) from the calculation
<style type="text/css">td {border: 1px solid #ccc;}br {mso-data-placement:same-cell;}</style>
<tbody>
615K SNPs - Max-Maf 0.5 - Chukchi
POPULATION
IBS
Eskimo_Sireniki.DG
0.7921
Eskimo_Naukan.DG
0.7914
Itelmen
0.7911
Mansi
0.7873
Kyrgyz_Kyrgyzstan
0.7864
Even
0.7860
Yakut
0.7856
Hezhen
0.7851
Uyghur
0.7848
Mongola
0.7847
Ulchi
0.7847
Xibo
0.7840
Mixtec
0.7835
Daur
0.7831
Japanese
0.7829
Han
0.7829
Saami
0.7825
Korean
0.7825
Hazara
0.7821
Yi
0.7818
Burmese
0.7818
Finnish
0.7817
Mayan
0.7816
Russian
0.7814
She
0.7814
Mixe
0.7808
Norwegian
0.7801
Pima
0.7801
Kinh
0.7801
Estonian
0.7801
Icelandic
0.7800
Polish
0.7799
Kurds-IRAQ
0.7799
Piapoco
0.7798
Burusho
0.7794
English
0.7794
Hungarian
0.7793
Pathan
0.7793
Dai
0.7790
China_Lahu
0.7786
Bulgarian
0.7784
Adygei
0.7784
Czech
0.7784
Orcadian
0.7783
Tajik
0.7779
Chechen
0.7778
French
0.7776
Tuscan
0.7776
Ami.DG
0.7775
Russia_NorthOssetian
0.7775
Iranian-Fars
0.7775
Dusun
0.7774
Spanish
0.7773
Russia_Abkhasian
0.7772
Greek
0.7771
Lezgin
0.7770
Yadava
0.7770
Sindhi
0.7767
Basque
0.7767
Turkish
0.7766
Kapu
0.7765
Mala
0.7764
Karitiana
0.7763
Albanian.DG
0.7761
Punjabi
0.7761
Armenian
0.7759
Sardinian
0.7754
Georgian
0.7753
Surui
0.7753
Brahui
0.7747
Irula
0.7747
Kalash
0.7744
Balochi
0.7737
Jew_Iraqi
0.7736
Kusunda
0.7733
Makrani
0.7730
Druze
0.7717
BedouinB
0.7702
Jordanian
0.7691
Samaritan
0.7670
Saharawi
0.7634
Bougainville
0.7626
Mozabite
0.7623
Papuan
0.7568
Somali
0.7475
Masai
0.7401
Luo
0.7274
BantuKenya
0.7270
Luhya
0.7261
Mandenka
0.7256
Gambian
0.7254
Mende
0.7242
BantuHerero
0.7236
Esan
0.7231
BantuTswana
0.7217
Mbuti
0.7147
Ju_hoan_North
0.7105
Khomani_San
0.7095
</tbody>
This set for CHUKCHI is after removing common old alleles (ancestry). All alleles having a minor allele frequency > 30% have been removed. I like this better because it tends to better reflect more recent ancestry
<colgroup><col width="140"><col width="144"></colgroup><tbody>
430K SNPs - Max-Maf 0.3 - Chukchi
POPULATION
IBS
Eskimo_Sireniki.DG
0.8540
Eskimo_Naukan.DG
0.8537
Itelmen
0.8527
Even
0.8482
Hezhen
0.8479
Mansi
0.8477
Yakut
0.8474
Ulchi
0.8473
Daur
0.8466
Kyrgyz_Kyrgyzstan
0.8466
Mongola
0.8465
Mayan
0.8464
Pima
0.8462
Japanese
0.8461
Xibo
0.8460
Han
0.8460
Mixtec
0.8458
Mixe
0.8458
Korean
0.8455
Piapoco
0.8454
She
0.8448
Yi
0.8445
Karitiana
0.8441
Uyghur
0.8440
Saami
0.8439
Surui
0.8438
Kinh
0.8436
Burmese
0.8435
Hazara
0.8433
Dai
0.8428
Russian
0.8425
China_Lahu
0.8425
Kurds-IRAQ
0.8424
Finnish
0.8422
Ami.DG
0.8422
Dusun
0.8416
Estonian
0.8410
Polish
0.8408
Adygei
0.8405
Norwegian
0.8405
English
0.8404
Icelandic
0.8403
Hungarian
0.8400
Pathan
0.8399
Orcadian
0.8397
Burusho
0.8397
Tajik
0.8396
Chechen
0.8395
Czech
0.8394
Bulgarian
0.8393
Tuscan
0.8389
French
0.8388
Yadava
0.8388
Kusunda
0.8388
Russia_NorthOssetian
0.8387
Russia_Abkhasian
0.8387
Lezgin
0.8386
Iranian-Fars
0.8386
Spanish
0.8384
Basque
0.8383
Sindhi
0.8383
Greek
0.8383
Albanian.DG
0.8380
Mala
0.8380
Kalash
0.8378
Armenian
0.8377
Punjabi
0.8377
Kapu
0.8376
Sardinian
0.8373
Brahui
0.8370
Irula
0.8367
Georgian
0.8364
Balochi
0.8361
Jew_Iraqi
0.8354
Makrani
0.8353
Druze
0.8335
Samaritan
0.8321
BedouinB
0.8319
Jordanian
0.8317
Bougainville
0.8303
Papuan
0.8270
Saharawi
0.8235
Mozabite
0.8215
Somali
0.8065
Masai
0.7974
Luo
0.7836
BantuKenya
0.7834
Luhya
0.7825
Gambian
0.7817
Mandenka
0.7817
Mende
0.7801
BantuHerero
0.7795
Esan
0.7791
BantuTswana
0.7776
Mbuti
0.7729
Khomani_San
0.7690
Ju_hoan_North
0.7687
</tbody>
<style type="text/css">td {border: 1px solid #ccc;}br {mso-data-placement:same-cell;}</style>
This set for SAAMI is after removing common old alleles (ancestry). All alleles having a minor allele frequency > 30% have been removed. I like this better because it tends to better reflect more recent ancestry
<style type="text/css">td {border: 1px solid #ccc;}br {mso-data-placement:same-cell;}</style>
<colgroup><col width="134"><col width="188"></colgroup><tbody>
430K SNPs - Max-Maf 0.3 - Saami -Finland
POPULATION
IBS
Saami
0.8527
Finnish
0.8442
Chukchi
0.8439
Mansi
0.8436
Russian
0.8436
Estonian
0.8429
Norwegian
0.8421
Icelandic
0.8420
Czech
0.8419
Polish
0.8417
English
0.8417
Kurds - IRAQ
0.8417
Orcadian
0.8414
Hungarian
0.8409
Adygei
0.8405
Basque
0.8405
Kyrgyz_Kyrgyzstan
0.8405
Bulgarian
0.8401
Even
0.8400
Spanish
0.8398
French
0.8397
Lezgin
0.8396
Chechen
0.8392
Uyghur
0.8391
Hazara
0.8391
Russia_Abkhasian
0.8391
Russia_NorthOssetian
0.8390
Tuscan
0.8390
Albanian.DG
0.8390
Sardinian
0.8388
Eskimo_Sireniki.DG
0.8387
Yakut
0.8386
Greek
0.8386
Eskimo_Naukan.DG
0.8383
Hezhen
0.8381
Armenian
0.8381
Daur
0.8380
Tajik
0.8380
Burusho
0.8378
Georgian
0.8378
Itelmen
0.8377
Pathan
0.8375
Mongola
0.8373
Mixtec
0.8373
Ulchi
0.8372
Iranians - Fars
0.8372
Korean
0.8370
Kalash
0.8369
Sindhi
0.8367
Xibo
0.8367
Mayan
0.8366
Punjabi
0.8362
Pima
0.8361
Japanese
0.8359
Druze
0.8359
Mixe
0.8358
Han
0.8358
Jew_Iraqi
0.8358
Burmese
0.8354
She
0.8353
Yadava
0.8353
Brahui
0.8351
Piapoco
0.8350
Kapu
0.8349
Yi
0.8349
Balochi
0.8349
Karitiana
0.8348
Kinh
0.8346
Mala
0.8341
Makrani
0.8341
Dai
0.8341
Irula
0.8340
China_Lahu
0.8339
Ami.DG
0.8337
Surui
0.8337
BedouinB
0.8329
Dusun
0.8327
Samaritan
0.8324
Jordanian
0.8321
Kusunda
0.8317
Bougainville
0.8256
Saharawi
0.8226
Papuan
0.8222
Mozabite
0.8219
Somali
0.8049
Masai
0.7952
BantuKenya
0.7803
Luo
0.7799
Luhya
0.7793
Gambian
0.7786
Mandenka
0.7780
Mende
0.7769
Esan
0.7762
BantuTswana
0.7757
BantuHerero
0.7755
Mbuti
0.7702
Khomani_San
0.7661
Ju_hoan_North
0.7657
</tbody>
Zanzibar
02-24-2021, 11:47 PM
Nah, you've posted all the relevant calculators, maybe except for EUtest and Euro K15.
By the way, just recently I got a Russian kit, the girl looks far more ching-chong than the OP, even though she's like 5-6% Mongoloid only. I can only imagine what The Apricity would say about her... :rolleyes:
Interesting. Where in Russia is she from? Can you post a pic of her? Im curious. It shows genotype doesn't always equal phenotype.
Zanzibar
02-24-2021, 11:49 PM
Here's the IBS for Finland Saami and Chukchi
Plink calculates IBS as (IBS2 + 0.5*IBS1) / (IBS0 + IBS1 + IBS2) meaning the more positions where the target and the population compared match both alleles at a position (IBS2) the higher the IBS score. What this means is since you get 1 allele from each parent that if BOTH your dad's allele and mom's allele match Saami or Chukchi at every position you get a higher IBS score
The first set of results for CHUKCHI is without removing really ancient common alleles (very ancient ancestry) from the calculation
<style type="text/css">td {border: 1px solid #ccc;}br {mso-data-placement:same-cell;}</style>
<tbody>
615K SNPs - Max-Maf 0.5 - Chukchi
POPULATION
IBS
Eskimo_Sireniki.DG
0.7921
Eskimo_Naukan.DG
0.7914
Itelmen
0.7911
Mansi
0.7873
Kyrgyz_Kyrgyzstan
0.7864
Even
0.7860
Yakut
0.7856
Hezhen
0.7851
Uyghur
0.7848
Mongola
0.7847
Ulchi
0.7847
Xibo
0.7840
Mixtec
0.7835
Daur
0.7831
Japanese
0.7829
Han
0.7829
Saami
0.7825
Korean
0.7825
Hazara
0.7821
Yi
0.7818
Burmese
0.7818
Finnish
0.7817
Mayan
0.7816
Russian
0.7814
She
0.7814
Mixe
0.7808
Norwegian
0.7801
Pima
0.7801
Kinh
0.7801
Estonian
0.7801
Icelandic
0.7800
Polish
0.7799
Kurds-IRAQ
0.7799
Piapoco
0.7798
Burusho
0.7794
English
0.7794
Hungarian
0.7793
Pathan
0.7793
Dai
0.7790
China_Lahu
0.7786
Bulgarian
0.7784
Adygei
0.7784
Czech
0.7784
Orcadian
0.7783
Tajik
0.7779
Chechen
0.7778
French
0.7776
Tuscan
0.7776
Ami.DG
0.7775
Russia_NorthOssetian
0.7775
Iranian-Fars
0.7775
Dusun
0.7774
Spanish
0.7773
Russia_Abkhasian
0.7772
Greek
0.7771
Lezgin
0.7770
Yadava
0.7770
Sindhi
0.7767
Basque
0.7767
Turkish
0.7766
Kapu
0.7765
Mala
0.7764
Karitiana
0.7763
Albanian.DG
0.7761
Punjabi
0.7761
Armenian
0.7759
Sardinian
0.7754
Georgian
0.7753
Surui
0.7753
Brahui
0.7747
Irula
0.7747
Kalash
0.7744
Balochi
0.7737
Jew_Iraqi
0.7736
Kusunda
0.7733
Makrani
0.7730
Druze
0.7717
BedouinB
0.7702
Jordanian
0.7691
Samaritan
0.7670
Saharawi
0.7634
Bougainville
0.7626
Mozabite
0.7623
Papuan
0.7568
Somali
0.7475
Masai
0.7401
Luo
0.7274
BantuKenya
0.7270
Luhya
0.7261
Mandenka
0.7256
Gambian
0.7254
Mende
0.7242
BantuHerero
0.7236
Esan
0.7231
BantuTswana
0.7217
Mbuti
0.7147
Ju_hoan_North
0.7105
Khomani_San
0.7095
</tbody>
This set for CHUKCHI is after removing common old alleles (ancestry). All alleles having a minor allele frequency > 30% have been removed. I like this better because it tends to better reflect more recent ancestry
<colgroup><col width="140"><col width="144"></colgroup><tbody>
430K SNPs - Max-Maf 0.3 - Chukchi
POPULATION
IBS
Eskimo_Sireniki.DG
0.8540
Eskimo_Naukan.DG
0.8537
Itelmen
0.8527
Even
0.8482
Hezhen
0.8479
Mansi
0.8477
Yakut
0.8474
Ulchi
0.8473
Daur
0.8466
Kyrgyz_Kyrgyzstan
0.8466
Mongola
0.8465
Mayan
0.8464
Pima
0.8462
Japanese
0.8461
Xibo
0.8460
Han
0.8460
Mixtec
0.8458
Mixe
0.8458
Korean
0.8455
Piapoco
0.8454
She
0.8448
Yi
0.8445
Karitiana
0.8441
Uyghur
0.8440
Saami
0.8439
Surui
0.8438
Kinh
0.8436
Burmese
0.8435
Hazara
0.8433
Dai
0.8428
Russian
0.8425
China_Lahu
0.8425
Kurds-IRAQ
0.8424
Finnish
0.8422
Ami.DG
0.8422
Dusun
0.8416
Estonian
0.8410
Polish
0.8408
Adygei
0.8405
Norwegian
0.8405
English
0.8404
Icelandic
0.8403
Hungarian
0.8400
Pathan
0.8399
Orcadian
0.8397
Burusho
0.8397
Tajik
0.8396
Chechen
0.8395
Czech
0.8394
Bulgarian
0.8393
Tuscan
0.8389
French
0.8388
Yadava
0.8388
Kusunda
0.8388
Russia_NorthOssetian
0.8387
Russia_Abkhasian
0.8387
Lezgin
0.8386
Iranian-Fars
0.8386
Spanish
0.8384
Basque
0.8383
Sindhi
0.8383
Greek
0.8383
Albanian.DG
0.8380
Mala
0.8380
Kalash
0.8378
Armenian
0.8377
Punjabi
0.8377
Kapu
0.8376
Sardinian
0.8373
Brahui
0.8370
Irula
0.8367
Georgian
0.8364
Balochi
0.8361
Jew_Iraqi
0.8354
Makrani
0.8353
Druze
0.8335
Samaritan
0.8321
BedouinB
0.8319
Jordanian
0.8317
Bougainville
0.8303
Papuan
0.8270
Saharawi
0.8235
Mozabite
0.8215
Somali
0.8065
Masai
0.7974
Luo
0.7836
BantuKenya
0.7834
Luhya
0.7825
Gambian
0.7817
Mandenka
0.7817
Mende
0.7801
BantuHerero
0.7795
Esan
0.7791
BantuTswana
0.7776
Mbuti
0.7729
Khomani_San
0.7690
Ju_hoan_North
0.7687
</tbody>
<style type="text/css">td {border: 1px solid #ccc;}br {mso-data-placement:same-cell;}</style>
What are these datas showing? What populations share the closest alleles with the Chukchi?
What are these datas showing? What populations share the closest alleles with the Chukchi?
They’re sorted from closest (top) to furthest (bottom). The one which says 430k SNPs is more informative because the common very ancient alleles have been removed
Zanzibar
02-24-2021, 11:56 PM
This set for SAAMI is after removing common old alleles (ancestry). All alleles having a minor allele frequency > 30% have been removed. I like this better because it tends to better reflect more recent ancestry
<style type="text/css">td {border: 1px solid #ccc;}br {mso-data-placement:same-cell;}</style>
<colgroup><col width="134"><col width="188"></colgroup><tbody>
430K SNPs - Max-Maf 0.3 - Saami -Finland
POPULATION
IBS
Saami
0.8527
Finnish
0.8442
Chukchi
0.8439
Mansi
0.8436
Russian
0.8436
Estonian
0.8429
Norwegian
0.8421
Icelandic
0.8420
Czech
0.8419
Polish
0.8417
English
0.8417
Kurds - IRAQ
0.8417
Orcadian
0.8414
Hungarian
0.8409
Adygei
0.8405
Basque
0.8405
Kyrgyz_Kyrgyzstan
0.8405
Bulgarian
0.8401
Even
0.8400
Spanish
0.8398
French
0.8397
Lezgin
0.8396
Chechen
0.8392
Uyghur
0.8391
Hazara
0.8391
Russia_Abkhasian
0.8391
Russia_NorthOssetian
0.8390
Tuscan
0.8390
Albanian.DG
0.8390
Sardinian
0.8388
Eskimo_Sireniki.DG
0.8387
Yakut
0.8386
Greek
0.8386
Eskimo_Naukan.DG
0.8383
Hezhen
0.8381
Armenian
0.8381
Daur
0.8380
Tajik
0.8380
Burusho
0.8378
Georgian
0.8378
Itelmen
0.8377
Pathan
0.8375
Mongola
0.8373
Mixtec
0.8373
Ulchi
0.8372
Iranians - Fars
0.8372
Korean
0.8370
Kalash
0.8369
Sindhi
0.8367
Xibo
0.8367
Mayan
0.8366
Punjabi
0.8362
Pima
0.8361
Japanese
0.8359
Druze
0.8359
Mixe
0.8358
Han
0.8358
Jew_Iraqi
0.8358
Burmese
0.8354
She
0.8353
Yadava
0.8353
Brahui
0.8351
Piapoco
0.8350
Kapu
0.8349
Yi
0.8349
Balochi
0.8349
Karitiana
0.8348
Kinh
0.8346
Mala
0.8341
Makrani
0.8341
Dai
0.8341
Irula
0.8340
China_Lahu
0.8339
Ami.DG
0.8337
Surui
0.8337
BedouinB
0.8329
Dusun
0.8327
Samaritan
0.8324
Jordanian
0.8321
Kusunda
0.8317
Bougainville
0.8256
Saharawi
0.8226
Papuan
0.8222
Mozabite
0.8219
Somali
0.8049
Masai
0.7952
BantuKenya
0.7803
Luo
0.7799
Luhya
0.7793
Gambian
0.7786
Mandenka
0.7780
Mende
0.7769
Esan
0.7762
BantuTswana
0.7757
BantuHerero
0.7755
Mbuti
0.7702
Khomani_San
0.7661
Ju_hoan_North
0.7657
</tbody>
Does it mean that more allele the Saami is sharing with other pops, the more the latter genetically closer to the Saami?
Interesting. Where in Russia is she from? Can you post a pic of her? Im curious. It shows genotype doesn't always equal phenotype.
That’s not true otherwise chinese would look African or European . Everything in your body is dictated by genes. They shape your eyes, nose etc.
Now what you maybe referring to is that if you have 2 brothers with 10% E. Asian. It’s possible one brother’s 10% would include genes that affect facial features whereas the other brothers 10% E Asian doesn’t include genes affecting facial features and would thus look more European than his Asian looking brother
Does it mean that more allele the Saami is sharing with other pops, the more the latter genetically closer to the Saami?
Yes. Also just because Chukchi is 3rd on Saami list doesn’t necessarily mean they are very close to each other because if you look at the Chukchi 430k SNP list Saami is like 26th on the list
Zanzibar
02-25-2021, 12:03 AM
Yes
Interesting how the Saami are genetically closer to the Chukchi than the Mansi, who are their Uralic relatives according to the run.
