View Full Version : Are Euros closer to West Asia, North Africa, some Central Asians than East Asians are to Siberians?
Zanzibar
11-28-2021, 09:42 AM
Is this because West Eurasians are less isolated from one another and shared more genetic components such as EEF, CHG, Steppe more than East Eurasians do?
Like if you notice East Asians here seem to be genetically more distant from many Siberian populations than Europeans are to West Asians, North Africans and South Central Asians like Tajiks, Afghans, Kalash.
Distance to: English
0.13495718 Italian_Calabria
0.14073311 Ashkenazi_Germany
0.14797407 Tatar_Kazan
0.15222007 Darginian
0.15806418 Chechen
0.15941922 Tajik_Yagnobi
0.16170312 Adygei
0.16279491 Turkish_North
0.16598093 Tajik_Rushan
0.17174317 Turkish_East
0.17291307 Cypriot
0.17654193 Ossetian
0.17919342 Azerbaijani
0.18146889 Iranian_Zoroastrian
0.18482676 Turkish_Trabzon
0.18585313 Syrian
0.18666478 Armenian
0.19119984 Lebanese_Christian
0.19150013 Georgian_Laz
0.19191049 Assyrian
0.19782542 Saami
0.19795619 Palestinian_Beit_Sahour
0.19823759 Georgian_Megr
0.19961644 Jordanian
0.20004149 Udmurt
0.20240717 Iraqi_Jew
0.20322401 Iranian_Mazandarani
0.20448407 Palestinian
0.20581011 Pashtun_North_Afghanistan
0.20730745 Tatar_Crimean_steppe
0.20905043 Samaritan
0.21953197 Jatt_Pathak
0.22050357 Ror
0.22571712 Turkmen
0.22718906 Kho_Singanali
0.22972964 Kalash
0.23546362 Balochi
0.23853694 Moroccan_North
0.23879009 Pashtun_Kurram
0.24050008 Yemenite_Amran
0.24156246 Egyptian
0.24241418 Mari
0.25253866 Tunisian
0.26064119 Saudi
0.26261359 Sindhi
0.26339192 Burusho
0.26718126 Yemenite_Mahra
0.26809501 Mozabite
0.27689024 Uzbek
0.30435969 Saharawi
Distance to: Norwegian
0.14001127 Tatar_Kazan
0.14782213 Italian_Calabria
0.15269523 Ashkenazi_Germany
0.15463180 Darginian
0.15953135 Tajik_Yagnobi
0.16310466 Chechen
0.16340044 Tajik_Rushan
0.16859005 Adygei
0.16882821 Turkish_North
0.18022534 Turkish_East
0.18378911 Ossetian
0.18506152 Cypriot
0.18560255 Saami
0.18607481 Azerbaijani
0.18780003 Iranian_Zoroastrian
0.18977107 Udmurt
0.19571511 Syrian
0.19589839 Turkish_Trabzon
0.19737539 Armenian
0.20171539 Assyrian
0.20221225 Georgian_Laz
0.20261487 Tatar_Crimean_steppe
0.20267707 Lebanese_Christian
0.20501595 Pashtun_North_Afghanistan
0.20800675 Georgian_Megr
0.20848916 Palestinian_Beit_Sahour
0.20935093 Iranian_Mazandarani
0.20943289 Jordanian
0.21311621 Iraqi_Jew
0.21424570 Palestinian
0.21580995 Jatt_Pathak
0.21710230 Ror
0.22065021 Samaritan
0.22331346 Turkmen
0.22421099 Kho_Singanali
0.22792976 Kalash
0.23388498 Mari
0.23652604 Balochi
0.23716406 Pashtun_Kurram
0.24648444 Moroccan_North
0.24997666 Yemenite_Amran
0.25088880 Egyptian
0.25988384 Burusho
0.26026315 Tunisian
0.26109935 Sindhi
0.26975137 Saudi
0.27209362 Uzbek
0.27544394 Mozabite
0.27631497 Yemenite_Mahra
0.31099540 Saharawi
Distance to: Ukrainian
0.12990819 Tatar_Kazan
0.15406687 Italian_Calabria
0.15606868 Darginian
0.15877692 Ashkenazi_Germany
0.15972336 Tajik_Yagnobi
0.16342506 Tajik_Rushan
0.16422988 Chechen
0.16609948 Adygei
0.16815725 Turkish_North
0.17927329 Saami
0.18036462 Ossetian
0.18120890 Turkish_East
0.18449143 Udmurt
0.18590878 Azerbaijani
0.18819131 Iranian_Zoroastrian
0.18861781 Cypriot
0.19545392 Turkish_Trabzon
0.19637390 Syrian
0.19757256 Tatar_Crimean_steppe
0.19780240 Armenian
0.20159033 Georgian_Laz
0.20240172 Assyrian
0.20370524 Pashtun_North_Afghanistan
0.20531316 Lebanese_Christian
0.20675512 Georgian_Megr
0.20732235 Iranian_Mazandarani
0.21148328 Jordanian
0.21234756 Iraqi_Jew
0.21320522 Palestinian_Beit_Sahour
0.21595770 Palestinian
0.21716055 Jatt_Pathak
0.21746786 Ror
0.22021889 Turkmen
0.22098686 Samaritan
0.22181869 Kho_Singanali
0.22486058 Mari
0.22706190 Kalash
0.23541273 Balochi
0.23587718 Pashtun_Kurram
0.25082623 Yemenite_Amran
0.25137478 Egyptian
0.25199564 Moroccan_North
0.25859008 Burusho
0.26066811 Sindhi
0.26340648 Tunisian
0.26894675 Uzbek
0.27097989 Saudi
0.27771421 Yemenite_Mahra
0.27974899 Mozabite
0.31490251 Saharawi
Now compare to East Asians to many Siberians, the distance seems much higher especially Nganassan and Samoyedics such as Selkup, Nenets and Paleosiberians such as Chukchi, Eskimo.
Distance to: Han_Henan
0.08063643 Rai
0.10097847 Gurung
0.12279979 Kinh_Vietnam
0.13015106 Tamang
0.13507158 Burmese
0.13598195 Garo
0.13616733 Dai
0.14921910 Oroqen
0.15834879 Thai
0.16568507 Filipino_Luzon
0.16683400 Nivkh
0.17098176 Cambodian
0.17464834 Atayal
0.18785060 Malay_Malaysia
0.19453734 Buryat
0.20426038 Batak_Toba
0.20459322 Mentawai
0.22513592 Indonesian_Java
0.22559156 Mogush
0.22592925 Tuvinian
0.22721431 Tahitian
0.22741764 Samoan
0.22951066 Altaian
0.23016126 Tharu
0.25845181 Todzin
0.25931494 Newar
0.26228442 Anakalang
0.26414844 Manggarai_Rampasasa
0.26496099 Kazakh
0.27015927 Khakass
0.27125005 Yakut
0.28432701 Itelmen
0.30142502 Evenk
0.30660090 Chukchi
0.31319893 Hazara
0.31590366 Ngadha_Bena
0.32465385 Eskimo_Sireniki
0.33170261 Tetum_Umanen_Lawalu
0.34261601 Selkup
0.34479834 Nenets
0.35339849 Nganassan
0.37316773 Yukagir_Forest
0.38027115 Khanty
0.38426929 Mansi
Distance to: Japanese
0.11038120 Rai
0.12381833 Gurung
0.13885523 Oroqen
0.14296708 Nivkh
0.14555118 Kinh_Vietnam
0.14803585 Tamang
0.15686463 Burmese
0.15967841 Dai
0.16236012 Garo
0.16985722 Filipino_Luzon
0.17722511 Thai
0.17833819 Atayal
0.18811671 Buryat
0.19340031 Cambodian
0.20304299 Malay_Malaysia
0.21018086 Mentawai
0.21336423 Batak_Toba
0.22016286 Mogush
0.22029273 Tuvinian
0.22516759 Tahitian
0.22528960 Samoan
0.22683050 Altaian
0.23604712 Tharu
0.24399813 Indonesian_Java
0.24997550 Todzin
0.26410544 Yakut
0.26429809 Newar
0.26468925 Kazakh
0.26510839 Anakalang
0.26869988 Khakass
0.26949736 Itelmen
0.27019850 Manggarai_Rampasasa
0.28681343 Evenk
0.29255957 Chukchi
0.31245668 Eskimo_Sireniki
0.31440406 Hazara
0.31768100 Ngadha_Bena
0.33058329 Tetum_Umanen_Lawalu
0.33723993 Selkup
0.33760294 Nenets
0.33957514 Nganassan
0.36954318 Yukagir_Forest
0.37665369 Khanty
0.38149357 Mansi
Distance to: Korean
0.09542701 Rai
0.11421661 Gurung
0.13437997 Oroqen
0.13758753 Kinh_Vietnam
0.14358738 Tamang
0.14701021 Nivkh
0.15135281 Dai
0.15211531 Burmese
0.15391058 Garo
0.17324825 Filipino_Luzon
0.17435804 Thai
0.17998873 Atayal
0.18722777 Buryat
0.18724479 Cambodian
0.20139673 Malay_Malaysia
0.21198551 Mentawai
0.21537706 Batak_Toba
0.22038200 Tuvinian
0.22086490 Mogush
0.22929135 Altaian
0.23214911 Samoan
0.23273219 Tahitian
0.23908100 Indonesian_Java
0.24052149 Tharu
0.24976434 Todzin
0.26195436 Yakut
0.26943300 Kazakh
0.26955490 Anakalang
0.26986824 Newar
0.27184439 Khakass
0.27264859 Itelmen
0.27303188 Manggarai_Rampasasa
0.28647432 Evenk
0.29549905 Chukchi
0.31527058 Eskimo_Sireniki
0.32084357 Hazara
0.32269827 Ngadha_Bena
0.33687223 Tetum_Umanen_Lawalu
0.33985777 Nganassan
0.34028945 Selkup
0.34078187 Nenets
0.37557576 Yukagir_Forest
0.38171778 Khanty
0.38651312 Mansi
Thoughts? Pretty crazy, Norwegians are here are closer to Saudis and Uzbeks than Koreans are to Evenks (Tungusic tribe of Siberia) or how the English are closer to Balochi than Han Chinese from Henan are to Kazakhs.
Hell even Ukrainians are genetically closer to Chechens, Tajiks, Ashkenazi Jews and Adygei than they are to Saami and Udmurts.
It seems Saharawi is the only one who is comparable to some Siberians in distance.
Thanks for posting these ! Another piece of evidence to be added to the evidence I have already pointed out so far that G25 shouldn't be taken seriously. Keep posting these because the more proofs people see how G25 is wrong the more they will be convinced it's a joke :D
No it's NOT true that Europeans are closer to West or Central or South- Central Asians than East Asians are to Siberians !
Here's your proof that G25 is wrong.
These are gene to gene comparisons averaged over populations using IBS and 400,000 overlapping SNPs
As you can see Han share more genes with Siberians such as Even (0.733105) and even Mansi (0.71674) than British share with even the closest W. Asians (0.7131) and Pathan (0.7090)
<colgroup width="268"></colgroup> <colgroup width="85" span="2"></colgroup> <tbody>
IBS with HAN_1000G
REGION
AVG-IBS
Chinese_Han_S_1000G
E_Asia
0.742565
Chinese_Han_1000G
E_Asia
0.742465
Japanese_1000G
E_Asia
0.74105
Chinese_Dai_1000G
E_Asia
0.74039
Vietnam_Kinh_1000G
E_Asia
0.73973
Mongola_Simons
E_Asia
0.738855
Even_Simons
Siberia
0.733105
PALEO-SIBERIAN-Kolyma-Mesol-WGS
Siberia
0.729545
Karitiana_Simons
Americas
0.72603
Kyrgyz_Simons
C_Asia
0.725555
Mayan_Simons
Americas
0.72554
Onge_1000G
S_Asia
0.71883
Uyghur
C_Asia
0.71769
Peruvian_1000G
Americas
0.71683
Mansi_Simons
Siberia
0.71674
Uzbek
C_Asia
0.715205
Tatar_Tomsk
E_Europe
0.71519
Turkmen
C_Asia
0.71304
Bengali_1000G
S_Asia
0.71212
Bashkir
E_Europe
0.710635
Tamil_1000G
S_Asia
0.70905
Indian_Telugu_1000G
S_Asia
0.7084
Gujarati_1000G
S_Asia
0.70741
Punjabi_Simons
S_Asia
0.70672
Punjabi_Lahore_1000G
S_Asia
0.70636
Saami_Simons
E_Europe
0.705815
ANS-Yana-UP-WGS
Siberia
0.70572
Tatar_Volga
E_Europe
0.704275
Pathan_Simons
S_Asia
0.70238
Brahui_Simons
S_Asia
0.70056
Finnish_1000G
E_Europe
0.700375
Kurds_IQ
W_Asia
0.699595
Ossetian_Simons
W_Asia
0.699535
Russian_Simons
E_Europe
0.69942
Turkish_Kayseri_Simons
W_Asia
0.69868
YAMNAYA-Karagash-Dipl
E_Europe
0.698655
Finnish_Simons
E_Europe
0.698485
Iranian_South_Simons
W_Asia
0.69765
Abkhasian_Simons
W_Asia
0.69736
Lezgin_Simons
W_Asia
0.697145
Estonian_Simons
E_Europe
0.696935
British_1000G
W_Europe
0.696865
WHG-Loschbour
W_Europe
0.696275
Armenian_Simons
W_Asia
0.69611
Georgian_Simons
W_Asia
0.695625
Iberian_1000G
W_Europe
0.69553
Basque_Simons
W_Europe
0.69529
BedouinB_Simons
W_Asia
0.693955
</tbody>
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<colgroup width="201"></colgroup> <colgroup width="85" span="2"></colgroup> <tbody>
IBS with BRITISH_1000G
REGION
AVG-IBS
British_1000G
W_Europe
0.7181
WHG-Loschbour
W_Europe
0.7179
Finnish_1000G
E_Europe
0.7170
Basque_Simons
W_Europe
0.7169
Finnish_Simons
E_Europe
0.7165
Estonian_Simons
E_Europe
0.7164
Iberian_1000G
W_Europe
0.7161
Russian_Simons
E_Europe
0.7155
YAMNAYA-Karagash-Dipl
E_Europe
0.7154
EEF-Stuttgart
W_Europe
0.7151
Lezgin_Simons
W_Asia
0.7133
Abkhasian_Simons
W_Asia
0.7131
Kurds_IQ
W_Asia
0.7131
Tatar_Volga
E_Europe
0.7131
Armenian_Simons
W_Asia
0.7128
Georgian_Simons
W_Asia
0.7127
Saami_Simons
E_Europe
0.7126
Ossetian_Simons
W_Asia
0.7124
Turkish_Kayseri_Simons
W_Asia
0.7122
Iranian_South_Simons
W_Asia
0.7107
Bashkir
E_Europe
0.7102
BedouinB_Simons
W_Asia
0.7094
Pathan_Simons
S_Asia
0.7090
Brahui_Simons
S_Asia
0.7090
Jordanian_Simons
W_Asia
0.7090
Colombian_1000G
Americas
0.7084
Turkmen
C_Asia
0.7078
Tatar_Tomsk
E_Europe
0.7075
Mansi_Simons
Siberia
0.7070
Punjabi_Lahore_1000G
S_Asia
0.7069
Uzbek
C_Asia
0.7065
Gujarati_1000G
S_Asia
0.7061
Punjabi_Simons
S_Asia
0.7052
</tbody>
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If anyone is wondering why Chinese share more genes with other Chinese (IBS 0.742) than British with other British (IBS 0.718), this means that there is less genetic variation among Chinese than among British.
Since genotype is phenotype this means Chinese faces are more uniform among themselves whereas British faces are all over the place indicating British are more mixed
Zanzibar
11-28-2021, 12:17 PM
Thanks for posting these ! Another piece of evidence to be added to the evidence I have already pointed out so far that G25 shouldn't be taken seriously. Keep posting these because the more proofs people see how G25 is wrong the more they will be convinced it's a joke :D
No it's NOT true that Europeans are closer to West or Central or South- Central Asians than East Asians are to Siberians !
Here's your proof that G25 is wrong.