Ajeje Brazorf
02-25-2021, 12:08 AM
This is how they score on scaled Global25
Chukchi:
Distance to: Chukchi
0.05144905 Eskimo_Sireniki
0.05246831 Itelmen
0.05393111 Eskimo_Chaplin
0.05584933 Koryak
0.06919831 Eskimo
0.07634917 Eskimo_Naukan
0.12454608 Yukagir_Tundra
0.16683660 Greenlander_East
0.17236774 Todzin
0.17313255 Even
0.17792759 Negidal
0.18305369 Tuvinian
0.18328869 Ulchi
0.18351484 Khamnegan
0.18364967 Mogush
0.18784084 Nganassan
0.18822965 Nivkh
0.18838499 Evenk
0.19473998 Nanai
0.19887397 Dolgan
0.20198147 Buryat
0.20492081 Nenets
0.20545313 Oroqen
0.20594544 Khakass_Kachins
0.20867591 Kalmyk
0.21082288 Altaian
0.21173955 Mongolian
0.21452292 Selkup
0.22500173 Greenlander_West
0.22518165 Khakass
0.22520998 Chipewyan
0.22715263 Hezhen
0.22928000 Kazakh_China
0.23314800 Daur
0.23613302 Kirghiz
0.23973206 Kirghiz_China
0.24047722 Shor_Khakassia
0.24234787 Shor
0.24402121 Yakut
0.24462334 Shor_Mountain
0.24545292 Amerindian_North
0.24830167 Sakha
0.25451722 Tubalar
0.25542039 Xibo
0.25971278 Mongola
0.25976259 Kazakh
0.26641301 Tibetan_Gangcha
0.27098751 Dongxiang
0.27101527 Cree
0.27261786 Khanty
0.27379685 Salar
0.27649099 Tu
0.27737859 Tibetan_Shigatse
0.27739983 Tibetan_Xunhua
0.27753652 Tibetan_Shannan
0.27758677 Ket
0.27906903 Dungan
0.27929956 Tibetan_Lhasa
0.27984307 Bonan
0.28032684 Tibetan_Nagqu
0.28211199 Sherpa
0.28212704 Gurung
0.28239830 Tibetan_Gannan
0.28255251 Magar
0.28269242 Tamang
0.28302240 Tibetan_Chamdo
0.28400469 Mansi
0.28490101 Tatar_Siberian_Zabolotniye
0.28493551 Yugur
0.28536379 Karakalpak
0.28575438 Qiang_Daofu
0.28698272 Rai
0.28730854 Tlingit
0.28866709 Tibetan_Yajiang
0.29049333 Tibetan_Yunnan
0.29255957 Japanese
0.29321849 Yukagir_Forest
0.29549905 Korean
0.30024019 Tibetan_Xinlong
0.30026806 Han_Shanxi
0.30068444 Tripuri
0.30141388 Qiang_Danba
0.30228373 Kusunda
0.30255377 Jamatia
0.30318210 Burmese
0.30516481 Yi
0.30536644 Naxi
0.30551417 Tatar_Siberian
0.30584919 Han_Shandong
0.30660090 Han_Henan
0.30826185 Nogai
0.31186238 Tharu
0.31302029 Hazara
0.31805102 Uygur
0.31958523 Han_Jiangsu
0.32039522 Brahmin_Manipuri
0.32062975 Han_Shanghai
0.32158881 Han_Hubei
0.32170661 Newar
0.32219332 Hazara_Afghanistan
0.32246574 Han_Sichuan
0.32452683 Han_Zhejiang
0.32733758 Tujia
0.33063506 Han_Chongqing
0.33266152 Miao
0.33461253 Han_Fujian
0.33705073 Thai
0.33896337 Bashkir
0.34058772 Lahu
0.34162094 She
0.34456817 Han_Guangdong
0.34999189 Dong_Guizhou
0.35001392 Dong_Hunan
0.35075040 Kinh_Vietnam
0.35358016 Uzbek
0.35569198 Cambodian
0.35688177 Aeta
0.35703315 Mulam
0.35772364 Gelao
0.35838305 Zhuang
0.36016272 Agta
0.36093267 Vizayan
0.36278467 Malay
0.36291987 Dai
0.36443657 Batak
0.36537995 Jehai
0.36556764 Mixtec
0.36566569 Maonan
0.36599952 Huichol
0.36622119 Zapotec
0.36647137 Pima
0.36674400 Nahua
0.37022340 Li
0.37400671 Hawaiian
0.37453277 Onge
0.37482517 Bolivian_Pando
0.37526052 Mayan
0.37612652 Bajo
0.37621421 Jarawa
0.37644154 Mixe
0.37845569 Bolivian_Cochabamba
0.37875812 Atayal
0.37907095 Htin_Mal
0.37983117 Luzon
0.38077128 Quechua
0.38391638 Mlabri
0.38446504 Indonesian_Bali
0.38547604 Ami
0.38710811 Indonesian_Java
0.39043291 Cachi
0.39102348 Lebbo
0.39166985 Igorot
0.39324904 Maori
0.39345667 Dusun
0.39634050 Turkmen_Uzbekistan
0.39729022 Mari
0.39746078 Murut
0.39821775 Tatar_Crimean_steppe
0.39868560 Bolivian_LaPaz
0.39933712 Bonda
0.39939769 Juang
0.39995957 Colla
0.40191571 Bahun
0.40396012 Gadaba
0.40450450 Turkmen
0.40837100 Aymara
0.40838807 Saami
0.41030231 Khonda_Dora
0.41315032 Udmurt
0.41538226 Yukpa
0.41681040 Korwa
0.41774057 Piapoco
0.41825935 Birhor
0.41871441 Tatar_Lipka
0.41918012 Ho
0.42077442 Wichi
0.42449173 Santhal
0.42528632 Besermyan
0.42695543 Bhumij
0.42785822 Chuvash
0.42867269 Asur
0.43282810 Gond
0.43744510 Bengali_Bangladesh
0.44220874 Karitiana
0.44233071 Burusho
0.44710488 Tatar_Kazan
0.44759832 Chenchu
0.45016139 Paniya
0.45085508 Kadar
0.45144851 Surui
0.45175307 Irula
0.45270378 Relli
0.45304988 Saami_Kola
0.45392181 Malayan
0.45614557 Pulliyar
0.45784309 Brahmin_West_Bengal
0.45925790 North_Kannadi
0.46136008 Hakkipikki
0.46185792 Tajik
0.46205070 Uttar_Pradesh
0.46301080 Kamboj_o
0.46357747 Madiga
0.46387902 Pallan
0.46426374 Dusadh
0.46438603 Yadava
0.46511129 Kol
0.46516388 Maratha
0.46552623 Dharkar
0.46567247 Chamar
0.46575555 Komi
0.46615737 Kanjar
0.46748473 Punjabi_Lahore
0.46827679 Kshatriya
0.46829298 Mala
0.46894269 Kurumba
0.46953775 Brahmin_Tamil_Nadu
0.46970219 Kho_Singanali
0.47057448 Sakilli
0.47066661 Kashmiri_Pandit
0.47102981 Piramalai
0.47207599 Velamas
0.47260738 Iyer
0.47409872 Gujarati
0.47445850 Kohistani
0.47649400 Tatar_Mishar
0.47668425 Brahmin_Gujarat
0.47967617 Brahmin_Uttar_Pradesh
0.48048834 Tajik_Ishkashim
0.48209592 Gupta
0.48249075 Punjabi_Sikh_India
0.48303491 Pashtun
0.48305653 Gujar_India
0.48329926 Jatt_Pathak
0.48348705 Tajik_Shugnan
0.48440404 Khatri
0.48601458 Ror
0.48701751 Punjabi_Jatt
0.48763482 Gujar_Pakistan
0.48813836 Kamboj
0.48841073 Yusufzai
0.48871651 Uthmankhel
0.48889579 Sindhi
0.49093281 Tarkalani
0.49180271 Tajik_Rushan
0.49351515 Kalash
0.49668033 Turkish_South
0.49711573 Turkish_Northwest
0.49936588 Turkish_Southwest
0.49972452 Turkish_Balikesir
0.50039999 Turkish_Aydin
0.50588061 Russian_Pinega
0.50847591 Turkish_North
0.51105919 Tajik_Yagnobi
0.51421268 Vepsian
0.51530653 Roma_Balkans
0.51733443 Brahui
0.51783351 Finnish_East
0.51840199 Abazin
0.51902955 Karelian
0.51935316 Balochi
0.52199604 Roma_Granada
0.52235551 Mordovian
0.52281681 Roma_Bilbao
0.52407091 Kabardin
0.52430099 Parsi_India
0.52442995 Parsi_Pakistan
0.52524100 Cherkes
0.52541988 Karachay
0.52561052 Roma_Porto
0.52578893 Turkish_Central
0.52665071 Turkish_Rumeli
0.52669676 Balkar
0.52690097 Circassian
0.52705563 Makrani
0.52847027 Russian_Kostroma
0.52923609 Kumyk
0.53045195 Iranian_Bandari
0.53257306 Ingrian
0.53299754 Finnish
0.53347443 Turkish_Adana
0.53428738 Roma_Madrid
0.53443660 Azeri
0.53506996 North_Ossetian
0.53759528 Nasoi
0.53846194 Turkish_Deliorman
0.53905948 Iranian_Seyyed
0.53906209 Azeri_Dagestan
0.53986763 Azeri_Turkey
0.54006354 Turkish_Kayseri
0.54016544 Roma_Barcelona
0.54090207 Cossack_Kuban
0.54189871 Iranian_Fars
0.54192317 Ingushian
0.54300809 Lak
0.54344199 Darginian
0.54475384 Tabasaran
0.54503324 Avar
0.54560065 Ossetian
0.54572949 Chechen
0.54608083 Adygei
0.54637451 Kaitag
0.54829815 Kubachinian
0.54991104 Russian_Tver
0.55119419 Talysh_Azerbaijan
0.55282300 Iranian_Lor
0.55287638 Iranian_Zoroastrian
0.55309289 Turkish_East
0.55317881 Iranian_Mazandarani
0.55611772 Ezid
0.55629483 Russian_Kursk
0.55696083 Moldovan_o
0.55836110 Cossack_Ukrainian
0.55884792 Russian_Orel
0.55999437 Estonian
0.56059004 Kurdish
0.56189190 Russian_Voronez
0.56294310 Abkhasian
0.56332827 Moldovan
0.56445084 Ukrainian
0.56459767 Iraqi
0.56565761 Afrikaner
0.56638536 Hungarian
0.56661643 Russian_Smolensk
0.56702991 Belarusian
0.56754833 Syrian
0.56777164 Norwegian
0.56781459 Ashkenazi_Russia
0.56831219 Swedish
0.56831604 Slovakian
0.56899312 Lithuanian_PA
0.56941906 Ashkenazi_Lithuania
0.56947180 Romanian
0.56980371 Udi
0.56986254 Polish
0.57008371 Gagauz
0.57010855 Bosnian
0.57011136 Dutch
0.57015265 Bulgarian
0.57025220 Czech
0.57041342 Croatian
0.57053232 Ashkenazi_Belarussia
0.57072601 Lithuanian_RA
0.57088168 Slovenian
0.57092123 Austrian
0.57101468 Lithuanian_VA
0.57103400 Latvian
0.57126057 Ashkenazi_Ukraine
0.57221228 Montenegrin
0.57245261 Orcadian
0.57284130 Shetlandic
0.57291654 Ashkenazi_Poland
0.57299349 Serbian
0.57299622 Scottish
0.57330901 Icelandic
0.57342875 Irish
0.57378332 Lithuanian_VZ
0.57429445 Lithuanian_SZ
0.57431486 Lithuanian_PZ
0.57444085 Danish
0.57462078 German
0.57465311 Mountain_Jew
0.57469981 Jordanian
0.57485898 Belgian
0.57532879 English
0.57550648 German_East
0.57562594 Lebanese_Muslim
0.57609076 Rumelia_East
0.57625088 Georgian_Jew
0.57632167 French_Brittany
0.57639781 French_Nord
0.57644386 French_Alsace
0.57670095 Swiss_Italian
0.57686023 Welsh
0.57709995 Macedonian
0.57735016 Albanian
0.57742296 Greek_Central_Macedonia
0.57758211 French_Seine-Maritime
0.57792565 Palestinian
0.57796601 Greek_Macedonia
0.57801453 BedouinA
0.57804005 Swiss_German
0.57818402 French_Pas-de-Calais
0.57828741 English_Cornwall
0.57871136 Iranian_Jew
0.57878882 Spanish_Murcia
0.57909693 Assyrian
0.57927794 Spanish_Canarias
0.57949527 Italian_Northeast
0.57949683 French_Paris
0.57961652 Sorb_Niederlausitz
0.58000210 Ashkenazi_Germany
0.58014038 French_Provence
0.58019098 Greek_Thessaly
0.58043836 Greek_Peloponnese
0.58045338 Maltese
0.58093590 Portuguese
0.58107460 Italian_Liguria
0.58121445 Sephardic_Jew
0.58133429 Greek_Izmir
0.58155641 Spanish_Castilla_Y_Leon
0.58156060 Spanish_Camp_de_Tarragona
0.58167553 French_Auvergne
0.58174840 Spanish_Asturias
0.58176896 Moroccan_Jew
0.58195232 Spanish_Galicia
0.58218798 French_Occitanie
0.58225478 Sicilian_West
0.58229444 Swiss_French
0.58231617 Italian_Aosta_Valley
0.58240252 Spanish_Soria
0.58261008 Italian_Molise
0.58265598 Spanish_Penedes
0.58273767 Spanish_Valencia
0.58281599 Spanish_Cataluna
0.58283570 Spanish_Girona
0.58286242 Libyan
0.58299770 Syrian_Jew
0.58304372 Egyptian
0.58311173 Italian_Trentino-Alto-Adige
0.58317606 Spanish_Alacant
0.58318324 Lebanese_Druze
0.58320772 Greek_Crete
0.58321756 Italian_Basilicata
0.58322173 Spanish_Baleares
0.58330811 Italian_Calabria
0.58342361 Italian_Umbria
0.58343300 Spanish_Andalucia
0.58355504 Romaniote_Jew
0.58355798 Italian_Piedmont
0.58369930 Spanish_Eivissa
0.58376074 Sicilian_East
0.58393624 Armenian
0.58394559 Italian_Jew
0.58394990 Spanish_Lleida
0.58401057 Italian_Marche
0.58402645 Italian_Lombardy
0.58408834 Spanish_Mallorca
0.58408964 Druze
0.58411031 Georgian_Imer
0.58421551 Armenian_Hemsheni
0.58422246 Spanish_Castello
0.58430426 Greek_Cappadocia
0.58448456 Italian_Tuscany
0.58450234 Turkish_Trabzon
0.58459290 Spanish_Castilla_La_Mancha
0.58464491 Georgian_Laz
0.58483093 Spanish_Extremadura
0.58483424 Italian_Abruzzo
0.58485439 Spanish_Terres_de_l'Ebre
0.58488833 Libyan_Jew
0.58499767 Italian_Veneto
0.58512696 Spanish_Pirineu
0.58523785 Italian_Apulia
0.58525159 Spanish_Menorca
0.58527800 Tunisian
0.58557448 Italian_Campania
0.58565504 Spanish_Navarra
0.58580688 Greek_Dodecanese
0.58581414 Spanish_Aragon
0.58585241 Greek_Central_Anatolia
0.58585545 French_South
0.58594802 Spanish_Cantabria
0.58618034 Greek_Trabzon
0.58625979 Greek_Laconia
0.58630299 Greek_Kos
0.58655188 Tunisian_Jew
0.58683481 Karaite_Egypt
0.58693842 Italian_Bergamo
0.58696518 Spanish_Barcelones
0.58699190 Spanish_Peri-Barcelona
0.58699783 Tunisian_Berber_Matmata
0.58743676 Algerian
0.58770851 Spanish_Catalunya_Central
0.58786753 Moroccan_North
0.58794656 Berber_Tunisia_Sen
0.58876566 Tunisian_Berber_Tamezret
0.58892653 Iraqi_Jew
0.58895840 Cypriot
0.58934987 French_Corsica
0.58937704 Italian_Lazio
0.58953621 Lebanese_Christian
0.59003513 Yemenite_Amran
0.59004758 Tunisian_Berber_Zraoua
0.59053242 Tunisian_Douz
0.59151170 Moroccan
0.59225548 Spanish_Pais_Vasco
0.59275465 Spanish_La_Rioja
0.59304621 Berber_Tunisia_Chen
0.59318449 Palestinian_Beit_Sahour
0.59340049 Basque_Spanish
0.59346331 Mozabite
0.59455721 Basque_French
0.59508987 Tunisian_Rbaya
0.59521266 Australian
0.59566382 Berber_MAR_ERR
0.59720053 Yemenite_Dhamar
0.59728807 Yemenite_Al_Bayda
0.59799399 Samaritan
0.60103621 Saharawi
0.60269101 Yemenite_Al_Jawf
0.60312132 Yemenite_Jew
0.60318306 Saudi
0.60325129 Yemenite_Ma'rib
0.60390806 Berber_MAR_TIZ
0.60410727 Yemenite_Mahra
0.60475044 BedouinB
0.61009049 Moroccan_South
0.61880844 Sardinian
0.62046501 Eritrean
0.62123483 Ethiopian_Afar
0.62320114 Ethiopian_Tigray
0.62698292 Ethiopian_Agaw
0.62762304 Ethiopian_Amhara
0.63059454 Ethiopian_Jew
0.64118882 Berber_Algeria
0.64137285 Ethiopian_Oromo
0.65264939 Ethiopian_Wolayta
0.65269011 Somali
0.66163471 Somali_Kenya
0.66910794 Rendille
0.67457316 Iraqw
0.68987883 Fulani
0.69286872 Datog
0.69956792 Ethiopian_Ari_cultivator
0.70227648 Ethiopian_Ari
0.70285620 Elmolo
0.70436285 Ethiopian_Ari_blacksmith
0.71379959 Ogiek
0.71966052 Masai
0.72755092 Sandawe
0.74235614 Sengwer
0.74640893 Hadza
0.74865314 Kikuyu
0.75138257 Kosipe
0.76606845 Bulala
0.76692339 Ethiopian_Gumuz
0.77126182 Ethiopian_Mursi
0.77152610 Koinanbe
0.77181447 Papuan
0.80192222 Ethiopian_Anuak
0.80367281 Dinka
0.80457044 Sudanese
0.81167587 Mada
0.81581998 Luhya_Kenya
0.81770141 Luo
0.81909075 Bantu_Kenya
0.82455947 Mandenka
0.82532587 Gambian
0.82886774 Mwani
0.82986637 Laka
0.83240404 Kaba
0.83359411 Makhuwa
0.83517370 Cameroon_Bakoko
0.83519458 Sena
0.83550040 Bantu_S.W.
0.83575378 Ndau
0.83614200 Mende_Sierra_Leone
0.83643236 Nyanja
0.83701989 Nyaneka
0.83736661 Yao
0.83766266 Umbundu
0.83777742 Cameroon_Bangwa
0.83813526 Lemande
0.83936511 Cameroon_Bafut
0.83941443 Ngumba
0.83947176 Ganguela
0.83956136 Changana
0.83960049 Cameroon_Aghem
0.84010982 Kongo
0.84014441 Ronga
0.84049661 Tikar_South
0.84051354 Chopi
0.84119888 Tswa
0.84145339 Manyika
0.84162023 Cameroon_Mbo
0.84224448 Bantu_S.E.
0.84293414 Bitonga
0.84409525 Yoruba
0.84415993 Igbo
0.84637199 Esan_Nigeria
0.87100643 Bedzan
0.87521630 Bakola
0.87945893 Baka
0.89117327 Biaka
0.92970851 Khomani_San
0.99457570 Ju_hoan_North
1.00762217 Mbuti
Saami:
Distance to: Saami
0.05165166 Saami_Kola
0.05229796 Udmurt
0.06021780 Besermyan
0.07106311 Chuvash
0.07375363 Komi
0.08198600 Tatar_Kazan
0.09534176 Mari
0.10053647 Tatar_Mishar
0.10443703 Tatar_Lipka
0.10963287 Russian_Pinega
0.11182593 Bashkir
0.11883667 Vepsian
0.12036459 Finnish_East
0.12213113 Karelian
0.12774128 Tatar_Crimean_steppe
0.13412494 Mordovian
0.13609329 Russian_Kostroma
0.13690079 Ingrian
0.13826217 Finnish
0.14160670 Yukagir_Forest
0.14216068 Tatar_Siberian
0.15078272 Cossack_Kuban
0.15607780 Tatar_Siberian_Zabolotniye
0.15796967 Tlingit
0.16075159 Russian_Tver
0.16336793 Turkmen
0.16459138 Turkmen_Uzbekistan
0.16632238 Estonian
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
0.17686750 Moldovan_o
0.17822236 Tajik_Rushan
0.17827602 Tajik_Shugnan
0.17926072 Belarusian
0.17927329 Ukrainian
0.17931411 Latvian
0.17952044 Russian_Smolensk
0.17971434 Lithuanian_PA
0.18073708 Lithuanian_VA
0.18076503 Lithuanian_RA
0.18157993 Nogai
0.18221751 Lithuanian_SZ
0.18279075 Swedish
0.18283221 Lithuanian_VZ
0.18283997 Lithuanian_PZ
0.18381285 Polish
0.18547941 Slovakian
0.18560255 Norwegian
0.18837516 Tajik_Ishkashim
0.18848438 Khanty
0.18862550 Czech
0.18949914 Hungarian
0.19039592 Icelandic
0.19087737 Dutch
0.19112002 Turkish_Deliorman
0.19124715 Turkish_Rumeli
0.19176339 Afrikaner
0.19226524 Danish
0.19384756 Shetlandic
0.19394972 Orcadian
0.19445420 Sorb_Niederlausitz
0.19452394 Scottish
0.19459547 German_East
0.19534091 Irish
0.19587038 Croatian
0.19604462 Austrian
0.19634888 Turkish_Northwest
0.19636953 Slovenian
0.19658845 Tajik_Yagnobi
0.19673689 Moldovan
0.19719818 German
0.19724073 Turkish_Balikesir
0.19782542 English
0.19927325 Welsh
0.20060210 Ket
0.20117721 Bosnian
0.20118615 French_Brittany
0.20157132 English_Cornwall
0.20194140 Hazara_Afghanistan
0.20361165 Turkish_Southwest
0.20432707 Uygur
0.20439751 Belgian
0.20445223 Roma_Barcelona
0.20462215 Turkish_Aydin
0.20562802 French_Seine-Maritime
0.20633981 Maori
0.20636918 Karakalpak
0.20650501 French_Pas-de-Calais
0.20682974 French_Nord
0.20693335 Turkish_South
0.20699293 Kho_Singanali
0.20726226 French_Alsace
0.20795723 Montenegrin
0.20798674 Serbian
0.20854188 Jatt_Pathak
0.20953171 Romanian
0.21012969 Roma_Bilbao
0.21019578 Swiss_German
0.21102027 Hazara
0.21116312 Roma_Madrid
0.21116963 Ror
0.21145083 French_Paris
0.21361686 Turkish_North
0.21417279 Abazin
0.21418889 Bulgarian
0.21429159 Roma_Granada
0.21462089 Roma_Porto
0.21499635 Kabardin
0.21507515 Cherkes
0.21511053 Roma_Balkans
0.21634777 Kumyk
0.21653079 Tubalar
0.21776706 French_Occitanie
0.21786404 Gagauz
0.21818609 Darginian
0.21819196 Balkar
0.21824446 Macedonian
0.21838606 Greenlander_West
0.21869659 Circassian
0.21889639 French_Auvergne
0.21933852 Karachay
0.21995853 Avar
0.21998347 Kaitag
0.22026626 Swiss_French
0.22034786 Burusho
0.22059482 Lak
0.22134912 French_Provence
0.22167998 Tabasaran
0.22180535 Italian_Northeast
0.22249621 Uthmankhel
0.22359130 Pashtun
0.22384145 Italian_Aosta_Valley
0.22472817 Kubachinian
0.22491409 Tarkalani
0.22499092 Spanish_Camp_de_Tarragona
0.22592539 Spanish_Penedes
0.22631736 Spanish_Girona
0.22637707 Spanish_Soria
0.22686358 Yusufzai
0.22694372 Kalash
0.22746928 Spanish_Cataluna
0.22796941 Spanish_Lleida
0.22832028 Spanish_Castilla_Y_Leon
0.22836868 Spanish_Barcelones
0.22852135 Spanish_Mallorca
0.22875742 Turkish_Central
0.22881186 Italian_Trentino-Alto-Adige
0.22888814 Shor_Mountain
0.22894406 French_South
0.22905624 Spanish_Galicia
0.22938034 Swiss_Italian
0.22944763 Spanish_Valencia
0.22947054 Spanish_Pirineu
0.22957599 Spanish_Baleares
0.22981432 Spanish_Castello
0.22988411 Spanish_Catalunya_Central
0.23026006 Spanish_Cantabria
0.23030883 Spanish_Eivissa
0.23038721 Spanish_Murcia
0.23056844 Portuguese
0.23057927 Spanish_Peri-Barcelona
0.23064760 Chechen
0.23082048 Spanish_Alacant
0.23087119 Spanish_Terres_de_l'Ebre
0.23096605 Spanish_Asturias
0.23103212 Ingushian
0.23134900 Shor_Khakassia
0.23139644 Rumelia_East
0.23160167 Italian_Veneto
0.23233423 North_Ossetian
0.23259576 Spanish_Aragon
0.23260692 Spanish_Andalucia
0.23274092 Spanish_Castilla_La_Mancha
0.23286304 Shor
0.23304636 Greek_Central_Macedonia
0.23311248 Spanish_Menorca
0.23346567 Spanish_Navarra
0.23399951 Spanish_Extremadura
0.23429169 Turkish_Adana
0.23429490 Greek_Macedonia
0.23442998 Albanian
0.23465355 Punjabi_Jatt
0.23472822 Italian_Liguria
0.23477325 Kamboj
0.23479057 Azeri_Dagestan
0.23482051 Spanish_Pais_Vasco
0.23533737 Adygei
0.23572340 Basque_French
0.23581486 Kazakh
0.23687648 Italian_Piedmont
0.23699127 Basque_Spanish
0.23733768 Italian_Bergamo
0.23760903 Spanish_Canarias
0.23791360 Kohistani
0.23812838 Italian_Lombardy
0.23818118 Kashmiri_Pandit
0.23847295 Greek_Thessaly
0.23931373 Punjabi_Sikh_India
0.24101451 Turkish_Kayseri
0.24157317 Spanish_La_Rioja
0.24183627 Khatri
0.24292289 Greek_Peloponnese
0.24300897 Italian_Tuscany
0.24324375 Ashkenazi_Russia
0.24396832 Azeri
0.24413804 Ossetian
0.24446487 Bahun
0.24581833 Ashkenazi_Belarussia
0.24624821 Ashkenazi_Ukraine
0.24629777 Ashkenazi_Lithuania
0.24675200 Azeri_Turkey
0.24702133 Italian_Marche
0.24721748 Italian_Umbria
0.24806275 Parsi_Pakistan
0.24844101 French_Corsica
0.24966152 Ashkenazi_Poland
0.24980008 Italian_Molise
0.24988853 Greek_Izmir
0.24997522 Parsi_India
0.25070430 Iranian_Fars
0.25112561 Khakass
0.25131387 Sicilian_West
0.25141987 Iranian_Seyyed
0.25209750 Greek_Laconia
0.25223944 Gujar_Pakistan
0.25296651 Italian_Abruzzo
0.25312698 Sindhi
0.25335245 Italian_Lazio
0.25421206 Turkish_East
0.25572831 Iranian_Zoroastrian
0.25607982 Italian_Basilicata
0.25662969 Iranian_Bandari
0.25687057 Maltese
0.25711336 Balochi
0.25726530 Italian_Apulia
0.25744236 Brahui
0.25801235 Sicilian_East
0.25824113 Brahmin_Gujarat
0.25839003 Ezid
0.25908810 Talysh_Azerbaijan
0.26030544 Greek_Crete
0.26070124 Gujar_India
0.26071234 Italian_Campania
0.26118616 Ashkenazi_Germany
0.26229518 Italian_Calabria
0.26423832 Iranian_Lor
0.26444679 Makrani
0.26454310 Kurdish
0.26523514 Brahmin_West_Bengal
0.26614517 Udi
0.26631614 Abkhasian
0.26807413 Iranian_Mazandarani
0.26984022 Greek_Kos
0.26991056 Italian_Jew
0.27029943 Selkup
0.27052103 Sephardic_Jew
0.27196410 Kshatriya
0.27200529 Greek_Dodecanese
0.27235421 Moroccan_Jew
0.27295840 Brahmin_Uttar_Pradesh
0.27322436 Kirghiz
0.27485559 Syrian
0.27491232 Kirghiz_China
0.27599089 Romaniote_Jew
0.27866649 Greek_Central_Anatolia
0.27917442 Syrian_Jew
0.27962127 Iraqi
0.27967688 Greek_Cappadocia
0.28056025 Georgian_Jew
0.28058260 Lebanese_Muslim
0.28136763 Mountain_Jew
0.28221703 Brahmin_Tamil_Nadu
0.28337370 Nenets
0.28393756 Iyer
0.28402583 Libyan_Jew
0.28540120 Cypriot
0.28554859 Assyrian
0.28561185 Georgian_Laz
0.28579750 Greenlander_East
0.28649552 Armenian
0.28668105 Turkish_Trabzon
0.28690686 Tunisian_Jew
0.28728552 Iranian_Jew
0.28784084 Greek_Trabzon
0.28792844 Druze
0.28796670 Jordanian
0.28796837 Lebanese_Druze
0.28900593 Georgian_Imer
0.28944965 Armenian_Hemsheni
0.28949870 Karaite_Egypt
0.29046411 Khakass_Kachins
0.29253684 Palestinian
0.29399600 Punjabi_Lahore
0.29475111 Kazakh_China
0.29550190 Lebanese_Christian
0.29567035 Sardinian
0.29710937 Kanjar
0.29738191 Altaian
0.30001066 Kol
0.30020257 Iraqi_Jew
0.30033705 BedouinA
0.30114767 Gujarati
0.30205517 Palestinian_Beit_Sahour
0.30444052 Dharkar
0.30470054 Kamboj_o
0.30547974 Bengali_Bangladesh
0.30829264 Cree
0.31118359 Uttar_Pradesh
0.31151678 Samaritan
0.31154818 Newar
0.31567485 Moroccan_North
0.31721780 Egyptian
0.31877023 Velamas
0.32116961 Yemenite_Amran
0.32197837 Tunisian
0.32242849 Brahmin_Manipuri
0.32261472 Libyan
0.32310611 Berber_Tunisia_Sen
0.32326646 Tunisian_Berber_Zraoua
0.32342068 Dusadh
0.32362802 Tunisian_Berber_Tamezret
0.32427386 Yadava
0.32629611 Tunisian_Berber_Matmata
0.32693104 Berber_Tunisia_Chen
0.32703113 Chenchu
0.32714518 Maratha
0.32751293 Gupta
0.32774029 Algerian
0.32951116 Chamar
0.33030263 Kurumba
0.33178901 Yemenite_Dhamar
0.33199331 Relli
0.33250841 Yemenite_Al_Bayda
0.33252596 Piramalai
0.33392443 Tunisian_Rbaya
0.33511725 Mozabite
0.33664712 Yemenite_Jew
0.33673466 Mogush
0.33754623 Yemenite_Ma'rib
0.33794440 Yemenite_Al_Jawf
0.33960721 Saudi
0.34040927 BedouinB
0.34046220 Mongolian
0.34112411 Tunisian_Douz
0.34174855 Moroccan
0.34213664 North_Kannadi
0.34417939 Buryat
0.34483883 Yemenite_Mahra
0.34499273 Kalmyk
0.34642576 Sakilli
0.34705145 Pallan
0.34725249 Tharu
0.34790131 Tuvinian
0.34860959 Hakkipikki
0.34984052 Madiga
0.35030310 Berber_MAR_ERR
0.35943917 Mala
0.36181724 Saharawi
0.36238680 Kusunda
0.36475803 Irula
0.36534483 Berber_MAR_TIZ
0.36625219 Jarawa
0.36679082 Onge
0.36903468 Pulliyar
0.37027838 Dolgan
0.37184266 Gond
0.37230356 Kadar
0.37475855 Todzin
0.37750908 Malayan
0.37869184 Paniya
0.37891200 Asur
0.38381305 Salar
0.38668094 Khamnegan
0.38729929 Santhal
0.38778582 Gadaba
0.38968394 Korwa
0.39004167 Bhumij
0.39057135 Dongxiang
0.39121233 Birhor
0.39186238 Ho
0.39254493 Magar
0.39452990 Tamang
0.39571250 Khonda_Dora
0.39643733 Moroccan_South
0.39915698 Itelmen
0.39992788 Bonda
0.40003650 Juang
0.40277939 Jehai
0.40437359 Dungan
0.40649043 Jamatia
0.40838807 Chukchi
0.40920505 Koryak
0.40922625 Yakut
0.40969679 Tripuri
0.41220448 Eskimo_Sireniki
0.41464338 Eskimo_Naukan
0.41524660 Aeta
0.41687192 Eskimo_Chaplin
0.41816111 Eskimo
0.41875168 Agta
0.41881051 Burmese
0.42236245 Sakha
0.42269930 Tibetan_Gannan
0.42313862 Gurung
0.42348923 Bonan
0.42594422 Tibetan_Gangcha
0.42666508 Yukagir_Tundra
0.42887441 Eritrean
0.42958390 Thai
0.43011580 Tibetan_Xunhua
0.43094662 Tu
0.43315572 Chipewyan
0.43583383 Ethiopian_Tigray
0.43704498 Tibetan_Shannan
0.43719947 Ethiopian_Afar
0.43793156 Batak
0.43810211 Daur
0.44009775 Rai
0.44163130 Tibetan_Shigatse
0.44171810 Sherpa
0.44218603 Mongola
0.44236009 Tibetan_Lhasa
0.44389445 Ethiopian_Amhara
0.44389801 Ethiopian_Agaw
0.44398930 Yugur
0.44526819 Oroqen
0.44848717 Tibetan_Nagqu
0.44854915 Nganassan
0.44863303 Xibo
0.44907041 Ethiopian_Jew
0.44995815 Hezhen
0.45234649 Evenk
0.45252840 Ulchi
0.45358977 Malay
0.45373335 Nivkh
0.45427803 Tibetan_Yajiang
0.45487600 Tibetan_Chamdo
0.45558790 Qiang_Daofu
0.45663122 Amerindian_North
0.45824487 Nanai
0.45828542 Cambodian
0.46055142 Tibetan_Yunnan
0.46393053 Even
0.46409532 Negidal
0.46519172 Bajo
0.46648478 Berber_Algeria
0.46701559 Naxi
0.46788616 Tibetan_Xinlong
0.46863498 Han_Shanxi
0.46872268 Vizayan
0.47056275 Yi
0.47311278 Qiang_Danba
0.47410044 Indonesian_Bali
0.47498801 Japanese
0.47510951 Han_Henan
0.47550162 Ethiopian_Oromo
0.47880729 Han_Shandong
0.47996557 Lahu
0.48152484 Korean
0.48303861 Han_Shanghai
0.48329972 Indonesian_Java
0.48405904 Kinh_Vietnam
0.48465739 Han_Sichuan
0.48497974 Hawaiian
0.48598676 Htin_Mal
0.48659085 Miao
0.48709231 Mlabri
0.48789895 Tujia
0.48924820 Han_Jiangsu
0.48931205 Han_Hubei
0.49030448 Han_Zhejiang
0.49082809 Han_Chongqing
0.49236244 Han_Fujian
0.49342304 Dai
0.49440681 Somali
0.49483275 Dong_Guizhou
0.49542191 Gelao
0.49630873 Han_Guangdong
0.49634768 She
0.49642959 Lebbo
0.49704409 Dong_Hunan
0.49809829 Mulam
0.49869223 Luzon
0.49938611 Zhuang
0.50035516 Ethiopian_Wolayta
0.50210426 Li
0.50307269 Maonan
0.50621327 Dusun
0.50766931 Atayal
0.50891863 Somali_Kenya
0.50934776 Bolivian_Pando
0.51299931 Murut
0.51587832 Ami
0.51764217 Igorot
0.51817834 Bolivian_Cochabamba
0.51819655 Quechua
0.52227296 Rendille
0.52570872 Mixtec
0.52769366 Zapotec
0.53195048 Nahua
0.53325173 Mayan
0.53448912 Iraqw
0.53783372 Huichol
0.53943051 Pima
0.54401582 Nasoi
0.54677984 Cachi
0.54881849 Fulani
0.55173718 Mixe
0.55738849 Colla
0.56132127 Datog
0.56238621 Bolivian_LaPaz
0.57681098 Elmolo
0.57767812 Aymara
0.57884793 Ethiopian_Ari_cultivator
0.58335229 Ethiopian_Ari
0.58394082 Yukpa
0.58462017 Australian
0.58787374 Ethiopian_Ari_blacksmith
0.58808332 Piapoco
0.59180871 Wichi
0.59370601 Ogiek
0.60234141 Masai
0.60846215 Karitiana
0.61551656 Surui
0.61623829 Sandawe
0.63766262 Sengwer
0.64134494 Kikuyu
0.64807313 Hadza
0.66541509 Bulala
0.67607824 Ethiopian_Gumuz
0.67817780 Ethiopian_Mursi
0.71698319 Ethiopian_Anuak
0.71990115 Sudanese
0.72193961 Dinka
0.72682026 Mada
0.73001356 Luhya_Kenya
0.73263443 Luo
0.73271824 Bantu_Kenya
0.73930267 Gambian
0.74038301 Mandenka
0.74302914 Kosipe
0.74431069 Mwani
0.74724866 Laka
0.75027704 Kaba
0.75198880 Cameroon_Bakoko
0.75222188 Bantu_S.W.
0.75237609 Makhuwa
0.75289913 Sena
0.75324728 Mende_Sierra_Leone
0.75398114 Ndau
0.75514393 Nyanja
0.75535578 Nyaneka
0.75554785 Cameroon_Bangwa
0.75561243 Umbundu
0.75593581 Yao
0.75668196 Lemande
0.75786467 Changana
0.75802250 Tikar_South
0.75816375 Kongo
0.75845956 Cameroon_Bafut
0.75847248 Ngumba
0.75858043 Cameroon_Aghem
0.75863189 Ganguela
0.75999052 Ronga
0.76005694 Cameroon_Mbo
0.76007099 Tswa
0.76027697 Chopi
0.76064415 Manyika
0.76136121 Bantu_S.E.
0.76235736 Bitonga
0.76265156 Igbo
0.76341361 Koinanbe
0.76341544 Yoruba
0.76350379 Papuan
0.76548946 Esan_Nigeria
0.79304734 Bedzan
0.79986920 Bakola
0.80198051 Baka
0.81603188 Biaka
0.85718579 Khomani_San
0.92754448 Ju_hoan_North
0.94221812 Mbuti
Zanzibar
02-25-2021, 12:41 AM
This is how they score on scaled Global25
Chukchi:
Distance to: Chukchi
0.05144905 Eskimo_Sireniki
0.05246831 Itelmen
0.05393111 Eskimo_Chaplin
0.05584933 Koryak
0.06919831 Eskimo
0.07634917 Eskimo_Naukan
0.12454608 Yukagir_Tundra
0.16683660 Greenlander_East
0.17236774 Todzin
0.17313255 Even
0.17792759 Negidal
0.18305369 Tuvinian
0.18328869 Ulchi
0.18351484 Khamnegan
0.18364967 Mogush
0.18784084 Nganassan
0.18822965 Nivkh
0.18838499 Evenk
0.19473998 Nanai
0.19887397 Dolgan
0.20198147 Buryat
0.20492081 Nenets
0.20545313 Oroqen
0.20594544 Khakass_Kachins
0.20867591 Kalmyk
0.21082288 Altaian
0.21173955 Mongolian
0.21452292 Selkup
0.22500173 Greenlander_West
0.22518165 Khakass
0.22520998 Chipewyan
0.22715263 Hezhen
0.22928000 Kazakh_China
0.23314800 Daur
0.23613302 Kirghiz
0.23973206 Kirghiz_China
0.24047722 Shor_Khakassia
0.24234787 Shor
0.24402121 Yakut
0.24462334 Shor_Mountain
0.24545292 Amerindian_North
0.24830167 Sakha
0.25451722 Tubalar
0.25542039 Xibo
0.25971278 Mongola
0.25976259 Kazakh
0.26641301 Tibetan_Gangcha
0.27098751 Dongxiang
0.27101527 Cree
0.27261786 Khanty
0.27379685 Salar
0.27649099 Tu
0.27737859 Tibetan_Shigatse
0.27739983 Tibetan_Xunhua
0.27753652 Tibetan_Shannan
0.27758677 Ket
0.27906903 Dungan
0.27929956 Tibetan_Lhasa
0.27984307 Bonan
0.28032684 Tibetan_Nagqu
0.28211199 Sherpa
0.28212704 Gurung
0.28239830 Tibetan_Gannan
0.28255251 Magar
0.28269242 Tamang
0.28302240 Tibetan_Chamdo
0.28400469 Mansi
0.28490101 Tatar_Siberian_Zabolotniye
0.28493551 Yugur
0.28536379 Karakalpak
0.28575438 Qiang_Daofu
0.28698272 Rai
0.28730854 Tlingit
0.28866709 Tibetan_Yajiang
0.29049333 Tibetan_Yunnan
0.29255957 Japanese
0.29321849 Yukagir_Forest
0.29549905 Korean
0.30024019 Tibetan_Xinlong
0.30026806 Han_Shanxi
0.30068444 Tripuri
0.30141388 Qiang_Danba
0.30228373 Kusunda
0.30255377 Jamatia
0.30318210 Burmese
0.30516481 Yi
0.30536644 Naxi
0.30551417 Tatar_Siberian
0.30584919 Han_Shandong
0.30660090 Han_Henan
0.30826185 Nogai
0.31186238 Tharu
0.31302029 Hazara
0.31805102 Uygur
0.31958523 Han_Jiangsu
0.32039522 Brahmin_Manipuri
0.32062975 Han_Shanghai
0.32158881 Han_Hubei
0.32170661 Newar
0.32219332 Hazara_Afghanistan
0.32246574 Han_Sichuan
0.32452683 Han_Zhejiang
0.32733758 Tujia
0.33063506 Han_Chongqing
0.33266152 Miao
0.33461253 Han_Fujian
0.33705073 Thai
0.33896337 Bashkir
0.34058772 Lahu
0.34162094 She
0.34456817 Han_Guangdong
0.34999189 Dong_Guizhou
0.35001392 Dong_Hunan
0.35075040 Kinh_Vietnam
0.35358016 Uzbek
0.35569198 Cambodian
0.35688177 Aeta
0.35703315 Mulam
0.35772364 Gelao
0.35838305 Zhuang
0.36016272 Agta
0.36093267 Vizayan
0.36278467 Malay
0.36291987 Dai
0.36443657 Batak
0.36537995 Jehai
0.36556764 Mixtec
0.36566569 Maonan
0.36599952 Huichol
0.36622119 Zapotec
0.36647137 Pima
0.36674400 Nahua
0.37022340 Li
0.37400671 Hawaiian
0.37453277 Onge
0.37482517 Bolivian_Pando
0.37526052 Mayan
0.37612652 Bajo
0.37621421 Jarawa
0.37644154 Mixe
0.37845569 Bolivian_Cochabamba
0.37875812 Atayal
0.37907095 Htin_Mal
0.37983117 Luzon
0.38077128 Quechua
0.38391638 Mlabri
0.38446504 Indonesian_Bali
0.38547604 Ami
0.38710811 Indonesian_Java
0.39043291 Cachi
0.39102348 Lebbo
0.39166985 Igorot
0.39324904 Maori
0.39345667 Dusun
0.39634050 Turkmen_Uzbekistan