These are gene to gene comparisons averaged over populations using IBS and 400,000 overlapping SNPs
As you can see Han share more genes with Siberians such as Even (0.733105) and even Mansi (0.71674) than British share with even the closest W. Asians (0.7131) and Pathan (0.7090)
<colgroup width="268"></colgroup> <colgroup width="85" span="2"></colgroup> <tbody>
IBS with HAN_1000G
REGION
AVG-IBS
Chinese_Han_S_1000G
E_Asia
0.742565
Chinese_Han_1000G
E_Asia
0.742465
Japanese_1000G
E_Asia
0.74105
Chinese_Dai_1000G
E_Asia
0.74039
Vietnam_Kinh_1000G
E_Asia
0.73973
Mongola_Simons
E_Asia
0.738855
Even_Simons
Siberia
0.733105
PALEO-SIBERIAN-Kolyma-Mesol-WGS
Siberia
0.729545
Karitiana_Simons
Americas
0.72603
Kyrgyz_Simons
C_Asia
0.725555
Mayan_Simons
Americas
0.72554
Onge_1000G
S_Asia
0.71883
Uyghur
C_Asia
0.71769
Peruvian_1000G
Americas
0.71683
Mansi_Simons
Siberia
0.71674
Uzbek
C_Asia
0.715205
Tatar_Tomsk
E_Europe
0.71519
Turkmen
C_Asia
0.71304
Bengali_1000G
S_Asia
0.71212
Bashkir
E_Europe
0.710635
Tamil_1000G
S_Asia
0.70905
Indian_Telugu_1000G
S_Asia
0.7084
Gujarati_1000G
S_Asia
0.70741
Punjabi_Simons
S_Asia
0.70672
Punjabi_Lahore_1000G
S_Asia
0.70636
Saami_Simons
E_Europe
0.705815
ANS-Yana-UP-WGS
Siberia
0.70572
Tatar_Volga
E_Europe
0.704275
Pathan_Simons
S_Asia
0.70238
Brahui_Simons
S_Asia
0.70056
Finnish_1000G
E_Europe
0.700375
Kurds_IQ
W_Asia
0.699595
Ossetian_Simons
W_Asia
0.699535
Russian_Simons
E_Europe
0.69942
Turkish_Kayseri_Simons
W_Asia
0.69868
YAMNAYA-Karagash-Dipl
E_Europe
0.698655
Finnish_Simons
E_Europe
0.698485
Iranian_South_Simons
W_Asia
0.69765
Abkhasian_Simons
W_Asia
0.69736
Lezgin_Simons
W_Asia
0.697145
Estonian_Simons
E_Europe
0.696935
British_1000G
W_Europe
0.696865
WHG-Loschbour
W_Europe
0.696275
Armenian_Simons
W_Asia
0.69611
Georgian_Simons
W_Asia
0.695625
Iberian_1000G
W_Europe
0.69553
Basque_Simons
W_Europe
0.69529
BedouinB_Simons
W_Asia
0.693955
</tbody>
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<colgroup width="201"></colgroup> <colgroup width="85" span="2"></colgroup> <tbody>
IBS with BRITISH_1000G
REGION
AVG-IBS
British_1000G
W_Europe
0.7181
WHG-Loschbour
W_Europe
0.7179
Finnish_1000G
E_Europe
0.7170
Basque_Simons
W_Europe
0.7169
Finnish_Simons
E_Europe
0.7165
Estonian_Simons
E_Europe
0.7164
Iberian_1000G
W_Europe
0.7161
Russian_Simons
E_Europe
0.7155
YAMNAYA-Karagash-Dipl
E_Europe
0.7154
EEF-Stuttgart
W_Europe
0.7151
Lezgin_Simons
W_Asia
0.7133
Abkhasian_Simons
W_Asia
0.7131
Kurds_IQ
W_Asia
0.7131
Tatar_Volga
E_Europe
0.7131
Armenian_Simons
W_Asia
0.7128
Georgian_Simons
W_Asia
0.7127
Saami_Simons
E_Europe
0.7126
Ossetian_Simons
W_Asia
0.7124
Turkish_Kayseri_Simons
W_Asia
0.7122
Iranian_South_Simons
W_Asia
0.7107
Bashkir
E_Europe
0.7102
BedouinB_Simons
W_Asia
0.7094
Pathan_Simons
S_Asia
0.7090
Brahui_Simons
S_Asia
0.7090
Jordanian_Simons
W_Asia
0.7090
Colombian_1000G
Americas
0.7084
Turkmen
C_Asia
0.7078
Tatar_Tomsk
E_Europe
0.7075
Mansi_Simons
Siberia
0.7070
Punjabi_Lahore_1000G
S_Asia
0.7069
Uzbek
C_Asia
0.7065
Gujarati_1000G
S_Asia
0.7061
Punjabi_Simons
S_Asia
0.7052
</tbody>
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Would using f2 stats as distance be more accurate than G25?
Here is the f2 distance to Han btw: https://www.mycompiler.io/new/bash
.000227 Cordona_Manchu
.000254 Tujia
.000470 Korean
.000502 Yugur
.000892 Cordona_Korean
.000930 Mongola
.000939 Tu
.001211 Cordona_Han_South
.001253 Dong
.001273 Dongxiang
.001281 Xibo
.001358 Kinh
.001380 Cordona_Vietnamese
.001397 Dungan
.001619 Zhuang
.001674 Miao
.001766 Yi
.001788 Vietnamese
.001907 Bonan
.002030 Qiang
.002117 Mulam
.002221 Japanese
.002267 Salar
.002291 Burmese
.002357 Naxi
.002473 Maonan
.002630 She
.002686 Tibetan
.002729 Daur
.002744 Dai
.003059 Li
.003132 Gelao
.003279 Tagalog
.003677 Hezhen
.003862 Magar
.003895 Cordona_Tibetan
.004002 Mongol
.004044 Gurung
.004139 Cordona_Mongol
.004237 Cambodian
.004327 Oroqen
.004652 Malay
.004699 Tamang
.004931 Kalmyk
.005213 Sherpa
.005247 Thai
.005316 Rai
.005689 Visayan
.005730 Cordona_Buryat
.005783 Ilocano
.005975 Buryat
.005991 Khamnegan
.006014 Cordona_Indonesia_Java
.006141 Evenk_FarEast
.006332 Kazakh_China
.006627 Kyrgyz_Kyrgyzstan
.006662 Kyrgyz_China
.006918 Kyrgyz_Tajikistan
.007119 China_Lahu
.007160 Nanai
.007443 Tuvinian
.007460 Cordona_Uygur
.007661 Kazakh
.007705 Tibetan_Yunnan
.007722 Negidal
.007752 Tharu
.007774 Cordona_Kazakh
.007841 Dusun
.007857 Altaian
.008097 Cordona_Altai_Kizhi
.008257 Ulchi
.008355 Newar
.008825 Ami
.008829 Uyghur
.009177 Karakalpak
.009276 Khakass_Kachin
.009362 Dolgan
.009624 Hazara
.009686 Murut
.009833 Cordona_Teleut
.009918 Khakass
.009949 Nogai_Astrakhan
.010145 Yakut
.010524 Even
.010545 Cordona_Yakut
.011072 Nogai_Stavropol
.012023 Cordona_Dolgan
.012717 Yukagir_Tundra
.012828 Kankanaey
.013178 Kusunda
.013274 Tatar_Siberian
.013932 Todzin
.013969 Nivh
.014005 Uzbek
.014042 Cordona_Even
.014133 Cordona_Evenk
.014506 Evenk_Transbaikal
.014616 Tubalar
.014688 Yukagir_Forest
.014948 Cordona_Tundra_Nentsi
.015269 Shor_Mountain
.015444 Bahun
.016491 Altaian_Chelkan
.016577 Turkmen
.016939 Atayal
.016971 Tofalar
.017144 Cordona_Ket
.017378 Cordona_Selkup
.017465 Cordona_Tajik
.017544 Cordona_Turkmen
.017669 Enets
.017763 Selkup
.017854 Bashkir
.017885 Cordona_Khant
.018261 Bengali
.018806 Shor_Khakassia
.018894 Tatar_Siberian_Zabolotniye
.018910 Mansi
.019345 Cordona_Koryak
.019634 Ket
.019725 Nogai_Karachay_Cherkessia
.019808 Cordona_Nganasan
.019944 Cordona_Forest_Nentsi
.020362 Tlingit
.020737 Chukchi
.020864 Cordona_Indian
.021032 Nganasan
.021384 Cordona_Sri_Lankan
.021697 Burusho
.021821 Cordona_Yukagir
.022164 Eskimo_ChaplinSireniki
.022257 Cordona_Mari
.022516 Punjabi
.022638 Cordona_Komi
.022697 GujaratiC
.022841 Tatar_Kazan
.022917 Aleut
.022928 Koryak
.023251 Tajik
.023310 GujaratiB
.023610 Chuvash
.023893 GujaratiD
.023979 GujaratiA
.024221 Udmurt
.024472 Sindhi_Pakistan
.024796 Jew_Cochin
.024870 Pathan
.024963 Itelmen
.025009 Besermyan
.025936 Tatar_Mishar
.027304 Abazin
.027483 Eskimo_Naukan
.027514 Kabardinian
.027892 Balochi
.028435 Brahui
.028577 Balkar
.028723 Kumyk
.028770 Turkish
.028797 Azeri
.028876 Circassian
.028976 Makrani
.029013 Cordona_Turk
.029029 Iranian_Bandari
.029468 Ossetian
.029546 Russian_Archangelsk_Leshukonsky
.029607 Karachai
.029642 Iranian
.029821 Cordona_Iranian
.029893 Russian_Vologda
.029929 Cordona_Mordva
.030025 Russian_Archangelsk_Krasnoborsky
.030194 Mordovian
.030348 Adygei
.030381 Turkish_Balikesir
.030793 Russian_Archangelsk_Pinezhsky
.031101 Ingushian
.031205 Lezgin
.031384 Veps
.031442 Karelian
.031442 Yemeni
.031467 Finnish
.031535 Chechen
.031560 Yemeni_Desert2
.031856 Tabasaran
.031888 Russian_Tver
.031975 Russian_Yaroslavl
.032077 Lebanese
.032110 Jordanian
.032133 Russian_Ryazan
.032144 Mayan
.032201 Ezid
.032328 Abkhasian
.032381 Lebanese_Muslim
.032394 Yemeni_Highlands_Raymah
.032442 BedouinA
.032531 Egyptian
.032570 Russian_Orel
.032586 Cordona_Egyptian
.032629 Bulgarian
.032668 Syrian
.032715 Gagauz
.032825 Armenian
.032905 Hungarian
.032912 Quechua
.032943 Cordona_British
.032977 Ukrainian
.033058 Lak
.033094 Sicilian
.033096 Russian_Kursk
.033115 Palestinian
.033198 Avar
.033212 Ukrainian_North
.033224 Kaitag
.033262 Kurd
.033288 Russian_Belgorod
.033291 Greek
.033298 Jew_Turkish
.033300 Cordona_Avar
.033336 Albanian
.033337 Libyan
.033345 Russian_Kaluga
.033388 Tunisian
.033391 Jew_Ashkenazi
.033396 Belarusian
.033434 Romanian
.033461 Georgian
.033492 Assyrian
.033518 Estonian
.033590 Italian_South
.033609 Russian_Pskov
.033675 Lebanese_Christian
.033726 Cordona_German
.033728 Czech
.033767 French
.033788 Jew_Moroccan
.033825 Zapotec
.033829 Croatian
.033830 Moldavian
.033893 Italian_North
.033934 Cypriot
.033946 Cordona_Italian
.033987 Russian_Smolensk
.034082 Bolivian
.034086 Maltese
.034089 Spanish
.034242 Norwegian
.034283 Canary_Islander
.034291 Jew_Georgian
.034335 Moroccan
.034396 Chukchi1
.034401 Jew_Iranian
.034404 English
.034422 Jew_Iraqi
.034590 Yemeni_Highlands
.034628 Druze
.034717 Armenian_Hemsheni
.034748 Icelandic
.034773 Darginian
.034805 Lithuanian
.034806 Yemeni_Northwest
.034860 Kalash
.035048 Orcadian
.035496 Scottish
.035691 Saudi
.035766 Mixtec
.035822 Jew_Libyan
.035986 Spanish_North
.036058 Jew_Tunisian
.036837 Jew_Yemenite
.036949 Basque
.037030 Eritrea
.037562 Mozabite
.037682 Kubachinian
.037961 Yemeni_Desert
.038200 Sardinian
.038376 Algerian
.038546 Jew_Ethiopian
.038626 Saharawi
.040476 Mixe
.040573 BedouinB
.042880 Piapoco
.043335 Pima
.043594 Somali
.043838 Nasioi
.046965 Datog
.048594 Cordona_PNG_Highland
.049759 Masai
.052983 Kikuyu
.053853 AA
.055645 Australian
.057600 Karitiana
.058640 Papuan
.062142 Luhya
.062621 Luo
.063436 Surui
.063562 Cordona_Dinka
.063734 BantuKenya
.065325 Gambian
.065859 Malawi_Ngoni
.066138 Malawi_Tumbuka
.066339 Mandenka
.066381 Malawi_Chewa
.066390 Yoruba
.066516 Malawi_Yao
.066669 Mende
.066980 BantuSA_Ovambo
.067295 Esan
.068156 Namibia_Bantu_Herero
.068414 BantuSA
.074629 Khomani
.077097 Biaka
.081758 Hadza1
.087625 Mbuti
.094140 Ju_hoan_North
The lower the number in IBS, means the more distant the other population is?
Also can you answer this please?: Are Volga Uralic folks like Mari, Udmurt genetically closer to Central Asians/Turkics and Tajiks than most Euros?: https://www.theapricity.com/forum/showthread.php?348444-Many-VURers-Saamis-are-closer-to-many-Turkics-Central-Asians-than-to-most-Euros-according-to-G25
Komintasavalta
11-28-2021, 12:24 PM
As you can see Han share more genes with Siberians such as Even[/B] (0.733105) and even Mansi (0.71674) than British share with even the closest W. Asians (0.7131) and Pathan (0.7090)
Yeah but in your run, the IBS of Han_1000G with its closest neighbor is 0.742565, but the IBS of British_1000G with its closest neighbor is 0.7179.
In my run below, the IBS of East Asians with other East Asians is also higher than the IBS of Europeans with other Europeans. I don't know if it's because SNP panels are biased towards SNPs that are polymorphic in Europeans or something. For example the IBS value of Han with their closest neighbor is about 0.823, but the IBS value of the French with their closest neighbor is about 0.812:
https://i.ibb.co/nMDJkxq/2.png
JamesBond007
11-28-2021, 12:28 PM
Thanks for posting these ! Another piece of evidence to be added to the evidence I have already pointed out so far that G25 shouldn't be taken seriously. Keep posting these because the more proofs people see how G25 is wrong the more they will be convinced it's a joke :D
G25 is not a serious academic tool and neither is AncestryDNA and 23andme. Rather G25 is one of the best tools a layman can use to infer ancestry. You are using the wrong tool for the job because being an American you are anti-intellectual joke. AncestryDNA and 23andme etc.. are jokes compared to G25 everything is relative.
Yeah but in your run, the IBS of Han_1000G with its closest neighbor is 0.742565, but the IBS of British_1000G with its closest neighbor is 0.7179.
In my run below, the IBS of East Asians with other East Asians is also higher than the IBS of Europeans with other Europeans. I don't know if it's because SNP panels are biased towards SNPs that are polymorphic in Europeans or something. For example the IBS value of Han with their closest neighbor is about 0.823, but the IBS value of the French with their closest neighbor is about 0.812:
https://i.ibb.co/nMDJkxq/2.png
Yes ascertainment bias kills analysis. You can’t get rid of it. The SNPs 23andme uses are so hugely biased they cause Chinese to be closer to Africans than Eurasians. Only real fix is use whole genomes for every sample however million SNPs you’ll need
I think you need to clean up your dataset you seem to have a mish mash of data from all over. Simons is very different from 1000G which is different from HGDP. Try to use more compatible data and always use geno 0 to make sure all samples share the same SNPs.
Absent ascertainment bias look at my comment above for explanation of why intra European IBS lower than intra E Asian IBS
G25 is not a serious academic tool and neither is AncestryDNA and 23andme. Rather G25 is one of the best tools a layman can use to infer ancestry. You are using the wrong tool for the job because being an American you are anti-intellectual joke. AncestryDNA and 23andme etc.. are jokes compared to G25 everything is relative.
Yes all of them have corrupted millions of minds and caused a very skewed view of population histories, but the reason I have a beef with G25 is because it’s so readily available and easy to use that every other lay person uses it. It along other amateur tools have so brainwashed people that people will not recognize accurate ancestry analysis anymore even if it hits them on the face.
It’ll be very hard to undo the damage already done to peoples view of population history. Very bad indeed !
Zanzibar
11-28-2021, 12:54 PM
Yes all of them have corrupted millions of minds and caused a very skewed view of population histories, but the reason I have a beef with G25 is because it’s so readily available and easy to use that every other lay person uses it. It along other amateur tools have so brainwashed people that people will not recognize accurate ancestry analysis anymore even if it hits them on the face.
It’ll be very hard to undo the damage already done to peoples view of population history. Very bad indeed !
Can you answer the post #4 by me please?: https://www.theapricity.com/forum/showthread.php?355687-Are-Euros-closer-to-West-Asia-North-Africa-some-Central-Asians-than-East-Asians-are-to-Siberians&p=7360043&viewfull=1#post7360043
Can you answer the post #4 by me please?: https://www.theapricity.com/forum/showthread.php?355687-Are-Euros-closer-to-West-Asia-North-Africa-some-Central-Asians-than-East-Asians-are-to-Siberians&p=7360043&viewfull=1#post7360043
I would think so but you don’t have the same comparison posted as your G25. Maybe Komi can do that for you using 1000G and Simons samples
Zanzibar
11-28-2021, 01:44 PM
I would think so but you don’t have the same comparison posted as your G25. Maybe Komi can do that for you using 1000G and Simons samples
Sorry can you elaborate more please? Are you referring to the f2 distance to Han or the G25 runs showing Volga Uralics being closer to Central Asians/Turkics, Tajiks and Khanty/Mansi than to most Euros?
Yes all of them have corrupted millions of minds and caused a very skewed view of population histories, but the reason I have a beef with G25 is because it’s so readily available and easy to use that every other lay person uses it. It along other amateur tools have so brainwashed people that people will not recognize accurate ancestry analysis anymore even if it hits them on the face.
It’ll be very hard to undo the damage already done to peoples view of population history. Very bad indeed !
In this community we believe in Gedmatch and G25. You really should get the hell out of here, buddy!
In this community we believe in Gedmatch and G25. You really should get the hell out of here, buddy!
Speak for yourself and I’m not your buddy. Who the hell are you to tell anyone to get out of here. Stop being a prick and Post something useful for change or stfu.
Sorry can you elaborate more please? Are you referring to the f2 distance to Han or the G25 runs showing Volga Uralics being closer to Central Asians/Turkics, Tajiks and Khanty/Mansi than to most Euros?