0.39729022 Mari
0.39746078 Murut
0.39821775 Tatar_Crimean_steppe
0.39868560 Bolivian_LaPaz
0.39933712 Bonda
0.39939769 Juang
0.39995957 Colla
0.40191571 Bahun
0.40396012 Gadaba
0.40450450 Turkmen
0.40837100 Aymara
0.40838807 Saami
0.41030231 Khonda_Dora
0.41315032 Udmurt
0.41538226 Yukpa
0.41681040 Korwa
0.41774057 Piapoco
0.41825935 Birhor
0.41871441 Tatar_Lipka
0.41918012 Ho
0.42077442 Wichi
0.42449173 Santhal
0.42528632 Besermyan
0.42695543 Bhumij
0.42785822 Chuvash
0.42867269 Asur
0.43282810 Gond
0.43744510 Bengali_Bangladesh
0.44220874 Karitiana
0.44233071 Burusho
0.44710488 Tatar_Kazan
0.44759832 Chenchu
0.45016139 Paniya
0.45085508 Kadar
0.45144851 Surui
0.45175307 Irula
0.45270378 Relli
0.45304988 Saami_Kola
0.45392181 Malayan
0.45614557 Pulliyar
0.45784309 Brahmin_West_Bengal
0.45925790 North_Kannadi
0.46136008 Hakkipikki
0.46185792 Tajik
0.46205070 Uttar_Pradesh
0.46301080 Kamboj_o
0.46357747 Madiga
0.46387902 Pallan
0.46426374 Dusadh
0.46438603 Yadava
0.46511129 Kol
0.46516388 Maratha
0.46552623 Dharkar
0.46567247 Chamar
0.46575555 Komi
0.46615737 Kanjar
0.46748473 Punjabi_Lahore
0.46827679 Kshatriya
0.46829298 Mala
0.46894269 Kurumba
0.46953775 Brahmin_Tamil_Nadu
0.46970219 Kho_Singanali
0.47057448 Sakilli
0.47066661 Kashmiri_Pandit
0.47102981 Piramalai
0.47207599 Velamas
0.47260738 Iyer
0.47409872 Gujarati
0.47445850 Kohistani
0.47649400 Tatar_Mishar
0.47668425 Brahmin_Gujarat
0.47967617 Brahmin_Uttar_Pradesh
0.48048834 Tajik_Ishkashim
0.48209592 Gupta
0.48249075 Punjabi_Sikh_India
0.48303491 Pashtun
0.48305653 Gujar_India
0.48329926 Jatt_Pathak
0.48348705 Tajik_Shugnan
0.48440404 Khatri
0.48601458 Ror
0.48701751 Punjabi_Jatt
0.48763482 Gujar_Pakistan
0.48813836 Kamboj
0.48841073 Yusufzai
0.48871651 Uthmankhel
0.48889579 Sindhi
0.49093281 Tarkalani
0.49180271 Tajik_Rushan
0.49351515 Kalash
0.49668033 Turkish_South
0.49711573 Turkish_Northwest
0.49936588 Turkish_Southwest
0.49972452 Turkish_Balikesir
0.50039999 Turkish_Aydin
0.50588061 Russian_Pinega
0.50847591 Turkish_North
0.51105919 Tajik_Yagnobi
0.51421268 Vepsian
0.51530653 Roma_Balkans
0.51733443 Brahui
0.51783351 Finnish_East
0.51840199 Abazin
0.51902955 Karelian
0.51935316 Balochi
0.52199604 Roma_Granada
0.52235551 Mordovian
0.52281681 Roma_Bilbao
0.52407091 Kabardin
0.52430099 Parsi_India
0.52442995 Parsi_Pakistan
0.52524100 Cherkes
0.52541988 Karachay
0.52561052 Roma_Porto
0.52578893 Turkish_Central
0.52665071 Turkish_Rumeli
0.52669676 Balkar
0.52690097 Circassian
0.52705563 Makrani
0.52847027 Russian_Kostroma
0.52923609 Kumyk
0.53045195 Iranian_Bandari
0.53257306 Ingrian
0.53299754 Finnish
0.53347443 Turkish_Adana
0.53428738 Roma_Madrid
0.53443660 Azeri
0.53506996 North_Ossetian
0.53759528 Nasoi
0.53846194 Turkish_Deliorman
0.53905948 Iranian_Seyyed
0.53906209 Azeri_Dagestan
0.53986763 Azeri_Turkey
0.54006354 Turkish_Kayseri
0.54016544 Roma_Barcelona
0.54090207 Cossack_Kuban
0.54189871 Iranian_Fars
0.54192317 Ingushian
0.54300809 Lak
0.54344199 Darginian
0.54475384 Tabasaran
0.54503324 Avar
0.54560065 Ossetian
0.54572949 Chechen
0.54608083 Adygei
0.54637451 Kaitag
0.54829815 Kubachinian
0.54991104 Russian_Tver
0.55119419 Talysh_Azerbaijan
0.55282300 Iranian_Lor
0.55287638 Iranian_Zoroastrian
0.55309289 Turkish_East
0.55317881 Iranian_Mazandarani
0.55611772 Ezid
0.55629483 Russian_Kursk
0.55696083 Moldovan_o
0.55836110 Cossack_Ukrainian
0.55884792 Russian_Orel
0.55999437 Estonian
0.56059004 Kurdish
0.56189190 Russian_Voronez
0.56294310 Abkhasian
0.56332827 Moldovan
0.56445084 Ukrainian
0.56459767 Iraqi
0.56565761 Afrikaner
0.56638536 Hungarian
0.56661643 Russian_Smolensk
0.56702991 Belarusian
0.56754833 Syrian
0.56777164 Norwegian
0.56781459 Ashkenazi_Russia
0.56831219 Swedish
0.56831604 Slovakian
0.56899312 Lithuanian_PA
0.56941906 Ashkenazi_Lithuania
0.56947180 Romanian
0.56980371 Udi
0.56986254 Polish
0.57008371 Gagauz
0.57010855 Bosnian
0.57011136 Dutch
0.57015265 Bulgarian
0.57025220 Czech
0.57041342 Croatian
0.57053232 Ashkenazi_Belarussia
0.57072601 Lithuanian_RA
0.57088168 Slovenian
0.57092123 Austrian
0.57101468 Lithuanian_VA
0.57103400 Latvian
0.57126057 Ashkenazi_Ukraine
0.57221228 Montenegrin
0.57245261 Orcadian
0.57284130 Shetlandic
0.57291654 Ashkenazi_Poland
0.57299349 Serbian
0.57299622 Scottish
0.57330901 Icelandic
0.57342875 Irish
0.57378332 Lithuanian_VZ
0.57429445 Lithuanian_SZ
0.57431486 Lithuanian_PZ
0.57444085 Danish
0.57462078 German
0.57465311 Mountain_Jew
0.57469981 Jordanian
0.57485898 Belgian
0.57532879 English
0.57550648 German_East
0.57562594 Lebanese_Muslim
0.57609076 Rumelia_East
0.57625088 Georgian_Jew
0.57632167 French_Brittany
0.57639781 French_Nord
0.57644386 French_Alsace
0.57670095 Swiss_Italian
0.57686023 Welsh
0.57709995 Macedonian
0.57735016 Albanian
0.57742296 Greek_Central_Macedonia
0.57758211 French_Seine-Maritime
0.57792565 Palestinian
0.57796601 Greek_Macedonia
0.57801453 BedouinA
0.57804005 Swiss_German
0.57818402 French_Pas-de-Calais
0.57828741 English_Cornwall
0.57871136 Iranian_Jew
0.57878882 Spanish_Murcia
0.57909693 Assyrian
0.57927794 Spanish_Canarias
0.57949527 Italian_Northeast
0.57949683 French_Paris
0.57961652 Sorb_Niederlausitz
0.58000210 Ashkenazi_Germany
0.58014038 French_Provence
0.58019098 Greek_Thessaly
0.58043836 Greek_Peloponnese
0.58045338 Maltese
0.58093590 Portuguese
0.58107460 Italian_Liguria
0.58121445 Sephardic_Jew
0.58133429 Greek_Izmir
0.58155641 Spanish_Castilla_Y_Leon
0.58156060 Spanish_Camp_de_Tarragona
0.58167553 French_Auvergne
0.58174840 Spanish_Asturias
0.58176896 Moroccan_Jew
0.58195232 Spanish_Galicia
0.58218798 French_Occitanie
0.58225478 Sicilian_West
0.58229444 Swiss_French
0.58231617 Italian_Aosta_Valley
0.58240252 Spanish_Soria
0.58261008 Italian_Molise
0.58265598 Spanish_Penedes
0.58273767 Spanish_Valencia
0.58281599 Spanish_Cataluna
0.58283570 Spanish_Girona
0.58286242 Libyan
0.58299770 Syrian_Jew
0.58304372 Egyptian
0.58311173 Italian_Trentino-Alto-Adige
0.58317606 Spanish_Alacant
0.58318324 Lebanese_Druze
0.58320772 Greek_Crete
0.58321756 Italian_Basilicata
0.58322173 Spanish_Baleares
0.58330811 Italian_Calabria
0.58342361 Italian_Umbria
0.58343300 Spanish_Andalucia
0.58355504 Romaniote_Jew
0.58355798 Italian_Piedmont
0.58369930 Spanish_Eivissa
0.58376074 Sicilian_East
0.58393624 Armenian
0.58394559 Italian_Jew
0.58394990 Spanish_Lleida
0.58401057 Italian_Marche
0.58402645 Italian_Lombardy
0.58408834 Spanish_Mallorca
0.58408964 Druze
0.58411031 Georgian_Imer
0.58421551 Armenian_Hemsheni
0.58422246 Spanish_Castello
0.58430426 Greek_Cappadocia
0.58448456 Italian_Tuscany
0.58450234 Turkish_Trabzon
0.58459290 Spanish_Castilla_La_Mancha
0.58464491 Georgian_Laz
0.58483093 Spanish_Extremadura
0.58483424 Italian_Abruzzo
0.58485439 Spanish_Terres_de_l'Ebre
0.58488833 Libyan_Jew
0.58499767 Italian_Veneto
0.58512696 Spanish_Pirineu
0.58523785 Italian_Apulia
0.58525159 Spanish_Menorca
0.58527800 Tunisian
0.58557448 Italian_Campania
0.58565504 Spanish_Navarra
0.58580688 Greek_Dodecanese
0.58581414 Spanish_Aragon
0.58585241 Greek_Central_Anatolia
0.58585545 French_South
0.58594802 Spanish_Cantabria
0.58618034 Greek_Trabzon
0.58625979 Greek_Laconia
0.58630299 Greek_Kos
0.58655188 Tunisian_Jew
0.58683481 Karaite_Egypt
0.58693842 Italian_Bergamo
0.58696518 Spanish_Barcelones
0.58699190 Spanish_Peri-Barcelona
0.58699783 Tunisian_Berber_Matmata
0.58743676 Algerian
0.58770851 Spanish_Catalunya_Central
0.58786753 Moroccan_North
0.58794656 Berber_Tunisia_Sen
0.58876566 Tunisian_Berber_Tamezret
0.58892653 Iraqi_Jew
0.58895840 Cypriot
0.58934987 French_Corsica
0.58937704 Italian_Lazio
0.58953621 Lebanese_Christian
0.59003513 Yemenite_Amran
0.59004758 Tunisian_Berber_Zraoua
0.59053242 Tunisian_Douz
0.59151170 Moroccan
0.59225548 Spanish_Pais_Vasco
0.59275465 Spanish_La_Rioja
0.59304621 Berber_Tunisia_Chen
0.59318449 Palestinian_Beit_Sahour
0.59340049 Basque_Spanish
0.59346331 Mozabite
0.59455721 Basque_French
0.59508987 Tunisian_Rbaya
0.59521266 Australian
0.59566382 Berber_MAR_ERR
0.59720053 Yemenite_Dhamar
0.59728807 Yemenite_Al_Bayda
0.59799399 Samaritan
0.60103621 Saharawi
0.60269101 Yemenite_Al_Jawf
0.60312132 Yemenite_Jew
0.60318306 Saudi
0.60325129 Yemenite_Ma'rib
0.60390806 Berber_MAR_TIZ
0.60410727 Yemenite_Mahra
0.60475044 BedouinB
0.61009049 Moroccan_South
0.61880844 Sardinian
0.62046501 Eritrean
0.62123483 Ethiopian_Afar
0.62320114 Ethiopian_Tigray
0.62698292 Ethiopian_Agaw
0.62762304 Ethiopian_Amhara
0.63059454 Ethiopian_Jew
0.64118882 Berber_Algeria
0.64137285 Ethiopian_Oromo
0.65264939 Ethiopian_Wolayta
0.65269011 Somali
0.66163471 Somali_Kenya
0.66910794 Rendille
0.67457316 Iraqw
0.68987883 Fulani
0.69286872 Datog
0.69956792 Ethiopian_Ari_cultivator
0.70227648 Ethiopian_Ari
0.70285620 Elmolo
0.70436285 Ethiopian_Ari_blacksmith
0.71379959 Ogiek
0.71966052 Masai
0.72755092 Sandawe
0.74235614 Sengwer
0.74640893 Hadza
0.74865314 Kikuyu
0.75138257 Kosipe
0.76606845 Bulala
0.76692339 Ethiopian_Gumuz
0.77126182 Ethiopian_Mursi
0.77152610 Koinanbe
0.77181447 Papuan
0.80192222 Ethiopian_Anuak
0.80367281 Dinka
0.80457044 Sudanese
0.81167587 Mada
0.81581998 Luhya_Kenya
0.81770141 Luo
0.81909075 Bantu_Kenya
0.82455947 Mandenka
0.82532587 Gambian
0.82886774 Mwani
0.82986637 Laka
0.83240404 Kaba
0.83359411 Makhuwa
0.83517370 Cameroon_Bakoko
0.83519458 Sena
0.83550040 Bantu_S.W.
0.83575378 Ndau
0.83614200 Mende_Sierra_Leone
0.83643236 Nyanja
0.83701989 Nyaneka
0.83736661 Yao
0.83766266 Umbundu
0.83777742 Cameroon_Bangwa
0.83813526 Lemande
0.83936511 Cameroon_Bafut
0.83941443 Ngumba
0.83947176 Ganguela
0.83956136 Changana
0.83960049 Cameroon_Aghem
0.84010982 Kongo
0.84014441 Ronga
0.84049661 Tikar_South
0.84051354 Chopi
0.84119888 Tswa
0.84145339 Manyika
0.84162023 Cameroon_Mbo
0.84224448 Bantu_S.E.
0.84293414 Bitonga
0.84409525 Yoruba
0.84415993 Igbo
0.84637199 Esan_Nigeria
0.87100643 Bedzan
0.87521630 Bakola
0.87945893 Baka
0.89117327 Biaka
0.92970851 Khomani_San
0.99457570 Ju_hoan_North
1.00762217 Mbuti
Saami:
Distance to: Saami
0.05165166 Saami_Kola
0.05229796 Udmurt
0.06021780 Besermyan
0.07106311 Chuvash
0.07375363 Komi
0.08198600 Tatar_Kazan
0.09534176 Mari
0.10053647 Tatar_Mishar
0.10443703 Tatar_Lipka
0.10963287 Russian_Pinega
0.11182593 Bashkir
0.11883667 Vepsian
0.12036459 Finnish_East
0.12213113 Karelian
0.12774128 Tatar_Crimean_steppe
0.13412494 Mordovian
0.13609329 Russian_Kostroma
0.13690079 Ingrian
0.13826217 Finnish
0.14160670 Yukagir_Forest
0.14216068 Tatar_Siberian
0.15078272 Cossack_Kuban
0.15607780 Tatar_Siberian_Zabolotniye
0.15796967 Tlingit
0.16075159 Russian_Tver
0.16336793 Turkmen
0.16459138 Turkmen_Uzbekistan
0.16632238 Estonian
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
0.17686750 Moldovan_o
0.17822236 Tajik_Rushan
0.17827602 Tajik_Shugnan
0.17926072 Belarusian
0.17927329 Ukrainian
0.17931411 Latvian
0.17952044 Russian_Smolensk
0.17971434 Lithuanian_PA
0.18073708 Lithuanian_VA
0.18076503 Lithuanian_RA
0.18157993 Nogai
0.18221751 Lithuanian_SZ
0.18279075 Swedish
0.18283221 Lithuanian_VZ
0.18283997 Lithuanian_PZ
0.18381285 Polish
0.18547941 Slovakian
0.18560255 Norwegian
0.18837516 Tajik_Ishkashim
0.18848438 Khanty
0.18862550 Czech
0.18949914 Hungarian
0.19039592 Icelandic
0.19087737 Dutch
0.19112002 Turkish_Deliorman
0.19124715 Turkish_Rumeli
0.19176339 Afrikaner
0.19226524 Danish
0.19384756 Shetlandic
0.19394972 Orcadian
0.19445420 Sorb_Niederlausitz
0.19452394 Scottish
0.19459547 German_East
0.19534091 Irish
0.19587038 Croatian
0.19604462 Austrian
0.19634888 Turkish_Northwest
0.19636953 Slovenian
0.19658845 Tajik_Yagnobi
0.19673689 Moldovan
0.19719818 German
0.19724073 Turkish_Balikesir
0.19782542 English
0.19927325 Welsh
0.20060210 Ket
0.20117721 Bosnian
0.20118615 French_Brittany
0.20157132 English_Cornwall
0.20194140 Hazara_Afghanistan
0.20361165 Turkish_Southwest
0.20432707 Uygur
0.20439751 Belgian
0.20445223 Roma_Barcelona
0.20462215 Turkish_Aydin
0.20562802 French_Seine-Maritime
0.20633981 Maori
0.20636918 Karakalpak
0.20650501 French_Pas-de-Calais
0.20682974 French_Nord
0.20693335 Turkish_South
0.20699293 Kho_Singanali
0.20726226 French_Alsace
0.20795723 Montenegrin
0.20798674 Serbian
0.20854188 Jatt_Pathak
0.20953171 Romanian
0.21012969 Roma_Bilbao
0.21019578 Swiss_German
0.21102027 Hazara
0.21116312 Roma_Madrid
0.21116963 Ror
0.21145083 French_Paris
0.21361686 Turkish_North
0.21417279 Abazin
0.21418889 Bulgarian
0.21429159 Roma_Granada
0.21462089 Roma_Porto
0.21499635 Kabardin
0.21507515 Cherkes
0.21511053 Roma_Balkans
0.21634777 Kumyk
0.21653079 Tubalar
0.21776706 French_Occitanie
0.21786404 Gagauz
0.21818609 Darginian
0.21819196 Balkar
0.21824446 Macedonian
0.21838606 Greenlander_West
0.21869659 Circassian
0.21889639 French_Auvergne
0.21933852 Karachay
0.21995853 Avar
0.21998347 Kaitag
0.22026626 Swiss_French
0.22034786 Burusho
0.22059482 Lak
0.22134912 French_Provence
0.22167998 Tabasaran
0.22180535 Italian_Northeast
0.22249621 Uthmankhel
0.22359130 Pashtun
0.22384145 Italian_Aosta_Valley
0.22472817 Kubachinian
0.22491409 Tarkalani
0.22499092 Spanish_Camp_de_Tarragona
0.22592539 Spanish_Penedes
0.22631736 Spanish_Girona
0.22637707 Spanish_Soria
0.22686358 Yusufzai
0.22694372 Kalash
0.22746928 Spanish_Cataluna
0.22796941 Spanish_Lleida
0.22832028 Spanish_Castilla_Y_Leon
0.22836868 Spanish_Barcelones
0.22852135 Spanish_Mallorca
0.22875742 Turkish_Central
0.22881186 Italian_Trentino-Alto-Adige
0.22888814 Shor_Mountain
0.22894406 French_South
0.22905624 Spanish_Galicia
0.22938034 Swiss_Italian
0.22944763 Spanish_Valencia
0.22947054 Spanish_Pirineu
0.22957599 Spanish_Baleares
0.22981432 Spanish_Castello
0.22988411 Spanish_Catalunya_Central
0.23026006 Spanish_Cantabria
0.23030883 Spanish_Eivissa
0.23038721 Spanish_Murcia
0.23056844 Portuguese
0.23057927 Spanish_Peri-Barcelona
0.23064760 Chechen
0.23082048 Spanish_Alacant
0.23087119 Spanish_Terres_de_l'Ebre
0.23096605 Spanish_Asturias
0.23103212 Ingushian
0.23134900 Shor_Khakassia
0.23139644 Rumelia_East
0.23160167 Italian_Veneto
0.23233423 North_Ossetian
0.23259576 Spanish_Aragon
0.23260692 Spanish_Andalucia
0.23274092 Spanish_Castilla_La_Mancha
0.23286304 Shor
0.23304636 Greek_Central_Macedonia
0.23311248 Spanish_Menorca
0.23346567 Spanish_Navarra
0.23399951 Spanish_Extremadura
0.23429169 Turkish_Adana
0.23429490 Greek_Macedonia
0.23442998 Albanian
0.23465355 Punjabi_Jatt
0.23472822 Italian_Liguria
0.23477325 Kamboj
0.23479057 Azeri_Dagestan
0.23482051 Spanish_Pais_Vasco
0.23533737 Adygei
0.23572340 Basque_French
0.23581486 Kazakh
0.23687648 Italian_Piedmont
0.23699127 Basque_Spanish
0.23733768 Italian_Bergamo
0.23760903 Spanish_Canarias
0.23791360 Kohistani
0.23812838 Italian_Lombardy
0.23818118 Kashmiri_Pandit
0.23847295 Greek_Thessaly
0.23931373 Punjabi_Sikh_India
0.24101451 Turkish_Kayseri
0.24157317 Spanish_La_Rioja
0.24183627 Khatri
0.24292289 Greek_Peloponnese
0.24300897 Italian_Tuscany
0.24324375 Ashkenazi_Russia
0.24396832 Azeri
0.24413804 Ossetian
0.24446487 Bahun
0.24581833 Ashkenazi_Belarussia
0.24624821 Ashkenazi_Ukraine
0.24629777 Ashkenazi_Lithuania
0.24675200 Azeri_Turkey
0.24702133 Italian_Marche
0.24721748 Italian_Umbria
0.24806275 Parsi_Pakistan
0.24844101 French_Corsica
0.24966152 Ashkenazi_Poland
0.24980008 Italian_Molise
0.24988853 Greek_Izmir
0.24997522 Parsi_India
0.25070430 Iranian_Fars
0.25112561 Khakass
0.25131387 Sicilian_West
0.25141987 Iranian_Seyyed
0.25209750 Greek_Laconia
0.25223944 Gujar_Pakistan
0.25296651 Italian_Abruzzo
0.25312698 Sindhi
0.25335245 Italian_Lazio
0.25421206 Turkish_East
0.25572831 Iranian_Zoroastrian
0.25607982 Italian_Basilicata
0.25662969 Iranian_Bandari
0.25687057 Maltese
0.25711336 Balochi
0.25726530 Italian_Apulia
0.25744236 Brahui
0.25801235 Sicilian_East
0.25824113 Brahmin_Gujarat
0.25839003 Ezid
0.25908810 Talysh_Azerbaijan
0.26030544 Greek_Crete
0.26070124 Gujar_India
0.26071234 Italian_Campania
0.26118616 Ashkenazi_Germany
0.26229518 Italian_Calabria
0.26423832 Iranian_Lor
0.26444679 Makrani
0.26454310 Kurdish
0.26523514 Brahmin_West_Bengal
0.26614517 Udi
0.26631614 Abkhasian
0.26807413 Iranian_Mazandarani
0.26984022 Greek_Kos
0.26991056 Italian_Jew
0.27029943 Selkup
0.27052103 Sephardic_Jew
0.27196410 Kshatriya
0.27200529 Greek_Dodecanese
0.27235421 Moroccan_Jew
0.27295840 Brahmin_Uttar_Pradesh