You didn’t post the same comparison using f2 like you did with G25. If you don’t know how to run f2s maybe Komi can help you
Zanzibar
11-28-2021, 03:27 PM
You didn’t post the same comparison using f2 like you did with G25. If you don’t know how to run f2s maybe Komi can help you
Isn't this f2 distance to Han?: https://www.mycompiler.io/new/bash
Distance to Han:
.000227 Cordona_Manchu
.000254 Tujia
.000470 Korean
.000502 Yugur
.000892 Cordona_Korean
.000930 Mongola
.000939 Tu
.001211 Cordona_Han_South
.001253 Dong
.001273 Dongxiang
.001281 Xibo
.001358 Kinh
.001380 Cordona_Vietnamese
.001397 Dungan
.001619 Zhuang
.001674 Miao
.001766 Yi
.001788 Vietnamese
.001907 Bonan
.002030 Qiang
.002117 Mulam
.002221 Japanese
.002267 Salar
.002291 Burmese
.002357 Naxi
.002473 Maonan
.002630 She
.002686 Tibetan
.002729 Daur
.002744 Dai
.003059 Li
.003132 Gelao
.003279 Tagalog
.003677 Hezhen
.003862 Magar
.003895 Cordona_Tibetan
.004002 Mongol
.004044 Gurung
.004139 Cordona_Mongol
.004237 Cambodian
.004327 Oroqen
.004652 Malay
.004699 Tamang
.004931 Kalmyk
.005213 Sherpa
.005247 Thai
.005316 Rai
.005689 Visayan
.005730 Cordona_Buryat
.005783 Ilocano
.005975 Buryat
.005991 Khamnegan
.006014 Cordona_Indonesia_Java
.006141 Evenk_FarEast
.006332 Kazakh_China
.006627 Kyrgyz_Kyrgyzstan
.006662 Kyrgyz_China
.006918 Kyrgyz_Tajikistan
.007119 China_Lahu
.007160 Nanai
.007443 Tuvinian
.007460 Cordona_Uygur
.007661 Kazakh
.007705 Tibetan_Yunnan
.007722 Negidal
.007752 Tharu
.007774 Cordona_Kazakh
.007841 Dusun
.007857 Altaian
.008097 Cordona_Altai_Kizhi
.008257 Ulchi
.008355 Newar
.008825 Ami
.008829 Uyghur
.009177 Karakalpak
.009276 Khakass_Kachin
.009362 Dolgan
.009624 Hazara
.009686 Murut
.009833 Cordona_Teleut
.009918 Khakass
.009949 Nogai_Astrakhan
.010145 Yakut
.010524 Even
.010545 Cordona_Yakut
.011072 Nogai_Stavropol
.012023 Cordona_Dolgan
.012717 Yukagir_Tundra
.012828 Kankanaey
.013178 Kusunda
.013274 Tatar_Siberian
.013932 Todzin
.013969 Nivh
.014005 Uzbek
.014042 Cordona_Even
.014133 Cordona_Evenk
.014506 Evenk_Transbaikal
.014616 Tubalar
.014688 Yukagir_Forest
.014948 Cordona_Tundra_Nentsi
.015269 Shor_Mountain
.015444 Bahun
.016491 Altaian_Chelkan
.016577 Turkmen
.016939 Atayal
.016971 Tofalar
.017144 Cordona_Ket
.017378 Cordona_Selkup
.017465 Cordona_Tajik
.017544 Cordona_Turkmen
.017669 Enets
.017763 Selkup
.017854 Bashkir
.017885 Cordona_Khant
.018261 Bengali
.018806 Shor_Khakassia
.018894 Tatar_Siberian_Zabolotniye
.018910 Mansi
.019345 Cordona_Koryak
.019634 Ket
.019725 Nogai_Karachay_Cherkessia
.019808 Cordona_Nganasan
.019944 Cordona_Forest_Nentsi
.020362 Tlingit
.020737 Chukchi
.020864 Cordona_Indian
.021032 Nganasan
.021384 Cordona_Sri_Lankan
.021697 Burusho
.021821 Cordona_Yukagir
.022164 Eskimo_ChaplinSireniki
.022257 Cordona_Mari
.022516 Punjabi
.022638 Cordona_Komi
.022697 GujaratiC
.022841 Tatar_Kazan
.022917 Aleut
.022928 Koryak
.023251 Tajik
.023310 GujaratiB
.023610 Chuvash
.023893 GujaratiD
.023979 GujaratiA
.024221 Udmurt
.024472 Sindhi_Pakistan
.024796 Jew_Cochin
.024870 Pathan
.024963 Itelmen
.025009 Besermyan
.025936 Tatar_Mishar
.027304 Abazin
.027483 Eskimo_Naukan
.027514 Kabardinian
.027892 Balochi
.028435 Brahui
.028577 Balkar
.028723 Kumyk
.028770 Turkish
.028797 Azeri
.028876 Circassian
.028976 Makrani
.029013 Cordona_Turk
.029029 Iranian_Bandari
.029468 Ossetian
.029546 Russian_Archangelsk_Leshukonsky
.029607 Karachai
.029642 Iranian
.029821 Cordona_Iranian
.029893 Russian_Vologda
.029929 Cordona_Mordva
.030025 Russian_Archangelsk_Krasnoborsky
.030194 Mordovian
.030348 Adygei
.030381 Turkish_Balikesir
.030793 Russian_Archangelsk_Pinezhsky
.031101 Ingushian
.031205 Lezgin
.031384 Veps
.031442 Karelian
.031442 Yemeni
.031467 Finnish
.031535 Chechen
.031560 Yemeni_Desert2
.031856 Tabasaran
.031888 Russian_Tver
.031975 Russian_Yaroslavl
.032077 Lebanese
.032110 Jordanian
.032133 Russian_Ryazan
.032144 Mayan
.032201 Ezid
.032328 Abkhasian
.032381 Lebanese_Muslim
.032394 Yemeni_Highlands_Raymah
.032442 BedouinA
.032531 Egyptian
.032570 Russian_Orel
.032586 Cordona_Egyptian
.032629 Bulgarian
.032668 Syrian
.032715 Gagauz
.032825 Armenian
.032905 Hungarian
.032912 Quechua
.032943 Cordona_British
.032977 Ukrainian
.033058 Lak
.033094 Sicilian
.033096 Russian_Kursk
.033115 Palestinian
.033198 Avar
.033212 Ukrainian_North
.033224 Kaitag
.033262 Kurd
.033288 Russian_Belgorod
.033291 Greek
.033298 Jew_Turkish
.033300 Cordona_Avar
.033336 Albanian
.033337 Libyan
.033345 Russian_Kaluga
.033388 Tunisian
.033391 Jew_Ashkenazi
.033396 Belarusian
.033434 Romanian
.033461 Georgian
.033492 Assyrian
.033518 Estonian
.033590 Italian_South
.033609 Russian_Pskov
.033675 Lebanese_Christian
.033726 Cordona_German
.033728 Czech
.033767 French
.033788 Jew_Moroccan
.033825 Zapotec
.033829 Croatian
.033830 Moldavian
.033893 Italian_North
.033934 Cypriot
.033946 Cordona_Italian
.033987 Russian_Smolensk
.034082 Bolivian
.034086 Maltese
.034089 Spanish
.034242 Norwegian
.034283 Canary_Islander
.034291 Jew_Georgian
.034335 Moroccan
.034396 Chukchi1
.034401 Jew_Iranian
.034404 English
.034422 Jew_Iraqi
.034590 Yemeni_Highlands
.034628 Druze
.034717 Armenian_Hemsheni
.034748 Icelandic
.034773 Darginian
.034805 Lithuanian
.034806 Yemeni_Northwest
.034860 Kalash
.035048 Orcadian
.035496 Scottish
.035691 Saudi
.035766 Mixtec
.035822 Jew_Libyan
.035986 Spanish_North
.036058 Jew_Tunisian
.036837 Jew_Yemenite
.036949 Basque
.037030 Eritrea
.037562 Mozabite
.037682 Kubachinian
.037961 Yemeni_Desert
.038200 Sardinian
.038376 Algerian
.038546 Jew_Ethiopian
.038626 Saharawi
.040476 Mixe
.040573 BedouinB
.042880 Piapoco
.043335 Pima
.043594 Somali
.043838 Nasioi
.046965 Datog
.048594 Cordona_PNG_Highland
.049759 Masai
.052983 Kikuyu
.053853 AA
.055645 Australian
.057600 Karitiana
.058640 Papuan
.062142 Luhya
.062621 Luo
.063436 Surui
.063562 Cordona_Dinka
.063734 BantuKenya
.065325 Gambian
.065859 Malawi_Ngoni
.066138 Malawi_Tumbuka
.066339 Mandenka
.066381 Malawi_Chewa
.066390 Yoruba
.066516 Malawi_Yao
.066669 Mende
.066980 BantuSA_Ovambo
.067295 Esan
.068156 Namibia_Bantu_Herero
.068414 BantuSA
.074629 Khomani
.077097 Biaka
.081758 Hadza1
.087625 Mbuti
.094140 Ju_hoan_North
But yes I haven't done it for the other pops.
Btw can you do a run on IBS whether Mari, Udmurts are closer to Tajiks and Central Asians/Turks like Uzbeks, Turkmens, Nogais, Karakalpaks, etc than to most Euros?
Isn't this f2 distance to Han?: https://www.mycompiler.io/new/bash
Distance to Han:
.
But yes I haven't done it for the other pops.
Btw can you do a run on IBS whether Mari, Udmurts are closer to Tajiks and Central Asians/Turks like Uzbeks, Turkmens, Nogais, Karakalpaks, etc than to most Euros?
Yes it’s showing distance to Even of 0.010 but your G25 also compared to Euros vs W/S/C Asians. Have someone do both comparisons at same time using f2 for reliability and accuracy.
I’ll post the IBS you want in a minute
Komintasavalta
11-28-2021, 04:43 PM
Isn't this f2 distance to Han?: https://www.mycompiler.io/new/bash
You forgot to include the shell command:
curl -s https://pastebin.com/raw/B1t0ESsj|tr -d \\r|awk -F, 'NR==1{for(i=2;i<=NF;i++)if($i==x)break;next}$1!=x{print$i,$1}' x=Han -|sort -n
You can recreate the global f2 matrix like this:
$ wget https://reichdata.hms.harvard.edu/pub/datasets/amh_repo/curated_releases/V50/V50.0/SHARE/public.dir/v50.0_HO_public.{anno,ind,snp,geno}
$ igno()(grep -Ev '\.REF|rel\.|fail\.|Ignore_|_dup|_contam|_lc|_rela tive|_father|_mother|_son|_daughter|_brother|_sist er|_sibling|_twin|Neanderthal|Denisova|Vindija_lig ht|Gorilla|Macaque|Marmoset|Orangutan|Primate_Chim p|hg19ref')
$ sed 1d v50.0_HO_public.anno|awk -F$'\t' '$7!~/\./&&$5==0'|sort -t$'\t' -rnk14|awk -F\\t '!a[$3]++{print$2,$7}'|igno|grep -v _o|cut -d' ' -f1|grep -v ,>ind
$ brew install R
$ Rscript -e 'install.packages(c("devtools","tidyverse"));devtools::install_github("uqrmaie1/admixtools")'
$ Rscript -e 'library(admixtools);library(tidyverse);blocks=f2_ from_geno("v50.0_HO_public",inds=readLines("ind"),maxmiss=1);f=f2(blocks,unique_only=F);f[,-4]%>%pivot_wider(names_from=pop1,values_from=est)%>%data.frame(row.names=1)%>%round(7)%>%write.csv("worldf2.csv",quote=F)'
$ awk -F, 'NR==1{for(i=2;i<=NF;i++)if($i==x)break;next}$1!=x{print$i,$1}' x=Udmurt worldf2.csv|sort -n|head|awk '{$1=sprintf("%.5f",$1)}1'
However it suffers from the bias that populations with a small sample size get a higher distance to other populations than populations with a large sample size, because in populations with a large sample size, random individual-level variation gets more averaged out. The IBS distances in my previous post don't suffer from the same problem, because they are the average values of the IBS values between each individual pair of samples within two populations, or in other words the population averages are calculated after the distances, but with f2, the distances are calculated after the population averages.
Generally speaking W. Siberians will always have smaller distances to Finns and Russians than any Iranics. As you go to E. Siberia or E. Asia things change. Here generally E. Asians will be closer to Iranics than Europeans.
I didn't have Udmurts and had only one Mari sample so I used Mansi and Even and Simons 730K SNPs overlapping with all samples
<colgroup width="141"></colgroup> <colgroup width="163"></colgroup> <colgroup width="131"></colgroup> <colgroup width="123"></colgroup> <tbody>
POP
Pi_Hat_AVERAGED
IBS with MANSI
NORMALIZED
Mansi
0.09
0.7673
100
Even
0.02
0.7632
94.73
Yakut
0.02
0.7620
93.17
Altaian
0.07
0.7617
92.81
Hezhen
0.00
0.7604
91.12
Kyrgyz
0.05
0.7604
91.05
Ulchi
0.00
0.7603
91.02
Eskimo
0.00
0.7590
89.32
Mongola
0.00
0.7585
88.63
Tu
0.00
0.7576
87.48
Japanese
0.00
0.7569
86.59
Uyghur
0.02
0.7566
86.17
Hazara
0.02
0.7564
85.83
Saami
0.00
0.7559
85.28
Han
0.00
0.7556
84.89
Burmese
0.00
0.7555
84.72
Dai
0.00
0.7541
82.87
Russian
0.00
0.7532
81.67
Lahu
0.00
0.7530
81.49
Finnish
0.00
0.7524
80.75
Mayan
0.00
0.7523
80.62
Ami
0.00
0.7519
80
Estonian
0.00
0.7517
79.82
Burusho
0.00
0.7515
79.55
Bengali
0.00
0.7514
79.44
Pima
0.00
0.7512
79.19
Pathan
0.00
0.7505
78.24
Hungarian
0.00
0.7500
77.59
Punjabi
0.00
0.7498
77.32
Adygei
0.00
0.7497
77.17
Ossetian
0.00
0.7497
77.14
Kurds-IQ
0.00
0.7494
76.75
Bulgarian
0.00
0.7493
76.73
Orcadian
0.00
0.7490
76.34
Czech
0.00
0.7489
76.18
Chechen
0.00
0.7488
76.03
English
0.00
0.7488
76.01
Mala
0.00
0.7488
75.97
Sindhi
0.00
0.7483
75.38
Turkish
0.00
0.7482
75.24
Irula
0.00
0.7481
75.12
Lezgin
0.00
0.7480
75.04
Abkhasian
0.00
0.7480
74.94
Tajik_Simons
0.00
0.7479
74.83
Iranian
0.00
0.7474
74.25
Greek
0.00
0.7474
74.17
Spanish
0.00
0.7473
74.09
Kusunda
0.00
0.7470
73.7
Basque
0.00
0.7470
73.66
Armenian
0.00
0.7469
73.55
Kalash
0.00
0.7468
73.45
French
0.00
0.7465
73.04
Brahui
0.00
0.7464
72.84
Karitiana
0.00
0.7461
72.51
Albanian
0.00
0.7460
72.36
Georgian
0.00
0.7458
72.17
Surui
0.00
0.7458
72.07
Balochi
0.00
0.7454
71.57
Makrani
0.00
0.7447
70.68
Jew_Iraqi
0.00
0.7445
70.39
Sardinian
0.00
0.7444
70.32
Druze
0.00
0.7434
69.06
Jew_Yemenite
0.00
0.7418
66.92
Jordanian
0.00
0.7403
65.02
BedouinB
0.00
0.7402
64.81
Saharawi
0.00
0.7357
59.06
Mozabite
0.00
0.7348
57.86
Papuan
0.00
0.7308
52.64
Luhya
0.00
0.7037
17.48
Esan
0.00
0.7010
13.92
Mbuti
0.00
0.6939
4.75
Ju_hoan_North
0.00
0.6915
1.63
Khomani_San
0.00
0.6902
0
</tbody>
<colgroup width="181"></colgroup> <colgroup width="150"></colgroup> <colgroup width="181"></colgroup> <colgroup width="117"></colgroup> <tbody>
POP
Pi_Hat_AVERAGED
IBS with EVEN
NORMALIZED
Even
0.15
0.7832
100.0
Yakut
0.14
0.7811
97.8
Ulchi
0.15
0.7807
97.3
Hezhen
0.15
0.7796
96.2
Mongola
0.13
0.7749
91.3
Japanese
0.13
0.7738
90.1
Altaian
0.11
0.7725
88.6
Han
0.08
0.7722
88.4
Tu
0.12
0.7717
87.9
Eskimo
0.00
0.7713
87.4
Dai
0.01
0.7691
85.1
Burmese
0.08
0.7687
84.7
Kyrgyz
0.11
0.7681
84.0
Ami
0.00
0.7676
83.5
Lahu
0.00
0.7675
83.4
Mansi
0.02
0.7632
78.9
Mayan
0.00
0.7600
75.4
Uyghur
0.01
0.7593
74.7
Pima
0.00
0.7589
74.3
Hazara
0.00
0.7586
74.0
Kusunda
0.00
0.7555
70.7
Karitiana
0.00
0.7545
69.6
Surui
0.00
0.7537
68.8
Bengali
0.00
0.7493
64.2
Saami
0.00
0.7490
63.9
Mala
0.00
0.7479
62.7
Irula
0.00
0.7473
62.1
Burusho
0.00
0.7462
60.8
Punjabi
0.00
0.7457
60.3
Pathan
0.00
0.7425
57.0
Sindhi
0.00
0.7420
56.5
Russian
0.00
0.7406
54.9
Ossetian
0.00
0.7401
54.4
Finnish
0.00
0.7398
54.2
Kurds-IQ
0.00
0.7391
53.4
Chechen
0.00
0.7389
53.1
Tajik_Simons
0.00
0.7386
52.8
Turkish
0.00
0.7386
52.8
Adygei
0.00
0.7384
52.6
Kalash
0.00
0.7380
52.2
Brahui
0.00
0.7377
51.9
Balochi
0.00
0.7377
51.8
Estonian
0.00
0.7376
51.8
Abkhasian
0.00
0.7372
51.4
Iranian
0.00
0.7370
51.2
Lezgin
0.00
0.7368
50.9
Hungarian
0.00
0.7366
50.7
Bulgarian
0.00
0.7364
50.5
Papuan
0.00
0.7364
50.5
Polish
0.00
0.7361
50.2
Czech
0.00
0.7360
50.1
Orcadian
0.00
0.7360
50.0
Makrani
0.00
0.7353
49.4
Spanish
0.00
0.7349
49.0
Armenian
0.00
0.7348
48.8
Greek
0.00
0.7347
48.7
English
0.00
0.7346
48.6
French
0.00
0.7345
48.5
Georgian
0.00
0.7345
48.5
Albanian
0.00
0.7344
48.4
Basque
0.00
0.7341
48.0
Jew_Iraqi
0.00
0.7336
47.5
Druze
0.00
0.7331
47.1
Sardinian
0.00
0.7327
46.6
Jew_Yemenite
0.00
0.7308
44.6
BedouinB
0.00
0.7303
44.1
Jordanian
0.00
0.7300
43.8
Saharawi
0.00
0.7265
40.0
Mozabite
0.00
0.7264
39.9
Luhya
0.00
0.7014
13.5
Esan
0.00
0.6998
11.8
Mbuti
0.00
0.6926
4.2
Ju_hoan_North
0.00
0.6901
1.5
Khomani_San
0.00
0.6887
0.0
</tbody>
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Avicenna
11-28-2021, 04:59 PM
Yes all of them have corrupted millions of minds and caused a very skewed view of population histories, but the reason I have a beef with G25 is because it’s so readily available and easy to use that every other lay person uses it. It along other amateur tools have so brainwashed people that people will not recognize accurate ancestry analysis anymore even if it hits them on the face.