0.27322436 Kirghiz
0.27485559 Syrian
0.27491232 Kirghiz_China
0.27599089 Romaniote_Jew
0.27866649 Greek_Central_Anatolia
0.27917442 Syrian_Jew
0.27962127 Iraqi
0.27967688 Greek_Cappadocia
0.28056025 Georgian_Jew
0.28058260 Lebanese_Muslim
0.28136763 Mountain_Jew
0.28221703 Brahmin_Tamil_Nadu
0.28337370 Nenets
0.28393756 Iyer
0.28402583 Libyan_Jew
0.28540120 Cypriot
0.28554859 Assyrian
0.28561185 Georgian_Laz
0.28579750 Greenlander_East
0.28649552 Armenian
0.28668105 Turkish_Trabzon
0.28690686 Tunisian_Jew
0.28728552 Iranian_Jew
0.28784084 Greek_Trabzon
0.28792844 Druze
0.28796670 Jordanian
0.28796837 Lebanese_Druze
0.28900593 Georgian_Imer
0.28944965 Armenian_Hemsheni
0.28949870 Karaite_Egypt
0.29046411 Khakass_Kachins
0.29253684 Palestinian
0.29399600 Punjabi_Lahore
0.29475111 Kazakh_China
0.29550190 Lebanese_Christian
0.29567035 Sardinian
0.29710937 Kanjar
0.29738191 Altaian
0.30001066 Kol
0.30020257 Iraqi_Jew
0.30033705 BedouinA
0.30114767 Gujarati
0.30205517 Palestinian_Beit_Sahour
0.30444052 Dharkar
0.30470054 Kamboj_o
0.30547974 Bengali_Bangladesh
0.30829264 Cree
0.31118359 Uttar_Pradesh
0.31151678 Samaritan
0.31154818 Newar
0.31567485 Moroccan_North
0.31721780 Egyptian
0.31877023 Velamas
0.32116961 Yemenite_Amran
0.32197837 Tunisian
0.32242849 Brahmin_Manipuri
0.32261472 Libyan
0.32310611 Berber_Tunisia_Sen
0.32326646 Tunisian_Berber_Zraoua
0.32342068 Dusadh
0.32362802 Tunisian_Berber_Tamezret
0.32427386 Yadava
0.32629611 Tunisian_Berber_Matmata
0.32693104 Berber_Tunisia_Chen
0.32703113 Chenchu
0.32714518 Maratha
0.32751293 Gupta
0.32774029 Algerian
0.32951116 Chamar
0.33030263 Kurumba
0.33178901 Yemenite_Dhamar
0.33199331 Relli
0.33250841 Yemenite_Al_Bayda
0.33252596 Piramalai
0.33392443 Tunisian_Rbaya
0.33511725 Mozabite
0.33664712 Yemenite_Jew
0.33673466 Mogush
0.33754623 Yemenite_Ma'rib
0.33794440 Yemenite_Al_Jawf
0.33960721 Saudi
0.34040927 BedouinB
0.34046220 Mongolian
0.34112411 Tunisian_Douz
0.34174855 Moroccan
0.34213664 North_Kannadi
0.34417939 Buryat
0.34483883 Yemenite_Mahra
0.34499273 Kalmyk
0.34642576 Sakilli
0.34705145 Pallan
0.34725249 Tharu
0.34790131 Tuvinian
0.34860959 Hakkipikki
0.34984052 Madiga
0.35030310 Berber_MAR_ERR
0.35943917 Mala
0.36181724 Saharawi
0.36238680 Kusunda
0.36475803 Irula
0.36534483 Berber_MAR_TIZ
0.36625219 Jarawa
0.36679082 Onge
0.36903468 Pulliyar
0.37027838 Dolgan
0.37184266 Gond
0.37230356 Kadar
0.37475855 Todzin
0.37750908 Malayan
0.37869184 Paniya
0.37891200 Asur
0.38381305 Salar
0.38668094 Khamnegan
0.38729929 Santhal
0.38778582 Gadaba
0.38968394 Korwa
0.39004167 Bhumij
0.39057135 Dongxiang
0.39121233 Birhor
0.39186238 Ho
0.39254493 Magar
0.39452990 Tamang
0.39571250 Khonda_Dora
0.39643733 Moroccan_South
0.39915698 Itelmen
0.39992788 Bonda
0.40003650 Juang
0.40277939 Jehai
0.40437359 Dungan
0.40649043 Jamatia
0.40838807 Chukchi
0.40920505 Koryak
0.40922625 Yakut
0.40969679 Tripuri
0.41220448 Eskimo_Sireniki
0.41464338 Eskimo_Naukan
0.41524660 Aeta
0.41687192 Eskimo_Chaplin
0.41816111 Eskimo
0.41875168 Agta
0.41881051 Burmese
0.42236245 Sakha
0.42269930 Tibetan_Gannan
0.42313862 Gurung
0.42348923 Bonan
0.42594422 Tibetan_Gangcha
0.42666508 Yukagir_Tundra
0.42887441 Eritrean
0.42958390 Thai
0.43011580 Tibetan_Xunhua
0.43094662 Tu
0.43315572 Chipewyan
0.43583383 Ethiopian_Tigray
0.43704498 Tibetan_Shannan
0.43719947 Ethiopian_Afar
0.43793156 Batak
0.43810211 Daur
0.44009775 Rai
0.44163130 Tibetan_Shigatse
0.44171810 Sherpa
0.44218603 Mongola
0.44236009 Tibetan_Lhasa
0.44389445 Ethiopian_Amhara
0.44389801 Ethiopian_Agaw
0.44398930 Yugur
0.44526819 Oroqen
0.44848717 Tibetan_Nagqu
0.44854915 Nganassan
0.44863303 Xibo
0.44907041 Ethiopian_Jew
0.44995815 Hezhen
0.45234649 Evenk
0.45252840 Ulchi
0.45358977 Malay
0.45373335 Nivkh
0.45427803 Tibetan_Yajiang
0.45487600 Tibetan_Chamdo
0.45558790 Qiang_Daofu
0.45663122 Amerindian_North
0.45824487 Nanai
0.45828542 Cambodian
0.46055142 Tibetan_Yunnan
0.46393053 Even
0.46409532 Negidal
0.46519172 Bajo
0.46648478 Berber_Algeria
0.46701559 Naxi
0.46788616 Tibetan_Xinlong
0.46863498 Han_Shanxi
0.46872268 Vizayan
0.47056275 Yi
0.47311278 Qiang_Danba
0.47410044 Indonesian_Bali
0.47498801 Japanese
0.47510951 Han_Henan
0.47550162 Ethiopian_Oromo
0.47880729 Han_Shandong
0.47996557 Lahu
0.48152484 Korean
0.48303861 Han_Shanghai
0.48329972 Indonesian_Java
0.48405904 Kinh_Vietnam
0.48465739 Han_Sichuan
0.48497974 Hawaiian
0.48598676 Htin_Mal
0.48659085 Miao
0.48709231 Mlabri
0.48789895 Tujia
0.48924820 Han_Jiangsu
0.48931205 Han_Hubei
0.49030448 Han_Zhejiang
0.49082809 Han_Chongqing
0.49236244 Han_Fujian
0.49342304 Dai
0.49440681 Somali
0.49483275 Dong_Guizhou
0.49542191 Gelao
0.49630873 Han_Guangdong
0.49634768 She
0.49642959 Lebbo
0.49704409 Dong_Hunan
0.49809829 Mulam
0.49869223 Luzon
0.49938611 Zhuang
0.50035516 Ethiopian_Wolayta
0.50210426 Li
0.50307269 Maonan
0.50621327 Dusun
0.50766931 Atayal
0.50891863 Somali_Kenya
0.50934776 Bolivian_Pando
0.51299931 Murut
0.51587832 Ami
0.51764217 Igorot
0.51817834 Bolivian_Cochabamba
0.51819655 Quechua
0.52227296 Rendille
0.52570872 Mixtec
0.52769366 Zapotec
0.53195048 Nahua
0.53325173 Mayan
0.53448912 Iraqw
0.53783372 Huichol
0.53943051 Pima
0.54401582 Nasoi
0.54677984 Cachi
0.54881849 Fulani
0.55173718 Mixe
0.55738849 Colla
0.56132127 Datog
0.56238621 Bolivian_LaPaz
0.57681098 Elmolo
0.57767812 Aymara
0.57884793 Ethiopian_Ari_cultivator
0.58335229 Ethiopian_Ari
0.58394082 Yukpa
0.58462017 Australian
0.58787374 Ethiopian_Ari_blacksmith
0.58808332 Piapoco
0.59180871 Wichi
0.59370601 Ogiek
0.60234141 Masai
0.60846215 Karitiana
0.61551656 Surui
0.61623829 Sandawe
0.63766262 Sengwer
0.64134494 Kikuyu
0.64807313 Hadza
0.66541509 Bulala
0.67607824 Ethiopian_Gumuz
0.67817780 Ethiopian_Mursi
0.71698319 Ethiopian_Anuak
0.71990115 Sudanese
0.72193961 Dinka
0.72682026 Mada
0.73001356 Luhya_Kenya
0.73263443 Luo
0.73271824 Bantu_Kenya
0.73930267 Gambian
0.74038301 Mandenka
0.74302914 Kosipe
0.74431069 Mwani
0.74724866 Laka
0.75027704 Kaba
0.75198880 Cameroon_Bakoko
0.75222188 Bantu_S.W.
0.75237609 Makhuwa
0.75289913 Sena
0.75324728 Mende_Sierra_Leone
0.75398114 Ndau
0.75514393 Nyanja
0.75535578 Nyaneka
0.75554785 Cameroon_Bangwa
0.75561243 Umbundu
0.75593581 Yao
0.75668196 Lemande
0.75786467 Changana
0.75802250 Tikar_South
0.75816375 Kongo
0.75845956 Cameroon_Bafut
0.75847248 Ngumba
0.75858043 Cameroon_Aghem
0.75863189 Ganguela
0.75999052 Ronga
0.76005694 Cameroon_Mbo
0.76007099 Tswa
0.76027697 Chopi
0.76064415 Manyika
0.76136121 Bantu_S.E.
0.76235736 Bitonga
0.76265156 Igbo
0.76341361 Koinanbe
0.76341544 Yoruba
0.76350379 Papuan
0.76548946 Esan_Nigeria
0.79304734 Bedzan
0.79986920 Bakola
0.80198051 Baka
0.81603188 Biaka
0.85718579 Khomani_San
0.92754448 Ju_hoan_North
0.94221812 Mbuti
This is how the most East Eurasian-shifted Saami individual score in terms of distance to other pops:
Distance to: Saami:GS000035025
0.03431087 Saami
0.06484717 Udmurt
0.07581220 Saami_Kola
0.07635056 Besermyan
0.08057752 Chuvash
0.08945463 Mari
0.09662816 Komi
0.10311240 Tatar_Kazan
0.10832232 Bashkir
0.11753134 Tatar_Lipka
0.12239585 Tatar_Mishar
0.12804717 Yukagir_Forest
0.13135758 Russian_Pinega
0.13407839 Tatar_Siberian
0.13984898 Tatar_Crimean_steppe
0.14117080 Tatar_Siberian_Zabolotniye
0.14146563 Vepsian
0.14321710 Finnish_East
0.14516907 Tlingit
0.14518012 Karelian
0.15746846 Mordovian
0.15780722 Mansi
0.15928761 Russian_Kostroma
0.16086747 Ingrian
0.16114704 Finnish
0.17090740 Khanty
0.17232113 Turkmen
0.17241098 Turkmen_Uzbekistan
0.17544998 Uzbek
0.17696642 Cossack_Kuban
0.17726949 Nogai
0.18446833 Russian_Tver
0.18566008 Ket
0.18893651 Estonian
0.19022350 Tajik
0.19213942 Russian_Kursk
0.19462396 Tajik_Shugnan
0.19537029 Russian_Orel
0.19547822 Cossack_Ukrainian
0.19564399 Tajik_Rushan
0.19761805 Russian_Voronez
0.19982472 Karakalpak
0.19993139 Hazara_Afghanistan
0.20105455 Moldovan_o
0.20114102 Latvian
0.20128495 Belarusian
0.20143800 Russian_Smolensk
0.20168237 Ukrainian_B
0.20255111 Lithuanian_PA
0.20256351 Uygur
0.20258413 Ukrainian
0.20259872 Greenlander_West
0.20317962 Lithuanian_RA
0.20362370 Lithuanian_VA
0.20368092 Tajik_Ishkashim
0.20396729 Lithuanian_PZ
0.20422794 Lithuanian_SZ
0.20442601 Lithuanian_VZ
0.20500438 Tubalar
0.20707970 Swedish
0.20715251 Polish
0.20743505 Hazara
0.21042592 Maori
0.21057266 Norwegian
0.21058875 Slovakian
0.21261985 Czech
0.21279267 Turkish_Deliorman
0.21328762 Hungarian
0.21352400 Turkish_Rumeli
0.21434038 Icelandic
0.21449101 Tajik_Yagnobi
0.21453304 Turkish_Northwest
0.21505182 Turkish_Balikesir
0.21520710 Dutch
0.21571126 Afrikaner
0.21605982 Shor_Mountain
0.21659668 Danish
0.21752150 German_East
0.21755381 Orcadian
0.21812887 Sorb_Niederlausitz
0.21817474 Shetlandic
0.21823963 Shor_Khakassia
0.21845366 Scottish
0.21924110 Kho_Singanali
0.21933399 Slovenian
0.21940491 Croatian
0.21949449 Irish
0.21986900 Moldovan
0.21991154 Shor
0.22009585 Austrian
0.22140021 German
0.22170772 English
0.22172655 Jatt_Pathak
0.22206335 Turkish_Aydin
0.22210997 Turkish_Southwest
0.22349388 Welsh
0.22404192 Ror
0.22419244 Turkish_South
0.22482493 Bosnian
0.22530516 English_Cornwall
0.22538722 French_Brittany
0.22582893 Roma_Barcelona
0.22707081 Kazakh
0.22842638 Belgian
0.22880841 Roma_Bilbao
0.22917918 Burusho
0.22950433 French_Seine-Maritime
0.23062153 French_Nord
0.23091493 French_Alsace
0.23101902 Turkish_North
0.23114720 French_Pas-de-Calais
0.23122852 Serbian
0.23179622 Roma_Madrid
0.23179780 Montenegrin
0.23253708 Abazin
0.23282629 Romanian
0.23284014 Roma_Granada
0.23305851 Roma_Balkans
0.23334133 Cherkes
0.23341093 Kabardin
0.23341816 Roma_Porto
0.23395878 Swiss_German
0.23540157 Kumyk
0.23548020 Uthmankhel
0.23556310 Pashtun
0.23571814 French_Paris
0.23650209 Balkar
0.23684725 Circassian
0.23711483 Bulgarian
0.23730613 Darginian
0.23754983 Khakass
0.23756655 Karachay
0.23861166 Kalash
0.23862132 Tarkalani
0.23910079 Kaitag
0.23934904 Avar
0.23940061 Turkish_Istanbul
0.23974308 Yusufzai
0.24006558 Lak
0.24018098 Gagauz
0.24129075 French_Occitanie
0.24150431 Tabasaran
0.24247196 French_Auvergne
0.24386950 Macedonian:East1
0.24391187 Kubachinian
0.24403727 Macedonian:Northwest
0.24453256 Swiss_French
0.24461059 Macedonian:East2
0.24506176 French_Provence
0.24518975 Italian_Northeast
0.24570897 Punjabi_Jatt
0.24658913 Kamboj
0.24665978 Turkish_Central
0.24735159 Macedonian:Pelagonia1
0.24787235 Kashmiri_Pandit
0.24804243 Italian_Aosta_Valley
0.24805317 Spanish_Camp_de_Tarragona
0.24823252 Kohistani
0.24853820 Bahun
0.24927338 Spanish_Penedes
0.24963286 Ingushian
0.24968701 Spanish_Girona
0.24978165 Punjabi_Sikh_India
0.24988267 North_Ossetian
0.25022800 Spanish_Cataluna
0.25026030 Chechen
0.25036638 Spanish_Castilla_Y_Leon
0.25091418 Spanish_Barcelones
0.25091483 Turkish_B
0.25097691 Spanish_Lleida
0.25107314 Spanish_Soria
0.25142908 Spanish_Galicia
0.25173744 Spanish_Mallorca
0.25176833 Italian_Trentino-Alto-Adige
0.25183722 French_South
0.25188484 Spanish_Asturias
0.25194673 Spanish_Valencia
0.25235937 Selkup
0.25237274 Spanish_Pirineu
0.25237518 Turkish_Adana
0.25243624 Swiss_Italian
0.25267164 Spanish_Baleares
0.25268842 Khatri
0.25272563 Azeri_Dagestan
0.25275650 Spanish_Murcia
0.25297139 Spanish_Eivissa
0.25312611 Portuguese
0.25312837 Spanish_Cantabria
0.25313544 Spanish_Castello
0.25321865 Macedonian:Southeast
0.25334894 Spanish_Terres_de_l'Ebre
0.25338438 Spanish_Catalunya_Central
0.25354420 Spanish_Alacant
0.25378774 Spanish_Peri-Barcelona
0.25390673 Rumelia_East
0.25442540 Adygei
0.25466761 Spanish_Andalucia
0.25478623 Italian_Veneto
0.25500815 Spanish_Castilla_La_Mancha
0.25525533 Spanish_Aragon
0.25549546 Spanish_Menorca
0.25550110 Greek_Central_Macedonia
0.25582392 Greek_Macedonia
0.25588541 Spanish_Navarra
0.25620124 Italian_Liguria
0.25644935 Spanish_Extremadura
0.25650710 Albanian
0.25662898 Spanish_Pais_Vasco
0.25718765 Macedonian:Central
0.25776384 Basque_French
0.25850013 Iranian_B
0.25878134 Spanish_Canarias
0.25918302 Turkish_Kayseri
0.25936264 Italian_Piedmont
0.25970004 Italian_Bergamo
0.25971381 Basque_Spanish
0.25976153 Italian_Lombardy
0.26024931 Greek_Thessaly
0.26116496 Azeri
0.26178478 Ossetian
0.26239806 Gujar_Pakistan
0.26249581 Kirghiz
0.26299440 Azeri_Turkey
0.26347350 Parsi_Pakistan
0.26377789 Ashkenazi_Russia
0.26393602 Sindhi
0.26431543 Nenets
0.26450472 Kirghiz_China
0.26479982 Greek_Peloponnese
0.26541031 Parsi_India
0.26542802 Spanish_La_Rioja
0.26548806 Italian_Tuscany
0.26644246 Ashkenazi_Ukraine
0.26674727 Ashkenazi_Belarussia
0.26696222 Brahmin_Gujarat
0.26700404 Ashkenazi_Lithuania
0.26764571 Iranian_Fars
0.26803894 Iranian_Seyyed
0.26837331 Greenlander_East
0.26877510 Italian_Marche
0.26956340 Italian_Umbria
0.26981310 Gujar_India
0.26982008 Ashkenazi_Poland
0.27001096 Balochi
0.27014173 Brahui
0.27078641 French_Corsica
0.27100713 Iranian_Bandari
0.27130116 Italian_Molise
0.27177694 Greek_Izmir
0.27183982 Brahmin_West_Bengal
0.27191826 Sicilian_West
0.27262376 Turkish_East
0.27348076 Iranian_Zoroastrian
0.27358812 Zaza_Dersim
0.27443454 Italian_Abruzzo
0.27453358 Greek_Laconia
0.27518403 Italian_Lazio
0.27646711 Ezid
0.27709315 Talysh_Azerbaijan
0.27713676 Khakass_Kachins
0.27723415 Maltese
0.27725942 Makrani
0.27739601 Italian_Basilicata
0.27830038 Italian_Apulia
0.27831308 Sicilian_East
0.27885630 Kshatriya
0.27982481 Brahmin_Uttar_Pradesh
0.28098217 Greek_Crete
0.28104854 Iranian_Lor
0.28171984 Ashkenazi_Germany
0.28177740 Italian_Campania
0.28283667 Kurdish
0.28300543 Italian_Calabria
0.28358553 Kazakh_China
0.28416759 Iranian_Mazandarani
0.28448802 Abkhasian
0.28454683 Altaian
0.28776759 Althai_Kizhi
0.28956353 Sephardic_Jew
0.28975017 Italian_Jew
0.28978132 Brahmin_Tamil_Nadu
0.29069245 Greek_Kos
0.29083353 Iyer
0.29174486 Moroccan_Jew
0.29202871 Greek_Dodecanese
0.29229055 Syrian
0.29545896 Romaniote_Jew
0.29603097 Iraqi
0.29643926 Iraqi_B
0.29675537 Syrian_B
0.29690238 Cree
0.29791673 Syrian_Jew
0.29847309 Lebanese_Muslim
0.29856668 Lebanese_Muslim_Shia
0.29862907 Greek_Central_Anatolia
0.29866727 Greek_Cappadocia
0.29895642 Lebanese_Muslim_Sunni
0.29924464 Georgian_Jew
0.29952436 Mountain_Jew
0.29989513 Punjabi_Lahore
0.30188750 Kanjar
0.30244818 Libyan_Jew
0.30298699 Cypriot_B
0.30392856 Assyrian
0.30447119 Georgian_Laz
0.30479861 Cypriot
0.30491843 Iranian_Jew
0.30500936 Armenian
0.30517202 Tunisian_Jew
0.30537244 Jordanian
0.30547457 Kol
0.30554206 Turkish_Trabzon
0.30637849 Lebanese_Druze
0.30656645 Greek_Trabzon
0.30665645 Druze
0.30675187 Armenian_B
0.30689134 Gujarati
0.30697802 Newar
0.30705503 Georgian_Imer
0.30733151 Karaite_Egypt
0.30745884 Jordanian_B
0.30803768 Armenian_Hemsheni
0.30858374 Dharkar
0.30863788 Bengali_Bangladesh
0.30879579 Kamboj_o
0.30960990 Palestinian
0.31400229 Lebanese_Christian
0.31451104 Uttar_Pradesh
0.31489073 Lebanese_Christian_Maronite
0.31629903 Lebanese_Christian_Greek_Orthodox
0.31645597 BedouinA
0.31661685 Sardinian
0.31778151 Iraqi_Jew
0.31818816 Brahmin_Manipuri
0.32154291 Palestinian_Beit_Sahour
0.32173791 Mogush
0.32379213 Velamas
0.32774278 Dusadh
0.32776279 Mongolian
0.32825857 Yadava
0.32873781 Samaritan
0.32960689 Chenchu
0.33017529 Moroccan_North
0.33047800 Buryat
0.33116806 Gupta
0.33120393 Maratha
0.33136826 Egyptian
0.33216318 Kalmyk
0.33261867 Tuvinian
0.33308519 Chamar
0.33407402 Relli
0.33415846 Kurumba
0.33524228 Tunisian
0.33565677 Piramalai
0.33576955 Libyan
0.33677636 Yemenite_Amran
0.33686470 Berber_Tunisia_Sen
0.33721836 Tunisian_Berber_Zraoua
0.33788626 Tunisian_Berber_Tamezret
0.33960763 Tunisian_Berber_Matmata
0.34024103 Algerian
0.34116714 Berber_Tunisia_Chen
0.34134129 Tharu
0.34430671 North_Kannadi
0.34683817 Yemenite_Dhamar
0.34767011 Mozabite
0.34780711 Yemenite_Al_Bayda
0.34839313 Tunisian_Rbaya
0.34950755 Sakilli
0.34974947 Pallan
0.35014949 Hakkipikki
0.35190971 Yemenite_Jew
0.35275083 Yemenite_Ma'rib
0.35297341 Tunisian_Douz
0.35316720 Madiga
0.35323142 Yemenite_Al_Jawf
0.35350958 Dolgan
0.35356470 Moroccan
0.35504019 Saudi
0.35591588 BedouinB
0.35601792 Kusunda
0.35811586 Todzin
0.36015547 Yemenite_Mahra
0.36139542 Berber_MAR_ERR
0.36147497 Mala
0.36279300 Jarawa
0.36323563 Onge
0.36588368 Irula
0.37040905 Pulliyar
0.37149194 Gond
0.37162865 Khamnegan
0.37283268 Saharawi
0.37303732 Kadar
0.37507769 Salar
0.37633336 Berber_MAR_TIZ