It’ll be very hard to undo the damage already done to peoples view of population history. Very bad indeed !
I'm pretty sure we had a afghan pashtun guy on here a while back have an identity crisis over this gedmatch/g25 shenanigans. Not saying it's complete bs but honestly there Alot of holes in these , what seems to me , bias calculators. Try going over to anthrogenica and telling them this lol . Cult mentality they have .
Komintasavalta
11-28-2021, 05:03 PM
Generally speaking W. Siberians will always have smaller distances to Finns and Russians than any Iranics.
Aren't Hazara Iranic? Also based on my f2 run, Mansi are closer to Tajiks and Pathans than to Finns:
$ curl -s https://pastebin.com/raw/B1t0ESsj|tr -d \\r|awk -F, 'NR==1{for(i=2;i<=NF;i++)if($i==x)break;next}$1!=x{print$i,$1}' x=Mansi -|sort -n|grep -En 'Finnish|Pathan|Pashtun|Tajik$|Hazara'
19:.00621 Hazara
40:.00858 Tajik
52:.01015 Pathan
54:.01041 Finnish
I'm pretty sure we had a afghan pashtun guy on here a while back have an identity crisis over this gedmatch/g25 shenanigans. Not saying it's complete bs but honestly there Alot of holes in these , what seems to me , bias calculators. Try going over to anthrogenica and telling them this lol . Cult mentality they have .
Exactly cults only allow people whose ideas are aligned with the cult leaders. That’s why you have to be able to verify anything posted on forums with actual science since they’re biased to the forum owner’s own ideas and generally those forum owners aren’t scientists. Not to say there isn’t a few knowledgeable people on forums but they’re generally not able to freely express themselves no matter how valid their analysis is
The tools you mentioned were never designed to do a one to one comparison between a test subject and a population. Unfortunately the brainwashing has already been done. It’ll be very hard for people to unlearn the skewed analysis they have learned over the past few years
Aren't Hazara Iranic? Also based on my f2 run, Mansi are closer to Tajiks and Pathans than to Finns:
$ curl -s https://pastebin.com/raw/B1t0ESsj|tr -d \\r|awk -F, 'NR==1{for(i=2;i<=NF;i++)if($i==x)break;next}$1!=x{print$i,$1}' x=Mansi -|sort -n|grep -En 'Finnish|Pathan|Pashtun|Tajik$|Hazara'
19:.00621 Hazara
40:.00858 Tajik
52:.01015 Pathan
54:.01041 Finnish
Which datasets are you basing it on and how many overlapping snps. There is all kinds of ascertainment bias depending on the data set it also comes down to the individual Finn or Tajik samples
Avicenna
11-28-2021, 05:27 PM
Aren't Hazara Iranic? Also based on my f2 run, Mansi are closer to Tajiks and Pathans than to Finns:
$ curl -s https://pastebin.com/raw/B1t0ESsj|tr -d \\r|awk -F, 'NR==1{for(i=2;i<=NF;i++)if($i==x)break;next}$1!=x{print$i,$1}' x=Mansi -|sort -n|grep -En 'Finnish|Pathan|Pashtun|Tajik$|Hazara'
19:.00621 Hazara
40:.00858 Tajik
52:.01015 Pathan
54:.01041 Finnish
Lol are you serious bro? Hazaras are Turco Mongols and speak the hazaragi dialect which is Dari/ Farsi but contains some Mongol words and other things . They are more east Eurasian shifted than even central Asian turkics like Turkmens or Uzbeks .
Avicenna
11-28-2021, 05:31 PM
Exactly cults only allow people whose ideas are aligned with the cult leaders. That’s why you have to be able to verify anything posted on forums with actual science since they’re biased to the forum owner’s own ideas and generally those forum owners aren’t scientists. Not to say there isn’t a few knowledgeable people on forums but they’re generally not able to freely express themselves no matter how valid their analysis is
The tools you mentioned were never designed to do a one to one comparison between a test subject and a population. Unfortunately the brainwashing has already been done. It’ll be very hard for people to unlearn the skewed analysis they have learned over the past few years
People would get their knickers in a twist when people would compare afghans with their iranic Kin like Kurds , compared to populations east of the Indus . So they would.pull.out some bs oracle list which showed some western shifted NW south Asians to afghans and pamiris . Based on that , they would conclude that afghans should be grouped with Indians . Ffs . Go to anthrogenica , and this is what they low-key put out .
Zanzibar
11-28-2021, 05:32 PM
Generally speaking W. Siberians will always have smaller distances to Finns and Russians than any Iranics. As you go to E. Siberia or E. Asia things change. Here generally E. Asians will be closer to Iranics than Europeans.
I didn't have Udmurts and had only one Mari sample so I used Mansi and Even and Simons 730K SNPs overlapping with all samples
<colgroup width="141"></colgroup> <colgroup width="163"></colgroup> <colgroup width="131"></colgroup> <colgroup width="123"></colgroup> <tbody>
POP
Pi_Hat_AVERAGED
IBS with MANSI
NORMALIZED
Mansi
0.09
0.7673
100
Even
0.02
0.7632
94.73
Yakut
0.02
0.7620
93.17
Altaian
0.07
0.7617
92.81
Hezhen
0.00
0.7604
91.12
Kyrgyz
0.05
0.7604
91.05
Ulchi
0.00
0.7603
91.02
Eskimo
0.00
0.7590
89.32
Mongola
0.00
0.7585
88.63
Tu
0.00
0.7576
87.48
Japanese
0.00
0.7569
86.59
Uyghur
0.02
0.7566
86.17
Hazara
0.02
0.7564
85.83
Saami
0.00
0.7559
85.28
Han
0.00
0.7556
84.89
Burmese
0.00
0.7555
84.72
Dai
0.00
0.7541
82.87
Russian
0.00
0.7532
81.67
Lahu
0.00
0.7530
81.49
Finnish
0.00
0.7524
80.75
Mayan
0.00
0.7523
80.62
Ami
0.00
0.7519
80
Estonian
0.00
0.7517
79.82
Burusho
0.00
0.7515
79.55
Bengali
0.00
0.7514
79.44
Pima
0.00
0.7512
79.19
Pathan
0.00
0.7505
78.24
Hungarian
0.00
0.7500
77.59
Punjabi
0.00
0.7498
77.32
Adygei
0.00
0.7497
77.17
Ossetian
0.00
0.7497
77.14
Kurds-IQ
0.00
0.7494
76.75
Bulgarian
0.00
0.7493
76.73
Orcadian
0.00
0.7490
76.34
Czech
0.00
0.7489
76.18
Chechen
0.00
0.7488
76.03
English
0.00
0.7488
76.01
Mala
0.00
0.7488
75.97
Sindhi
0.00
0.7483
75.38
Turkish
0.00
0.7482
75.24
Irula
0.00
0.7481
75.12
Lezgin
0.00
0.7480
75.04
Abkhasian
0.00
0.7480
74.94
Tajik_Simons
0.00
0.7479
74.83
Iranian
0.00
0.7474
74.25
Greek
0.00
0.7474
74.17
Spanish
0.00
0.7473
74.09
Kusunda
0.00
0.7470
73.7
Basque
0.00
0.7470
73.66
Armenian
0.00
0.7469
73.55
Kalash
0.00
0.7468
73.45
French
0.00
0.7465
73.04
Brahui
0.00
0.7464
72.84
Karitiana
0.00
0.7461
72.51
Albanian
0.00
0.7460
72.36
Georgian
0.00
0.7458
72.17
Surui
0.00
0.7458
72.07
Balochi
0.00
0.7454
71.57
Makrani
0.00
0.7447
70.68
Jew_Iraqi
0.00
0.7445
70.39
Sardinian
0.00
0.7444
70.32
Druze
0.00
0.7434
69.06
Jew_Yemenite
0.00
0.7418
66.92
Jordanian
0.00
0.7403
65.02
BedouinB
0.00
0.7402
64.81
Saharawi
0.00
0.7357
59.06
Mozabite
0.00
0.7348
57.86
Papuan
0.00
0.7308
52.64
Luhya
0.00
0.7037
17.48
Esan
0.00
0.7010
13.92
Mbuti
0.00
0.6939
4.75
Ju_hoan_North
0.00
0.6915
1.63
Khomani_San
0.00
0.6902
0
</tbody>
<colgroup width="181"></colgroup> <colgroup width="150"></colgroup> <colgroup width="181"></colgroup> <colgroup width="117"></colgroup> <tbody>
POP
Pi_Hat_AVERAGED
IBS with EVEN
NORMALIZED
Even
0.15
0.7832
100.0
Yakut
0.14
0.7811
97.8
Ulchi
0.15
0.7807
97.3
Hezhen
0.15
0.7796
96.2
Mongola
0.13
0.7749
91.3
Japanese
0.13
0.7738
90.1
Altaian
0.11
0.7725
88.6
Han
0.08
0.7722
88.4
Tu
0.12
0.7717
87.9
Eskimo
0.00
0.7713
87.4
Dai
0.01
0.7691
85.1
Burmese
0.08
0.7687
84.7
Kyrgyz
0.11
0.7681
84.0
Ami
0.00
0.7676
83.5
Lahu
0.00
0.7675
83.4
Mansi
0.02
0.7632
78.9
Mayan
0.00
0.7600
75.4
Uyghur
0.01
0.7593
74.7
Pima
0.00
0.7589
74.3
Hazara
0.00
0.7586
74.0
Kusunda
0.00
0.7555
70.7
Karitiana
0.00
0.7545
69.6
Surui
0.00
0.7537
68.8
Bengali
0.00
0.7493
64.2
Saami
0.00
0.7490
63.9
Mala
0.00
0.7479
62.7
Irula
0.00
0.7473
62.1
Burusho
0.00
0.7462
60.8
Punjabi
0.00
0.7457
60.3
Pathan
0.00
0.7425
57.0
Sindhi
0.00
0.7420
56.5
Russian
0.00
0.7406
54.9
Ossetian
0.00
0.7401
54.4
Finnish
0.00
0.7398
54.2
Kurds-IQ
0.00
0.7391
53.4
Chechen
0.00
0.7389
53.1
Tajik_Simons
0.00
0.7386
52.8
Turkish
0.00
0.7386
52.8
Adygei
0.00
0.7384
52.6
Kalash
0.00
0.7380
52.2
Brahui
0.00
0.7377
51.9
Balochi
0.00
0.7377
51.8
Estonian
0.00
0.7376
51.8
Abkhasian
0.00
0.7372
51.4
Iranian
0.00
0.7370
51.2
Lezgin
0.00
0.7368
50.9
Hungarian
0.00
0.7366
50.7
Bulgarian
0.00
0.7364
50.5
Papuan
0.00
0.7364
50.5
Polish
0.00
0.7361
50.2
Czech
0.00
0.7360
50.1
Orcadian
0.00
0.7360
50.0
Makrani
0.00
0.7353
49.4
Spanish
0.00
0.7349
49.0
Armenian
0.00
0.7348
48.8
Greek
0.00
0.7347
48.7
English
0.00
0.7346
48.6
French
0.00
0.7345
48.5
Georgian
0.00
0.7345
48.5
Albanian
0.00
0.7344
48.4
Basque
0.00
0.7341
48.0
Jew_Iraqi
0.00
0.7336
47.5
Druze
0.00
0.7331
47.1
Sardinian
0.00
0.7327
46.6
Jew_Yemenite
0.00
0.7308
44.6
BedouinB
0.00
0.7303
44.1
Jordanian
0.00
0.7300
43.8
Saharawi
0.00
0.7265
40.0
Mozabite
0.00
0.7264
39.9
Luhya
0.00
0.7014
13.5
Esan
0.00
0.6998
11.8
Mbuti
0.00
0.6926
4.2
Ju_hoan_North
0.00
0.6901
1.5
Khomani_San
0.00
0.6887
0.0
</tbody>
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Can you run IBS with only one Mari sample please or there need to be more samples?