0.37786971 Asur
0.37818142 Malayan
0.37868171 Paniya
0.37871862 Itelmen
0.38134328 Dongxiang
0.38433154 Magar
0.38505801 Gadaba
0.38582184 Santhal
0.38632293 Tamang
0.38766794 Korwa
0.38793728 Chukchi
0.38844622 Bhumij
0.38889842 Koryak
0.38945958 Birhor
0.39017250 Ho
0.39193849 Eskimo_Sireniki
0.39366630 Khonda_Dora
0.39468598 Eskimo_Naukan
0.39519701 Dungan
0.39521721 Yakut
0.39623170 Juang
0.39649200 Eskimo_Chaplin
0.39662885 Bonda
0.39781277 Jehai
0.39792963 Eskimo
0.39880474 Jamatia
0.40183776 Tripuri
0.40399978 Moroccan_South
0.40712913 Yukagir_Tundra
0.40839507 Sakha
0.40908696 Aeta
0.41105808 Burmese
0.41259148 Agta
0.41320939 Tibetan_Gannan
0.41405630 Bonan
0.41407251 Gurung
0.41563645 Tibetan_Gangcha
0.41672185 Chipewyan
0.42062862 Tibetan_Xunhua
0.42104090 Tu
0.42257047 Thai
0.42483749 Daur
0.42703602 Tibetan_Shannan
0.42855306 Nganassan
0.43003622 Oroqen
0.43065645 Rai
0.43076858 Mongola
0.43129313 Tibetan_Shigatse
0.43142429 Batak
0.43170325 Sherpa
0.43233088 Tibetan_Lhasa
0.43401444 Yugur
0.43407798 Evenk
0.43541777 Eritrean
0.43628219 Hezhen
0.43642503 Ulchi
0.43693410 Xibo
0.43799762 Nivkh
0.43829521 Tibetan_Nagqu
0.44028229 Amerindian_North
0.44206747 Ethiopian_Tigray
0.44225748 Nanai
0.44279003 Batak_Toba_Sumatra
0.44290750 Ethiopian_Afar
0.44442495 Tibetan_Yajiang
0.44478038 Even
0.44481631 Tibetan_Chamdo
0.44541267 Qiang_Daofu
0.44636720 Malay
0.44721715 Negidal
0.44958599 Ethiopian_Amhara
0.44963747 Ethiopian_Agaw
0.45041463 Tibetan_Yunnan
0.45086604 Cambodian
0.45461447 Ethiopian_Jew
0.45749729 Naxi
0.45812133 Tibetan_Xinlong
0.45841085 Manggarai_Rampasasa
0.45870263 Bajo
0.45875511 Han_Shanxi
0.46053327 Vizayan
0.46107093 Yi
0.46340947 Qiang_Danba
0.46404122 Japanese
0.46440841 Kambera_Wunga
0.46532701 Han_Henan
0.46566089 Ngadha_Bena
0.46597296 Kambera_Rindi
0.46634628 Anakalang
0.46743496 Indonesian_Bali
0.46882259 Han_Shandong
0.47018428 Berber_Algeria
0.47043603 Lamaholot_Bama_Flores
0.47067294 Korean
0.47173019 Lahu
0.47227398 Mandar_Sulawesi
0.47373475 Han_Shanghai
0.47531667 Han_Sichuan
0.47584339 Kinh_Vietnam
0.47643764 Indonesian_Java
0.47739534 Hawaiian
0.47766071 Miao
0.47811938 Lamaholot_Lembata_Hadakewa
0.47861938 Tujia
0.47919066 Htin_Mal
0.47950093 Han_Jiangsu
0.47969838 Han_Hubei
0.47973649 Ethiopian_Oromo
0.48021852 Mlabri
0.48091489 Han_Zhejiang
0.48167324 Han_Chongqing
0.48259289 Tetum_Umanen_Lawalu
0.48336294 Han_Fujian
0.48555260 Tetum_Umaklaran
0.48579022 Dai
0.48636008 Dong_Guizhou
0.48709623 Gelao
0.48744409 She
0.48745761 Han_Guangdong
0.48855942 Dong_Hunan
0.48884060 Lebbo
0.48978534 Tetum_Kamanasa
0.48988658 Mulam
0.49070212 Luzon
0.49108238 Zhuang
0.49398174 Nias
0.49436274 Li
0.49473997 Mentawai
0.49500749 Maonan
0.49686428 Bolivian_Pando
0.49792510 Somali
0.49836296 Dusun
0.49922100 Atayal
0.50322507 Ethiopian_Wolayta
0.50547125 Murut
0.50557504 Bolivian_Cochabamba
0.50618289 Quechua
0.50736098 Ami
0.50791440 Pantar
0.50924065 Igorot
0.51205870 Somali_Kenya
0.51242189 Mixtec
0.51430105 Zapotec
0.51879061 Nahua
0.52031003 Mayan
0.52163503 Alor
0.52392308 Huichol
0.52525797 Rendille
0.52598796 Pima
0.53404322 Cachi
0.53652808 Iraqw
0.53802527 Mixe
0.54211874 Nasoi
0.54473883 Colla
0.54943809 Bolivian_LaPaz
0.55013325 Fulani
0.56294894 Datog
0.56461275 Aymara
0.57124148 Yukpa
0.57491994 Piapoco
0.57752424 Elmolo
0.57857630 Wichi
0.57950016 Ethiopian_Ari_cultivator
0.58418048 Australian
0.58418358 Ethiopian_Ari
0.58830571 Ethiopian_Ari_blacksmith
0.59375931 Ogiek
0.59569678 Karitiana
0.60257281 Masai
0.60270775 Surui
0.61606083 Sandawe
0.63675070 Sengwer
0.64059454 Kikuyu
0.64682126 Hadza
0.66422840 Bulala
0.67463718 Ethiopian_Gumuz
0.67663030 Ethiopian_Mursi
0.71502197 Ethiopian_Anuak
0.71783142 Sudanese
0.71971629 Dinka
0.72450795 Mada
0.72765215 Luhya_Kenya
0.73005059 Luo
0.73029830 Bantu_Kenya
0.73677435 Gambian
0.73781162 Mandenka
0.74161290 Mwani
0.74306569 Kosipe
0.74457978 Laka
0.74774703 Kaba
0.74928687 Cameroon_Bakoko
0.74957583 Bantu_S.W.
0.74960912 Makhuwa
0.75016066 Sena
0.75051697 Mende_Sierra_Leone
0.75108761 Ndau
0.75233073 Nyanja
0.75256773 Cameroon_Bangwa
0.75259214 Nyaneka
0.75281443 Umbundu
0.75307469 Yao
0.75376353 Lemande
0.75498547 Changana
0.75524870 Kongo
0.75530330 Tikar_South
0.75554074 Cameroon_Bafut
0.75569878 Ngumba
0.75570497 Ganguela
0.75576084 Cameroon_Aghem
0.75700884 Ronga
0.75714126 Tswa
0.75723420 Cameroon_Mbo
0.75731417 Chopi
0.75776263 Manyika
0.75853988 Bantu_S.E.
0.75941967 Bitonga
0.75990382 Igbo
0.76049438 Yoruba
0.76249392 Esan_Nigeria
0.76348339 Koinanbe
0.76364274 Papuan
0.79043272 Bedzan
0.79709474 Bakola
0.79946372 Baka
0.81332181 Biaka
0.85499058 Khomani_San
0.92570204 Ju_hoan_North
0.93975230 Mbuti
This is how they score on scaled Global25
]
I checked your G25 Chukchi list. I see a couple of issues with it:
1- It starts out good. The 1st few on the list down to Kirgiz or so look fine . They sort of mirror the 430K IBS list I posted but then things start to go horribly wrong with it. I'll just give one example. Look at Kurds-Iraq on the IBS list. You'll notice that Kurds-Iraq are like number 33 on the Chukchi and they're certainly higher than most Europeans and S Asians which makes sense. Yet on the G25 list they're way down.
The reason for this issue with the G25 is these distances are based on G25 coordinates and of course the coordinates are totally dependent on all the other samples in the run. This of course is problematic because each sample out of the 1000s he uses either pulls or pushes on another sample in some way or form. For example, some W Asian or Europeans samples pull Kurds close to them which in effect distances them from Chukchi.
Whereas with IBS you don't have all this pulling and pushing. Each sample is compared directly with Chukchi allele for allele and checked to see how many alleles it shares with Chukchi. So there's really nothing that can go wrong. You just add up the number of alleles Kurds or some other pop shares with Chukchi. It's that simple. The reason Kurds are so high on the Chukchi list is that there are many positions in their genome where they don't just share 1 allele with Chukchi but rather they share both alleles with Chukchi.
2- The other weird thing I noticed with G25 is once you pass the 1st 10 or so pops on the list the distances start getting huge. This of course also distorts things. If you check the IBS list the distances don't get out of control when you start heading to the bottom of the list.
Edit: I noticed you have a pop called 'Salar" on the list. What the heck is it? Salar is a common Kurd name. It means brave :)
Zanzibar
02-25-2021, 12:52 AM
I checked your G25 Chukchi list. I see a couple of issues with it:
1- It starts out good. The 1st few on the list down to Kirgiz or so look fine . They sort of mirror the 430K IBS list I posted but then things start to go horribly wrong with it. I'll just give one example. Look at Kurds-Iraq on the IBS list. You'll notice that Kurds-Iraq are like number 33 on the Chukchi and they're certainly higher than most Europeans and S Asians which makes sense. Yet on the G25 list they're way down.
The reason for this issue with the G25 is these distances are based on G25 coordinates and of course the coordinates are totally dependent on all the other samples in the run. This of course is problematic because each sample out of the 1000s he uses either pulls or pushes on another sample in some way or form. For example, some W Asian or Europeans samples pull Kurds close to them which in effect distances them from Chukchi.
Whereas with IBS you don't have all this pulling and pushing. Each sample is compared directly with Chukchi allele for allele and checked to see how many alleles it shares with Chukchi. So there's really nothing that can go wrong. You just add up the number of alleles Kurds or some other pop shares with Chukchi. It's that simple. The reason Kurds are so high on the Chukchi list is that there are many positions in their genome where they don't just share 1 allele with Chukchi but rather they share both alleles with Chukchi.
2- The other weird thing I noticed with G25 is once you pass the 1st 10 or so pops on the list the distances start getting huge. This of course also distorts things. If you check the IBS list the distances don't get out of control when you start heading to the bottom of the list.
Edit: I noticed you have a pop called 'Salar" on the list. What the heck is it? Salar is a common Kurd name. It means brave :)
How much East Eurasian ancestry do Kurds have on average? Its higher than their neighbors right?
I believe that Salar in this case is an ethnic group from NW China: https://en.wikipedia.org/wiki/Salar_people
How much East Eurasian ancestry do Kurds have on average? Its higher than their neighbors right?
I believe that Salar in this case is an ethnic group from NW China: https://en.wikipedia.org/wiki/Salar_people
Interesting. I had no idea Salar is an ethnic group in NW China. Even a couple of my Kurdish cousins are named Salar lol.
As for Kurds in Iraq it's certainly higher than their other neighbors in Iraq but E Asian or Siberian ancestry in Kurds is far from uniform just like Kurdish phenotypes are all over the place. I'm limited by the 1240K public samples which only include 2 Kayseri Turk samples and 2 Iranian-Fars samples and some Caucasian samples.
So far I have mostly done one-to-one comparisons using the Kurds with E Asian because that's more interesting to me since I'm more interested in Absolute comparisons over relative comparisons but I would think around 10% post Neolithic accumulated E Asian is probably close. I'll start doing some of those calculations soon.
EDIT: Forgot to mention there's one Central Asian pop that Kurds are very high on the IBS list with. It's Uyghurs. They are number 10 on the Uyghur IBS list. Pashtuns are also high on that list
Zanzibar
02-25-2021, 02:11 AM
Interesting. I had no idea Salar is an ethnic group in NW China. Even a couple of my Kurdish cousins are named Salar lol.
As for Kurds in Iraq it's certainly higher than their other neighbors in Iraq but E Asian or Siberian ancestry in Kurds is far from uniform just like Kurdish phenotypes are all over the place. I'm limited by the 1240K public samples which only include 2 Kayseri Turk samples and 2 Iranian-Fars samples and some Caucasian samples.
So far I have mostly done one-to-one comparisons using the Kurds with E Asian because that's more interesting to me since I'm more interested in Absolute comparisons over relative comparisons but I would think around 10% post Neolithic accumulated E Asian is probably close. I'll start doing some of those calculations soon.
EDIT: Forgot to mention there's one Central Asian pop that Kurds are very high on the IBS list with. It's Uyghurs. They are number 10 on the Uyghur IBS list. Pashtuns are also high on that list
They are a Turkic ethnic group btw.
What's the average East Eurasian amount that you have observed for Kurds? And do you think its from Steppe or from Turkic invaders into West Asia?
Is it lower than Iraqi Turkmens?
Damn that's remarkable. Maybe some type of connection with Uyghurs through shared potential Turkic affinity?
Komintasavalta
02-25-2021, 08:01 AM
Here's the IBS for Finland Saami and Chukchi
Plink calculates IBS as (IBS2 + 0.5*IBS1) / (IBS0 + IBS1 + IBS2) meaning the more positions where the target and the population compared match both alleles at a position (IBS2) the higher the IBS score. What this means is since you get 1 allele from each parent that if BOTH your dad's allele and mom's allele match Saami or Chukchi at every position you get a higher IBS score
The first set of results for CHUKCHI is without removing really ancient common alleles (very ancient ancestry) from the calculation
....
Wouldn't it make sense to calculate the average IBS values of Saami relative to multiple Mongoloid populations, and not just Chukchi? Now on the second list for Chukchi, Saami rank higher than some Southeast Asians, which doesn't make sense as an overall measure of Mongoloidness.
Or could you check how populations of the Volga-Ural compare to Saami, like for example Komis or Kazan Tatars or Maris?
Couldn't we compile a 99x99 (or whatever) table of each population compared against every other population? Then couldn't we use it as a precalculated matrix of genetic distances? Or for example we could take the average values of the columns for multiple Mongoloid populations and sort the rows of the table based on it.
Sorry for being like Joqool and asking too many questions.
I combined the data you posted (without the common old alleles) into a table. I omitted the row for Chukchis because you didn't post the score of Chukchis with themselves.
Population,Chukchi,Saami
Adygei,0.8405,0.8390
Albanian.DG,0.8380,0.8337
Ami.DG,0.8422,0.8381
Armenian,0.8377,0.8349
Balochi,0.8361,0.7755
BantuHerero,0.7795,0.7803
BantuKenya,0.7834,0.7757
BantuTswana,0.7776,0.8405
Basque,0.8383,0.8329
BedouinB,0.8319,0.8256
Bougainville,0.8303,0.8351
Brahui,0.8370,0.8401
Bulgarian,0.8393,0.8354
Burmese,0.8435,0.8378
Burusho,0.8397,0.8392
Chechen,0.8395,0.8339
China_Lahu,0.8425,0.8439
Czech,0.8394,0.8419
Dai,0.8428,0.8341
Daur,0.8466,0.8380
Druze,0.8335,0.8359
Dusun,0.8416,0.8327
English,0.8404,0.8417
Esan,0.7791,0.7762
Eskimo_Naukan.DG,0.8537,0.8383
Eskimo_Sireniki.DG,0.8540,0.8387
Estonian,0.8410,0.8429
Even,0.8482,0.8400
Finnish,0.8422,0.8442
French,0.8388,0.8397
Gambian,0.7817,0.7786
Georgian,0.8364,0.8378
Greek,0.8383,0.8386
Han,0.8460,0.8358
Hazara,0.8433,0.8391
Hezhen,0.8479,0.8381
Hungarian,0.8400,0.8409
Icelandic,0.8403,0.8420
Iranian-Fars,0.8386,0.8372
Irula,0.8367,0.8340
Itelmen,0.8527,0.8377
Japanese,0.8461,0.8359
Jew_Iraqi,0.8354,0.8358
Jordanian,0.8317,0.8321
Ju_hoan_North,0.7687,0.7657
Kalash,0.8378,0.8369
Kapu,0.8376,0.8349
Karitiana,0.8441,0.8348
Khomani_San,0.7690,0.7661
Kinh,0.8436,0.8346
Korean,0.8455,0.8370
Kurds-IRAQ,0.8424,0.8417
Kusunda,0.8388,0.8317
Kyrgyz_Kyrgyzstan,0.8466,0.8405
Lezgin,0.8386,0.8396
Luhya,0.7825,0.7793
Luo,0.7836,0.7799
Makrani,0.8353,0.8341
Mala,0.8380,0.8341
Mandenka,0.7817,0.7780
Mansi,0.8477,0.8436
Masai,0.7974,0.7952
Mayan,0.8464,0.8366
Mbuti,0.7729,0.7702
Mende,0.7801,0.7769
Mixe,0.8458,0.8358
Mixtec,0.8458,0.8373
Mongola,0.8465,0.8373
Mozabite,0.8215,0.8219
Norwegian,0.8405,0.8421
Orcadian,0.8397,0.8414
Papuan,0.8270,0.8222
Pathan,0.8399,0.8375
Piapoco,0.8454,0.8350
Pima,0.8462,0.8361
Polish,0.8408,0.8417
Punjabi,0.8377,0.8362
Russia_Abkhasian,0.8387,0.8391
Russia_NorthOssetian,0.8387,0.8390
Russian,0.8425,0.8436
Saami,0.8439,0.8527
Saharawi,0.8235,0.8226
Samaritan,0.8321,0.8324
Sardinian,0.8373,0.8388
She,0.8448,0.8353
Sindhi,0.8383,0.8367
Somali,0.8065,0.8049
Spanish,0.8384,0.8398
Surui,0.8438,0.8337
Tajik,0.8396,0.8380
Tuscan,0.8389,0.8390
Ulchi,0.8473,0.8372
Uyghur,0.8440,0.8391
Xibo,0.8460,0.8367
Yadava,0.8388,0.8353
Yakut,0.8474,0.8386
Yi,0.8445,0.8349
Here's the data as a plot. I used hierarchical K-means clustering to divide the populations into 16 groups.
https://i.ibb.co/FK8g6SB/a.png
library(ggplot2);library(factoextra);library(color space)
download.file("https://pastebin.com/raw/FnTJmkAj","chukchisaami")
t<-read.csv("chukchisaami",header=T,row.names=1)
k<-hkmeans(t,16)
ggplot(t,aes(x=Chukchi,y=Saami,label=row.names(t)) )+
geom_text(aes(color=as.factor(k$cluster)),size=2.5 ,show.legend=F)+
theme(
plot.background=element_rect(fill="gray35"),
panel.grid.major=element_line(color="gray35"),
text=element_text(color="gray10"),
axis.text=element_text(color="gray10"),
axis.ticks.x=element_blank(),
axis.ticks.y=element_blank(),
panel.grid.minor=element_blank()
)+
coord_fixed()+
xlab("430K SNPs - Max-Maf 0.3 - Chukchi")+
ylab("430K SNPs - Max-Maf 0.3 - Saami-Finland")+
scale_color_discrete_qualitative(palette="Set 3")
ggsave("/tmp/a.png")
I couldn't get the version of plink from here to compile with either gcc or clang, and when I tried running the Mac binary, it said `Bad CPU type in executable`: https://zzz.bwh.harvard.edu/plink/download.shtml. But now I realized that there's a version by another developer here, with a working Mac binary: http://www.cog-genomics.org/plink/2.0/. I'll figure it out eventually.
Ajeje Brazorf
02-25-2021, 12:39 PM
I checked your G25 Chukchi list. I see a couple of issues with it:
1- It starts out good. The 1st few on the list down to Kirgiz or so look fine . They sort of mirror the 430K IBS list I posted but then things start to go horribly wrong with it. I'll just give one example. Look at Kurds-Iraq on the IBS list. You'll notice that Kurds-Iraq are like number 33 on the Chukchi and they're certainly higher than most Europeans and S Asians which makes sense. Yet on the G25 list they're way down.
The reason for this issue with the G25 is these distances are based on G25 coordinates and of course the coordinates are totally dependent on all the other samples in the run. This of course is problematic because each sample out of the 1000s he uses either pulls or pushes on another sample in some way or form. For example, some W Asian or Europeans samples pull Kurds close to them which in effect distances them from Chukchi.
Whereas with IBS you don't have all this pulling and pushing. Each sample is compared directly with Chukchi allele for allele and checked to see how many alleles it shares with Chukchi. So there's really nothing that can go wrong. You just add up the number of alleles Kurds or some other pop shares with Chukchi. It's that simple. The reason Kurds are so high on the Chukchi list is that there are many positions in their genome where they don't just share 1 allele with Chukchi but rather they share both alleles with Chukchi.
2- The other weird thing I noticed with G25 is once you pass the 1st 10 or so pops on the list the distances start getting huge. This of course also distorts things. If you check the IBS list the distances don't get out of control when you start heading to the bottom of the list.
So for example, would Chukchi really be more genetically akin to Iraqi Kurds than Tajiks? Wow. This contradicts what has been seen in the "vulgar" GEDmatch calculators and on Global25 in general. After years, most of what I consider normal is now based on what those two tools easily accessible to anyone show. As for distances soaring, this happens especially in scaled coordinates but not in unscaled ones. I'll post the unscaled distances and tell me if you find more correlation with your distances. And most importantly, in your opinion, between scaled and unscaled coordinates which one is less worse?
Here's the IBS for Finland Saami and Chukchi
Plink calculates IBS as (IBS2 + 0.5*IBS1) / (IBS0 + IBS1 + IBS2) meaning the more positions where the target and the population compared match both alleles at a position (IBS2) the higher the IBS score. What this means is since you get 1 allele from each parent that if BOTH your dad's allele and mom's allele match Saami or Chukchi at every position you get a higher IBS score
The first set of results for CHUKCHI is without removing really ancient common alleles (very ancient ancestry) from the calculation
<style type="text/css">td {border: 1px solid #ccc;}br {mso-data-placement:same-cell;}</style>
<tbody>
615K SNPs - Max-Maf 0.5 - Chukchi
POPULATION
IBS
Eskimo_Sireniki.DG
0.7921
Eskimo_Naukan.DG
0.7914
Itelmen
0.7911
Mansi
0.7873
Kyrgyz_Kyrgyzstan
0.7864
Even
0.7860
Yakut
0.7856
Hezhen
0.7851
Uyghur
0.7848
Mongola
0.7847
Ulchi
0.7847
Xibo
0.7840
Mixtec
0.7835
Daur
0.7831
Japanese
0.7829
Han
0.7829
Saami
0.7825
Korean
0.7825
Hazara
0.7821
Yi
0.7818
Burmese
0.7818
Finnish
0.7817
Mayan
0.7816
Russian
0.7814
She
0.7814
Mixe
0.7808
Norwegian
0.7801
Pima
0.7801
Kinh
0.7801
Estonian
0.7801
Icelandic
0.7800
Polish
0.7799
Kurds-IRAQ
0.7799
Piapoco
0.7798
Burusho
0.7794
English
0.7794
Hungarian
0.7793
Pathan
0.7793
Dai
0.7790
China_Lahu
0.7786
Bulgarian
0.7784
Adygei
0.7784
Czech
0.7784
Orcadian
0.7783
Tajik
0.7779
Chechen
0.7778
French
0.7776
Tuscan
0.7776
Ami.DG
0.7775
Russia_NorthOssetian
0.7775
Iranian-Fars
0.7775
Dusun
0.7774
Spanish
0.7773
Russia_Abkhasian
0.7772
Greek
0.7771
Lezgin
0.7770
Yadava
0.7770
Sindhi
0.7767
Basque
0.7767
Turkish
0.7766
Kapu
0.7765
Mala
0.7764
Karitiana
0.7763
Albanian.DG
0.7761
Punjabi
0.7761
Armenian
0.7759
Sardinian
0.7754
Georgian
0.7753
Surui
0.7753
Brahui
0.7747
Irula
0.7747
Kalash
0.7744
Balochi
0.7737
Jew_Iraqi
0.7736
Kusunda
0.7733
Makrani
0.7730
Druze
0.7717
BedouinB
0.7702
Jordanian
0.7691
Samaritan
0.7670
Saharawi
0.7634
Bougainville
0.7626
Mozabite
0.7623
Papuan
0.7568
Somali
0.7475
Masai
0.7401
Luo
0.7274
BantuKenya
0.7270
Luhya
0.7261
Mandenka
0.7256
Gambian
0.7254
Mende
0.7242
BantuHerero
0.7236
Esan
0.7231
BantuTswana
0.7217
Mbuti
0.7147
Ju_hoan_North
0.7105
Khomani_San
0.7095
</tbody>
This set for CHUKCHI is after removing common old alleles (ancestry). All alleles having a minor allele frequency > 30% have been removed. I like this better because it tends to better reflect more recent ancestry
<colgroup><col width="140"><col width="144"></colgroup><tbody>
430K SNPs - Max-Maf 0.3 - Chukchi
POPULATION
IBS
Eskimo_Sireniki.DG
0.8540
Eskimo_Naukan.DG
0.8537
Itelmen
0.8527
Even
0.8482
Hezhen
0.8479
Mansi
0.8477
Yakut
0.8474
Ulchi
0.8473
Daur
0.8466
Kyrgyz_Kyrgyzstan
0.8466
Mongola
0.8465
Mayan
0.8464
Pima
0.8462
Japanese
0.8461
Xibo
0.8460
Han
0.8460
Mixtec
0.8458
Mixe
0.8458
Korean
0.8455
Piapoco
0.8454
She
0.8448
Yi
0.8445
Karitiana
0.8441
Uyghur
0.8440
Saami
0.8439
Surui
0.8438
Kinh
0.8436
Burmese
0.8435
Hazara
0.8433
Dai
0.8428
Russian
0.8425
China_Lahu
0.8425
Kurds-IRAQ
0.8424
Finnish
0.8422
Ami.DG
0.8422
Dusun
0.8416
Estonian
0.8410
Polish
0.8408
Adygei
0.8405
Norwegian
0.8405
English
0.8404
Icelandic
0.8403
Hungarian
0.8400
Pathan
0.8399
Orcadian
0.8397
Burusho
0.8397
Tajik
0.8396
Chechen
0.8395
Czech
0.8394
Bulgarian
0.8393
Tuscan
0.8389
French
0.8388
Yadava
0.8388
Kusunda
0.8388
Russia_NorthOssetian
0.8387
Russia_Abkhasian
0.8387
Lezgin
0.8386
Iranian-Fars
0.8386
Spanish
0.8384
Basque
0.8383
Sindhi
0.8383
Greek
0.8383
Albanian.DG
0.8380
Mala
0.8380
Kalash
0.8378
Armenian
0.8377
Punjabi
0.8377
Kapu
0.8376
Sardinian
0.8373
Brahui
0.8370
Irula
0.8367
Georgian
0.8364
Balochi
0.8361
Jew_Iraqi
0.8354
Makrani
0.8353
Druze
0.8335
Samaritan
0.8321
BedouinB
0.8319
Jordanian
0.8317
Bougainville
0.8303
Papuan
0.8270
Saharawi
0.8235
Mozabite
0.8215
Somali
0.8065
Masai
0.7974
Luo
0.7836
BantuKenya
0.7834
Luhya
0.7825
Gambian
0.7817
Mandenka
0.7817
Mende
0.7801
BantuHerero
0.7795
Esan
0.7791
BantuTswana
0.7776
Mbuti
0.7729
Khomani_San
0.7690
Ju_hoan_North
0.7687
</tbody>
<style type="text/css">td {border: 1px solid #ccc;}br {mso-data-placement:same-cell;}</style>
This set for SAAMI is after removing common old alleles (ancestry). All alleles having a minor allele frequency > 30% have been removed. I like this better because it tends to better reflect more recent ancestry
<style type="text/css">td {border: 1px solid #ccc;}br {mso-data-placement:same-cell;}</style>
<colgroup><col width="134"><col width="188"></colgroup><tbody>
430K SNPs - Max-Maf 0.3 - Saami -Finland
POPULATION
IBS
Saami
0.8527
Finnish
0.8442
Chukchi
0.8439
Mansi
0.8436
Russian
0.8436
Estonian
0.8429
Norwegian
0.8421
Icelandic
0.8420
Czech
0.8419
Polish
0.8417
English
0.8417
Kurds - IRAQ
0.8417
Orcadian
0.8414
Hungarian
0.8409
Adygei
0.8405
Basque
0.8405
Kyrgyz_Kyrgyzstan
0.8405
Bulgarian
0.8401
Even
0.8400
Spanish
0.8398
French
0.8397
Lezgin
0.8396
Chechen
0.8392
Uyghur
0.8391
Hazara
0.8391
Russia_Abkhasian
0.8391
Russia_NorthOssetian
0.8390
Tuscan
0.8390
Albanian.DG
0.8390
Sardinian
0.8388
Eskimo_Sireniki.DG
0.8387
Yakut
0.8386
Greek
0.8386
Eskimo_Naukan.DG
0.8383
Hezhen
0.8381
Armenian
0.8381
Daur
0.8380
Tajik
0.8380
Burusho
0.8378
Georgian
0.8378
Itelmen
0.8377
Pathan
0.8375
Mongola
0.8373
Mixtec
0.8373
Ulchi
0.8372
Iranians - Fars
0.8372
Korean
0.8370
Kalash
0.8369
Sindhi
0.8367
Xibo
0.8367
Mayan
0.8366
Punjabi
0.8362
Pima
0.8361
Japanese
0.8359
Druze
0.8359
Mixe
0.8358
Han
0.8358
Jew_Iraqi
0.8358
Burmese
0.8354
She
0.8353
Yadava
0.8353
Brahui
0.8351
Piapoco
0.8350
Kapu
0.8349
Yi
0.8349
Balochi
0.8349
Karitiana
0.8348
Kinh
0.8346
Mala
0.8341
Makrani
0.8341
Dai
0.8341
Irula
0.8340
China_Lahu
0.8339
Ami.DG
0.8337
Surui
0.8337
BedouinB
0.8329
Dusun
0.8327
Samaritan
0.8324
Jordanian
0.8321
Kusunda
0.8317
Bougainville
0.8256
Saharawi
0.8226
Papuan
0.8222
Mozabite
0.8219
Somali
0.8049
Masai
0.7952
BantuKenya
0.7803
Luo
0.7799
Luhya
0.7793
Gambian
0.7786
Mandenka
0.7780
Mende
0.7769
Esan
0.7762
BantuTswana
0.7757
BantuHerero
0.7755
Mbuti
0.7702
Khomani_San
0.7661
Ju_hoan_North
0.7657
</tbody>
Distance to: Chukchi
0.02354426 Eskimo_Sireniki
0.02385687 Itelmen
0.02435038 Koryak
0.02594064 Eskimo_Chaplin
0.03086655 Eskimo
0.03359152 Eskimo_Naukan
0.04069513 Greenlander_East
0.04966897 Greenlander_West
0.05955621 Yukagir_Tundra
0.07471429 Tlingit
0.07718228 Even
0.08009604 Negidal
0.08496246 Yukagir_Forest
0.08672651 Ulchi
0.09114151 Nivkh
0.09226023 Nanai
0.09405305 Nganassan
0.09763242 Evenk
0.09785663 Oroqen
0.09960749 Khamnegan
0.10336127 Todzin
0.10403733 Nenets
0.10430008 Cree
0.10430962 Mogush
0.10438220 Tatar_Siberian
0.10542034 Tuvinian
0.10698304 Hezhen
0.10747890 Bashkir
0.10770182 Tatar_Siberian_Zabolotniye
0.10778348 Saami
0.10801949 Chipewyan
0.10903791 Kirghiz
0.10964025 Kazakh
0.10983849 Khakass_Kachins
0.10992862 Altaian
0.11039207 Karakalpak
0.11087479 Udmurt
0.11155696 Kirghiz_China
0.11171845 Selkup
0.11176697 Kalmyk
0.11205860 Khakass
0.11211538 Saami_Kola
0.11211844 Buryat
0.11237019 Besermyan
0.11239256 Tatar_Crimean_steppe
0.11251735 Kazakh_China
0.11257707 Nogai
0.11289023 Hazara
0.11290850 Komi
0.11331383 Turkmen_Uzbekistan
0.11346318 Daur
0.11355366 Hazara_Afghanistan
0.11362959 Mongolian
0.11387833 Uzbek
0.11390229 Tatar_Kazan
0.11416330 Turkmen
0.11428662 Tatar_Lipka
0.11511547 Amerindian_North
0.11527545 Uygur
0.11531743 Tubalar
0.11623223 Khanty
0.11675042 Mansi
0.11676234 Turkish_South
0.11703852 Turkish_Aydin
0.11706098 Shor_Khakassia
0.11717274 Turkish_Rumeli
0.11724582 Turkish_Northwest
0.11726276 Tatar_Mishar
0.11780731 Turkish_Southwest
0.11813502 Turkish_Balikesir
0.11896454 Turkish_North
0.11902240 Turkish_Central
0.11910909 Turkish_Adana
0.11911532 Turkish_Deliorman
0.11914997 Dolgan
0.11920853 Shor
0.11923200 Vepsian
0.11978687 Finnish_East
0.11986855 Tajik
0.12006801 Tajik_Shugnan
0.12014845 Azeri_Turkey
0.12015675 Shor_Mountain
0.12020062 Karelian
0.12024623 Finnish
0.12050528 Italian_Calabria
0.12053540 Russian_Pinega
0.12069967 Roma_Porto
0.12070805 Ashkenazi_Poland
0.12079352 Ashkenazi_Ukraine
0.12080077 Ashkenazi_Russia
0.12081823 Ashkenazi_Lithuania
0.12094511 Roma_Balkans
0.12094942 Sephardic_Jew
0.12103786 Rumelia_East
0.12107358 Turkish_East
0.12107517 Mountain_Jew
0.12108928 Roma_Granada
0.12113365 Ashkenazi_Belarussia
0.12120662 Bosnian
0.12126015 Azeri
0.12134961 Maltese
0.12135867 Cherkes
0.12139484 Lebanese_Muslim
0.12139789 Swiss_Italian
0.12140453 Turkish_Kayseri
0.12143149 Mordovian
0.12158306 Talysh_Azerbaijan
0.12163859 Greek_Macedonia
0.12164504 Syrian
0.12165596 Mongola
0.12168128 Albanian
0.12170438 Slovenian
0.12174062 Bulgarian
0.12176974 Ashkenazi_Germany
0.12178845 Ingrian
0.12180587 Xibo
0.12183413 Greek_Peloponnese
0.12183664 Iraqi
0.12185091 Romanian
0.12188574 Italian_Jew
0.12191847 Kumyk
0.12196573 Austrian
0.12197379 Roma_Bilbao
0.12206559 Romaniote_Jew
0.12207723 Roma_Barcelona
0.12208745 Moldovan
0.12212008 Greek_Central_Macedonia
0.12212811 Montenegrin
0.12216095 Abazin
0.12218176 Italian_Basilicata
0.12220194 Russian_Kostroma
0.12224117 Roma_Madrid
0.12227294 Greek_Dodecanese
0.12229122 Iranian_Fars
0.12229811 Sicilian_East
0.12230970 Iranian_Lor
0.12235552 Ezid
0.12238798 Italian_Abruzzo
0.12240662 Moldovan_o
0.12246975 Iranian_Seyyed
0.12247321 Kabardin
0.12249362 Gagauz
0.12249838 Syrian_Jew
0.12250173 Greek_Crete
0.12253492 Udi
0.12256460 Parsi_Pakistan
0.12257270 Azeri_Dagestan
0.12259073 Italian_Marche
0.12262349 Italian_Northeast
0.12267550 Italian_Molise
0.12276653 Greek_Izmir
0.12282515 Turkish_Trabzon
0.12284943 Hungarian
0.12287783 Libyan_Jew
0.12290040 Lebanese_Christian
0.12292780 Serbian
0.12297603 Greek_Cappadocia
0.12298549 Spanish_Murcia
0.12299543 Croatian
0.12301485 Italian_Tuscany
0.12305433 Italian_Bergamo
0.12306548 Lebanese_Druze
0.12307244 German_East
0.12309356 Parsi_India
0.12310006 Greek_Thessaly
0.12312821 French_Nord
0.12314950 Italian_Apulia
0.12316775 Italian_Umbria
0.12319150 Italian_Campania
0.12323757 French_Alsace
0.12325935 German
0.12327604 Italian_Liguria
0.12328849 Iranian_Zoroastrian
0.12335007 Afrikaner
0.12335086 Czech
0.12338234 Kho_Singanali
0.12340392 Tunisian_Jew
0.12341751 Greek_Central_Anatolia
0.12348593 Chuvash
0.12355747 Italian_Lombardy
0.12358340 Druze
0.12366347 Tajik_Ishkashim
0.12367993 Cypriot
0.12372397 Circassian
0.12374242 Macedonian
0.12374898 Tajik_Yagnobi
0.12376101 Kurdish
0.12376614 Italian_Piedmont
0.12385357 Kaitag
0.12388062 Uthmankhel
0.12392586 Greek_Laconia
0.12395644 Burusho
0.12408085 Karachay
0.12408518 Belgian
0.12410495 Greek_Kos
0.12415247 Slovakian
0.12415490 Georgian_Jew
0.12415579 Pashtun
0.12416487 French_Provence
0.12416533 Italian_Aosta_Valley
0.12420188 Jatt_Pathak
0.12421259 Iranian_Jew
0.12423472 Sicilian_West
0.12429272 Russian_Kursk
0.12429739 Swiss_German
0.12432820 Jordanian
0.12441909 Swedish
0.12452413 Ingushian
0.12453529 French_Corsica
0.12454481 Iranian_Bandari
0.12463384 Italian_Veneto
0.12464378 Palestinian
0.12465318 Tabasaran
0.12465612 Italian_Lazio
0.12466509 Swiss_French
0.12468906 Tajik_Rushan
0.12473518 Cossack_Kuban
0.12473881 Spanish_Cataluna
0.12484674 Moroccan_Jew
0.12484730 Bahun
0.12485052 Yusufzai
0.12491344 Balkar
0.12491523 Armenian
0.12498813 Spanish_Lleida
0.12517568 Russian_Orel
0.12519493 Spanish_Extremadura
0.12519494 Shetlandic
0.12521335 Egyptian
0.12522679 Kubachinian
0.12523232 Dutch
0.12526135 BedouinA
0.12528115 Tarkalani
0.12529671 French_Auvergne
0.12530863 Italian_Trentino-Alto-Adige
0.12534063 Russian_Voronez
0.12534473 Ukrainian
0.12534612 Spanish_Penedes
0.12534831 Spanish_Asturias
0.12535228 Iranian_Mazandarani
0.12536983 Danish
0.12538600 Karaite_Egypt
0.12541074 Spanish_Girona
0.12542330 Spanish_Canarias
0.12542539 Assyrian
0.12549330 Ror
0.12549746 Kamboj
0.12553883 French_Pas-de-Calais
0.12559679 Greek_Trabzon
0.12559773 French_Brittany
0.12560568 English
0.12561489 Iraqi_Jew
0.12563535 French_Occitanie
0.12564728 Avar
0.12575032 Armenian_Hemsheni
0.12576274 Polish
0.12577275 Spanish_Peri-Barcelona
0.12578923 Brahmin_Manipuri
0.12579666 Palestinian_Beit_Sahour
0.12586091 Adygei
0.12589220 Dongxiang
0.12593429 Spanish_Mallorca
0.12601023 Lak
0.12608382 Orcadian
0.12608653 Icelandic
0.12611708 Norwegian
0.12616014 Welsh
0.12617455 Spanish_Valencia
0.12621543 Spanish_Baleares
0.12624898 Spanish_Camp_de_Tarragona
0.12627327 English_Cornwall
0.12632829 Spanish_Galicia
0.12644075 Cossack_Ukrainian
0.12644356 Scottish
0.12651022 Portuguese
0.12660649 French_Paris
0.12663090 Russian_Tver
0.12670022 Chechen
0.12675025 Spanish_Castilla_La_Mancha
0.12675045 Kohistani
0.12678721 Sorb_Niederlausitz
0.12685577 Spanish_Barcelones
0.12686608 Irish
0.12688566 Punjabi_Jatt
0.12699296 Spanish_Castello
0.12704283 Darginian
0.12704904 Estonian
0.12706813 Spanish_Alacant
0.12713545 Khatri
0.12718285 Spanish_Andalucia
0.12720813 Punjabi_Sikh_India
0.12726636 Salar
0.12731238 Spanish_Catalunya_Central
0.12739491 Spanish_Eivissa
0.12741756 Kashmiri_Pandit
0.12742994 Spanish_Terres_de_l'Ebre
0.12753571 Spanish_Pirineu
0.12757183 Spanish_Menorca
0.12772810 Samaritan
0.12778746 Russian_Smolensk
0.12783277 Georgian_Laz
0.12786392 Kalash
0.12787669 Sindhi
0.12795467 Belarusian
0.12800331 Berber_Algeria
0.12818668 Gujar_Pakistan
0.12822204 Spanish_Aragon
0.12823100 French_Seine-Maritime
0.12830021 Spanish_Castilla_Y_Leon
0.12832941 North_Ossetian
0.12844211 Tharu
0.12845537 Newar
0.12850601 Libyan
0.12873995 Ossetian
0.12893764 Gujar_India
0.12900096 Brahmin_Gujarat
0.12901634 Spanish_Cantabria
0.12907200 Burmese
0.12912527 Maori
0.12915484 Brahmin_West_Bengal
0.12925670 Abkhasian
0.12929465 Spanish_Navarra
0.12943315 Ket
0.12945022 Dungan
0.12956750 Lithuanian_PA
0.12972271 Tripuri
0.12973513 French_South
0.13009483 Lithuanian_VA
0.13024980 Kshatriya
0.13026016 Tu
0.13029731 Spanish_La_Rioja
0.13030455 Spanish_Pais_Vasco
0.13052450 Lithuanian_RA
0.13071474 Ronga
0.13087858 Bonan
0.13088234 Jamatia
0.13090653 Kikuyu
0.13091582 Lithuanian_VZ
0.13098812 Makrani
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0.10077781 Tibetan_Nagqu
0.10083317 Relli
0.10083548 Tibetan_Yajiang
0.10092675 Han_Shanghai
0.10136118 BedouinB
0.10150889 Itelmen
0.10154542 Batak
0.10160748 Sherpa
0.10172143 Qiang_Danba
0.10199566 Iraqw
0.10207170 Saudi
0.10208593 Hadza
0.10226959 Agta
0.10259696 Japanese
0.10310148 Qiang_Daofu
0.10316740 Datog
0.10318405 North_Kannadi
0.10338746 Koryak
0.10343518 Pallan
0.10357925 Berber_MAR_ERR
0.10392051 Somali_Kenya
0.10392375 Rendille
0.10408959 Vizayan
0.10415319 Sakilli
0.10415366 Somali
0.10445951 Indonesian_Bali
0.10451481 Tibetan_Chamdo
0.10505331 Berber_Tunisia_Chen
0.10518700 Htin_Mal
0.10556630 Yemenite_Mahra
0.10597841 Gupta
0.10619718 Madiga
0.10682038 Hakkipikki
0.10715440 Masai
0.10740329 Ethiopian_Ari_blacksmith
0.10758924 Sudanese
0.10767800 Ethiopian_Ari_cultivator
0.10778348 Chukchi
0.10792097 Sengwer
0.10812479 Indonesian_Java
0.10895222 Mala
0.10898593 Gond
0.10913417 Luzon
0.10913866 Even
0.10929467 Saharawi
0.10939467 Ethiopian_Ari
0.10955260 Bonda
0.10960521 Irula
0.10967850 Hawaiian
0.10977476 Atayal
0.11002714 Asur
0.11044979 Gadaba
0.11047650 Lebbo
0.11056432 Mlabri
0.11063629 Korwa
0.11066541 Khonda_Dora
0.11067540 Ethiopian_Anuak
0.11084131 Nganassan
0.11194092 Birhor
0.11195057 Bhumij
0.11217265 Ho
0.11218221 Santhal
0.11284191 Juang
0.11293154 Ethiopian_Gumuz
0.11294242 Kadar
0.11351879 Ami
0.11356703 Dinka
0.11445767 Berber_MAR_TIZ
0.11501138 Yakut
0.11502225 Ethiopian_Mursi
0.11530414 Cree
0.11539958 Pulliyar
0.11542885 Malayan
0.11559135 Murut
0.11577513 Dusun
0.11622853 Paniya
0.11728563 Eskimo_Sireniki
0.11730617 Eskimo_Chaplin
0.11742727 Sakha
0.11957381 Eskimo
0.11979065 Eskimo_Naukan
0.12294331 Igorot
0.12606664 Bedzan
0.13640271 Bakola
0.13781217 Chipewyan
0.14471381 Baka
0.14929018 Amerindian_North
0.15276062 Nasoi
0.16620004 Biaka
0.17162568 Australian
0.19575093 Mixtec
0.19612719 Bolivian_Pando
0.19645905 Zapotec
0.19747616 Nahua
0.19809789 Bolivian_Cochabamba
0.19811467 Huichol
0.19868330 Pima
0.19897830 Quechua
0.20013824 Mayan
0.20302388 Mixe
0.20727431 Cachi
0.21187970 Colla
0.21250426 Bolivian_LaPaz
0.21787237 Aymara
0.22038163 Yukpa
0.22123406 Piapoco
0.22375022 Wichi
0.23075211 Kosipe
0.23170648 Karitiana
0.23633335 Surui
0.23823313 Papuan
0.23844971 Koinanbe
0.27335104 Khomani_San
0.27989849 Mbuti
0.38822779 Ju_hoan_North
Wouldn't it make sense to calculate the average IBS values of Saami relative to multiple Mongoloid populations, and not just Chukchi? Now on the second list for Chukchi, Saami rank higher than some Southeast Asians, which doesn't make sense as an overall measure of Mongoloidness.
Or could you check how populations of the Volga-Ural compare to Saami, like for example Komis or Kazan Tatars or Maris?
Couldn't we compile a 99x99 (or whatever) table of each population compared against every other population? Then couldn't we use it as a precalculated matrix of genetic distances? Or for example we could take the average values of the columns for multiple Mongoloid populations and sort the rows of the table based on it.
Sorry for being like Joqool and asking too many questions.
I combined the data you posted (without the common old alleles) into a table. I omitted the row for Chukchis because you didn't post the score of Chukchis with themselves.
Population,Chukchi,Saami
Adygei,0.8405,0.8390
Albanian.DG,0.8380,0.8337
Ami.DG,0.8422,0.8381
Armenian,0.8377,0.8349
Balochi,0.8361,0.7755
BantuHerero,0.7795,0.7803
BantuKenya,0.7834,0.7757
BantuTswana,0.7776,0.8405
Basque,0.8383,0.8329
BedouinB,0.8319,0.8256
Bougainville,0.8303,0.8351
Brahui,0.8370,0.8401
Bulgarian,0.8393,0.8354
Burmese,0.8435,0.8378
Burusho,0.8397,0.8392
Chechen,0.8395,0.8339
China_Lahu,0.8425,0.8439
Czech,0.8394,0.8419
Dai,0.8428,0.8341
Daur,0.8466,0.8380
Druze,0.8335,0.8359
Dusun,0.8416,0.8327
English,0.8404,0.8417
Esan,0.7791,0.7762
Eskimo_Naukan.DG,0.8537,0.8383
Eskimo_Sireniki.DG,0.8540,0.8387
Estonian,0.8410,0.8429
Even,0.8482,0.8400
Finnish,0.8422,0.8442
French,0.8388,0.8397
Gambian,0.7817,0.7786
Georgian,0.8364,0.8378
Greek,0.8383,0.8386
Han,0.8460,0.8358
Hazara,0.8433,0.8391
Hezhen,0.8479,0.8381
Hungarian,0.8400,0.8409
Icelandic,0.8403,0.8420
Iranian-Fars,0.8386,0.8372
Irula,0.8367,0.8340
Itelmen,0.8527,0.8377
Japanese,0.8461,0.8359
Jew_Iraqi,0.8354,0.8358
Jordanian,0.8317,0.8321
Ju_hoan_North,0.7687,0.7657
Kalash,0.8378,0.8369
Kapu,0.8376,0.8349
Karitiana,0.8441,0.8348
Khomani_San,0.7690,0.7661
Kinh,0.8436,0.8346
Korean,0.8455,0.8370
Kurds-IRAQ,0.8424,0.8417
Kusunda,0.8388,0.8317
Kyrgyz_Kyrgyzstan,0.8466,0.8405
Lezgin,0.8386,0.8396
Luhya,0.7825,0.7793
Luo,0.7836,0.7799
Makrani,0.8353,0.8341
Mala,0.8380,0.8341
Mandenka,0.7817,0.7780
Mansi,0.8477,0.8436
Masai,0.7974,0.7952
Mayan,0.8464,0.8366
Mbuti,0.7729,0.7702
Mende,0.7801,0.7769
Mixe,0.8458,0.8358
Mixtec,0.8458,0.8373
Mongola,0.8465,0.8373
Mozabite,0.8215,0.8219
Norwegian,0.8405,0.8421
Orcadian,0.8397,0.8414
Papuan,0.8270,0.8222
Pathan,0.8399,0.8375
Piapoco,0.8454,0.8350
Pima,0.8462,0.8361
Polish,0.8408,0.8417
Punjabi,0.8377,0.8362
Russia_Abkhasian,0.8387,0.8391
Russia_NorthOssetian,0.8387,0.8390
Russian,0.8425,0.8436
Saami,0.8439,0.8527
Saharawi,0.8235,0.8226
Samaritan,0.8321,0.8324
Sardinian,0.8373,0.8388
She,0.8448,0.8353
Sindhi,0.8383,0.8367
Somali,0.8065,0.8049
Spanish,0.8384,0.8398
Surui,0.8438,0.8337
Tajik,0.8396,0.8380
Tuscan,0.8389,0.8390
Ulchi,0.8473,0.8372
Uyghur,0.8440,0.8391
Xibo,0.8460,0.8367
Yadava,0.8388,0.8353
Yakut,0.8474,0.8386
Yi,0.8445,0.8349
Here's the data as a plot. I used hierarchical K-means clustering to divide the populations into 16 groups.
https://i.ibb.co/FK8g6SB/a.png
library(ggplot2);library(factoextra);library(color space)
download.file("https://pastebin.com/raw/FnTJmkAj","chukchisaami")
t<-read.csv("chukchisaami",header=T,row.names=1)
k<-hkmeans(t,16)
ggplot(t,aes(x=Chukchi,y=Saami,label=row.names(t)) )+
geom_text(aes(color=as.factor(k$cluster)),size=2.5 ,show.legend=F)+
theme(
plot.background=element_rect(fill="gray35"),
panel.grid.major=element_line(color="gray35"),
text=element_text(color="gray10"),
axis.text=element_text(color="gray10"),
axis.ticks.x=element_blank(),
axis.ticks.y=element_blank(),
panel.grid.minor=element_blank()
)+
coord_fixed()+
xlab("430K SNPs - Max-Maf 0.3 - Chukchi")+
ylab("430K SNPs - Max-Maf 0.3 - Saami-Finland")+
scale_color_discrete_qualitative(palette="Set 3")
ggsave("/tmp/a.png")
I couldn't get the version of plink from here to compile with either gcc or clang, and when I tried running the Mac binary, it said `Bad CPU type in executable`: https://zzz.bwh.harvard.edu/plink/download.shtml. But now I realized that there's a version by another developer here, with a working Mac binary: http://www.cog-genomics.org/plink/2.0/. I'll figure it out eventually.
Makes good sense. I just didn’t time. Will try to get to it.
It’s good to have both plink 1.9 and 2.0 since 2 doesn’t have all the programs 1.9 does. Download it from https://www.cog-genomics.org/plink/
So for example, would Chukchi really be more genetically akin to Iraqi Kurds than Tajiks? Wow. This contradicts what has been seen in the "vulgar" GEDmatch calculators and on Global25 in general. After years, most of what I consider normal is now based on what those two tools easily accessible to anyone show. As for distances soaring, this happens especially in scaled coordinates but not in unscaled ones. I'll post the unscaled distances and tell me if you find more correlation with your distances. And most importantly, in your opinion, between scaled and unscaled coordinates which one is less worse?
]
To be fair we should use a couple more Siberian pops and maybe separate the Tajiks out to see if an outlier is causing issues. I did find some sequencing errors in some of the Simons samples so that should also be looked into.
G25 is a PCA program that’s mostly suitable for PCA work and not for distances or admix proportions. Like I explained in my previous post it seems to work for distances for the 1st few on the list then goes wacko for the rest. Also for some reason distances get huge as you go down the list. Biggest problem is unknown push-pull of other 1000s of samples he used in run. With IBS you just compare 2 samples or pops allele for allele and you don’t have these unknown forces from 1000s of samples affecting coordinates of your target in 25 dimensional space
Scaled of course for PCA work
They are a Turkic ethnic group btw.
What's the average East Eurasian amount that you have observed for Kurds? And do you think its from Steppe or from Turkic invaders into West Asia?
Is it lower than Iraqi Turkmens?
Damn that's remarkable. Maybe some type of connection with Uyghurs through shared potential Turkic affinity?
Will get back to you later today
Zanzibar
02-26-2021, 04:24 PM
Will get back to you later today
How are the results?
How are the results?
Eurasian DNA has a pretty detailed study where they model whole genome Turks and Kurds as modern Iranian/Armenian/Georgian/Adygei/Abkhasian/Jordanian + E. Asian and Siberian . They said it’ll be out soon but based on https://eurasiandna.com/2659-2/ it looks like around 10% E. Asian
Flashball
03-05-2021, 02:17 AM
Its normal for a hybride population to have among them a part of ''european'' face.
Flashball
03-05-2021, 02:25 AM
That’s not true otherwise chinese would look African or European . Everything in your body is dictated by genes. They shape your eyes, nose etc.
Now what you maybe referring to is that if you have 2 brothers with 10% E. Asian. It’s possible one brother’s 10% would include genes that affect facial features whereas the other brothers 10% E Asian doesn’t include genes affecting facial features and would thus look more European than his Asian looking brother
This.
Genotype = phénotype.
A sami with 75% euro and 25% ''siberian like'' could look european, his brother more 50-50, other almost fully siberian.
Same thing with askenazi.
Not a surprise...
When did Proto-Sami and Proto-Finnic split?
Scandal
03-05-2021, 10:15 AM
When did Proto-Sami and Proto-Finnic split?
https://en.wikipedia.org/wiki/S%C3%A1mi_languages#History
The Proto-Samic language is believed to have formed in the vicinity of the Gulf of Finland between 1000 BC to 700 AD, deriving from a common Proto-Sami-Finnic language (M. Korhonen 1981).[17] However, reconstruction of any basic proto-languages in the Uralic family have reached a level close to or identical to Proto-Uralic (Salminen 1999).[18] According to the comparative linguist Ante Aikio, the Proto-Samic language developed in South Finland or in Karelia around 2000–2500 years ago, spreading then to northern Fennoscandia.[19]
Zanzibar
03-07-2021, 05:33 AM
This.
Genotype = phénotype.
A sami with 75% euro and 25% ''siberian like'' could look european, his brother more 50-50, other almost fully siberian.
Same thing with askenazi.
Not a surprise...
This thread is made to disprove the stereotype that most modern day Samis are not 100% "pure" Saami but have recent Northern Germanic (Norwegian, Swedish) ancestors and that's why most of them now look like other Northern Euros, which is highly untrue as prove by the DNA results of the OP shown here.
Flashball
03-07-2021, 07:26 AM
This thread is made to disprove the stereotype that most modern day Samis are not 100% "pure" Saami but have recent Northern Germanic (Norwegian, Swedish) ancestors and that's why most of them now look like other Northern Euros, which is highly untrue as prove by the DNA results of the OP shown here.
It seems to me that the Sami have been studied enough and that there is enough data to be able to affirm that they have the phenotype of their ancestral contributions: European (mainly) and "siberian-like" (not Japanese).
It's nothing surprising to have this kind of face with people who have this kind of genetics.
The Sami are "pure" in the sense that they have their own "genetic signature" and are indistinguishable from "pure" Swedes. As the Ashkenazim are "pure" in their hybridization (for several centuries), it could be contradictory to stick "pure" or "homogeneous" and "hybrid" in one sentence, but not really: one can be homogeneous in a mixture.
eTrex
03-07-2021, 07:57 AM
Looks like hes only about a quarter saami.
Lemminkäinen
03-07-2021, 09:35 AM
I don't understand how removing minor alleles would in all cases weight more recent ancestry. Recent ancestry between Saami and Karitiana? Really? It is true that we can consider minor alleles being older in case they are inherited, not mutated, but sure f.ex. Karitiana and Saami people share only very old ancestry and removing minor alleles in a large data shifts the allele distribution away from the pairwise common ancestry. What do we expect if we use SNPs of chip population after removing minor alleles? All I want to say that deleting alleles can be good, but also bad.
Zanzibar
03-07-2021, 01:14 PM
It seems to me that the Sami have been studied enough and that there is enough data to be able to affirm that they have the phenotype of their ancestral contributions: European (mainly) and "siberian-like" (not Japanese).
It's nothing surprising to have this kind of face with people who have this kind of genetics.
The Sami are "pure" in the sense that they have their own "genetic signature" and are indistinguishable from "pure" Swedes. As the Ashkenazim are "pure" in their hybridization (for several centuries), it could be contradictory to stick "pure" or "homogeneous" and "hybrid" in one sentence, but not really: one can be homogeneous in a mixture.
Well you might be right regarding them being studied enough, but a lot of ppl including some users here seem to downplay or underestimate the amount of Siberian ancestry in the Sami; thinking that they are only 5% or 10-15% Mongoloid at most which is highly untrue. They are at least 20-25% Siberian or more (I have even seen a few samples who are almost 30% Mongoloid) except the Kola Saami who are less Siberian-shifted as they have recent admixture from other Euros.
Btw the Siberian portion of their ancestry is most similar to Arctic Mongs such as Nganasan and maybe Yukaghir.
Hmm when you say that the Sami are indistinguishable from "pure" Swedes, are you referring to their genomic aspect? I beg to differ as Swedes have literally zero East Eurasian ancestry while Samis have loads of Siberian. Furthermore, the Sami have very low Neolithic admix (like 15-16% on average) and much higher HG ancestry compared to most Euros, while Swedes have loads of EEF (around 36% or more) and very high Steppe ancestry.
I do get your point about how the term "pure" and "homogenous" can be applied even for hybrid populations though.
Ajeje Brazorf
03-09-2021, 10:42 PM
Well you might be right regarding them being studied enough, but a lot of ppl including some users here seem to downplay or underestimate the amount of Siberian ancestry in the Sami; thinking that they are only 5% or 10-15% Mongoloid at most which is highly untrue. They are at least 20-25% Siberian or more (I have even seen a few samples who are almost 30% Mongoloid) except the Kola Saami who are less Siberian-shifted as they have recent admixture from other Euros.
Btw the Siberian portion of their ancestry is most similar to Arctic Mongs such as Nganasan and maybe Yukaghir.
Hmm when you say that the Sami are indistinguishable from "pure" Swedes, are you referring to their genomic aspect? I beg to differ as Swedes have literally zero East Eurasian ancestry while Samis have loads of Siberian. Furthermore, the Sami have very low Neolithic admix (like 15-16% on average) and much higher HG ancestry compared to most Euros, while Swedes have loads of EEF (around 36% or more) and very high Steppe ancestry.
I do get your point about how the term "pure" and "homogenous" can be applied even for hybrid populations though.
<colgroup><col><col></colgroup><tbody>
Sample
EAST EURASIAN %
Saami:saami2
33,4
Saami:saami11
33,4
Saami:saami1
30,8
Saami:GS000035025
30,6
Saami:saami3
29,6
Saami:saami8
29,2
Saami:saami13
28,8
Saami:saami14
28,6
Saami:saami7
28,4
Saami:saami5
28,2
Saami:saami9
28,2
Saami:saami12
27
Saami:GS000035026
26,8
Saami_Kola:SaamiKola6
26
Saami:saami6
25,8
Saami_Kola:SaamiKola25
24,4
Saami_Kola:SaamiKola40
24,2
Saami_Kola:SaamiKola5
23,2
Saami:Saami001
22,8
Saami:saami4
22,8
Saami_Kola:SaamiKola74
19,4
Saami_Kola:SaamiKola47
17
Saami_Kola:SaamiKola7
15,8
Saami_Kola:SaamiKola49
13
</tbody>
Zanzibar
06-09-2021, 03:35 PM
Looks like hes only about a quarter saami.
Nope he seems to be a pure Saami based on his results.
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