Interesting, but at least they are closer to Turkics of Central Asia and Siberia, so it still a bit similar to what G25 shows.
People would get their knickers in a twist when people would compare afghans with their iranic Kin like Kurds , compared to populations east of the Indus . So they would.pull.out some bs oracle list which showed some western shifted NW south Asians to afghans and pamiris . Based on that , they would conclude that afghans should be grouped with Indians . Ffs . Go to anthrogenica , and this is what they low-key put out .
That’s pretty absurd! Iranics such as Afghan Tajiks and Pashtuns and Brahui and Baloch are genetically significantly closer to other Iranics like Kurds than Indics using one to one comparison. Not to say there’s some Pak Pashtuns closer to Punjabis than Kurds or some admixed Baloch but that’s the exception rather than the rule
Komintasavalta
11-28-2021, 05:49 PM
There's 4 Mari samples in Karafet et al. 2018: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE73996.
Which datasets are you basing it on and how many overlapping snps.
I forgot how many SNPs my old f2 run had, and I forgot if I did LD pruning or if I used `maxmiss=1`, but it only included samples from 1240K+HO. I now finished another f2 run that used all 593,124 autosomal SNPs from 1240K+HO, but the populations were in the same relative order:
$ curl -L 'https://drive.google.com/uc?export=download&id=1fncwNa4JeBpzlXfkDmRJHbsYNR7NvqpG'|awk -F, 'NR==1{for(i=2;i<=NF;i++)if($i==x)break;next}$1!=x{print$i,$1}' x=Mansi -|sort -n|grep -En 'Pathan|Hazara|Finnish|Tajik$'
19:0.005876 Hazara
39:0.0081431 Tajik
52:0.0096319 Pathan
53:0.0098501 Finnish
There's 4 Mari samples in Karafet et al. 2018: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE73996.
I forgot how many SNPs my old f2 run had, and I forgot if I did LD pruning or if I used `maxmiss=1`, but it only included samples from 1240K+HO. I now finished another f2 run that used all 593,124 autosomal SNPs from 1240K+HO, but the populations were in the same relative order:
$ curl -L 'https://drive.google.com/uc?export=download&id=1fncwNa4JeBpzlXfkDmRJHbsYNR7NvqpG'|awk -F, 'NR==1{for(i=2;i<=NF;i++)if($i==x)break;next}$1!=x{print$i,$1}' x=Mansi -|sort -n|grep -En 'Pathan|Hazara|Finnish|Tajik$'
19:0.005876 Hazara
39:0.0081431 Tajik
52:0.0096319 Pathan
53:0.0098501 Finnish
There’s no clearly wrong or right answer. It’s close. It comes down to the SNPs and samples used. I don’t have the HO dataset. Try seeing what IBS gives you using the same samples
Avicenna
11-28-2021, 06:22 PM
That’s pretty absurd! Iranics such as Afghan Tajiks and Pashtuns and Brahui and Baloch are genetically significantly closer to other Iranics like Kurds than Indics using one to one comparison. Not to say there’s some Pak Pashtuns closer to Punjabis than Kurds or some admixed Baloch but that’s the exception rather than the rule
That could reflect the idea that admixture between pashtuns and non pashtuns have occurred within modern day Pakistan , and the fact that being pashtun in Pakistan is mainly focused on ethno linguistic affinity .
Avicenna
11-28-2021, 06:32 PM
That’s pretty absurd! Iranics such as Afghan Tajiks and Pashtuns and Brahui and Baloch are genetically significantly closer to other Iranics like Kurds than Indics using one to one comparison. Not to say there’s some Pak Pashtuns closer to Punjabis than Kurds or some admixed Baloch but that’s the exception rather than the rule
That could reflect the idea that admixture between pashtuns and non pashtuns have occurred within modern day Pakistan , and the fact that being pashtun in Pakistan is mainly focused on ethno linguistic affinity .
Zanzibar
11-29-2021, 04:27 PM
Yes it’s showing distance to Even of 0.010 but your G25 also compared to Euros vs W/S/C Asians. Have someone do both comparisons at same time using f2 for reliability and accuracy.
I’ll post the IBS you want in a minute
Sorry. Here is f2 distance for Japanese:
.00055 Korean
.00131 Mongola
.00161 Xibo
.00170 Yugur
.00172 Han
.00191 Tujia
.00216 Tu
.00226 Dungan
.00233 Daur
.00236 Dongxiang
.00267 Bonan
.00280 Hezhen
.00295 Salar
.00299 Yi
.00314 Qiang
.00320 Dong
.00333 Mongol
.00334 Miao
.00341 Naxi
.00341 Tibetan
.00343 Burmese
.00347 Oroqen
.00349 Vietnamese
.00357 Kinh
.00357 Zhuang
.00397 Mulam
.00399 She
.00402 Kalmyk
.00425 Tagalog
.00435 Magar
.00445 Maonan
.00448 Buryat
.00453 Khamnegan
.00457 Evenk_FarEast
.00466 Gurung
.00472 Dai
.00480 Nanai
.00484 Gelao
.00503 Tamang
.00506 Li
.00511 Sherpa
.00513 Negidal
.00522 Cambodian
.00533 Ulchi
.00546 Kazakh_China
.00560 Malay
.00562 Kyrgyz_Kyrgyzstan
.00563 Kyrgyz_China
.00567 Rai
.00583 Tuvinian
.00606 Thai
.00608 Kyrgyz_Tajikistan
.00623 Visayan
.00634 Altaian
.00653 Ilocano
.00653 Kazakh
.00704 Dolgan
.00742 China_Lahu
.00746 Tharu
.00751 Khakass_Kachin
.00752 Yakut
.00760 Tibetan_Yunnan
.00794 Newar
.00803 Uyghur
.00808 Even
.00818 Khakass
.00819 Dusun
.00822 Karakalpak
.00885 Ami
.00885 Hazara
.00887 Nogai_Astrakhan
.00889 Nivh
.00911 Yukagir_Tundra
.00966 Murut
.00981 Nogai_Stavropol
.01043 Todzin
.01044 Evenk_Transbaikal
.01138 Tatar_Siberian
.01151 Kusunda
.01195 Tubalar
.01200 Kankanaey
.01216 Shor_Mountain
.01224 Yukagir_Forest
.01276 Uzbek
.01289 Tofalar
.01349 Altaian_Chelkan
.01379 Enets
.01412 Selkup
.01428 Bahun
.01469 Turkmen
.01499 Tatar_Siberian_Zabolotniye
.01513 Atayal
.01514 Ket
.01514 Shor_Khakassia
.01524 Mansi
.01534 Nganasan
.01538 Chukchi
.01566 Bashkir
.01617 Bengali
.01648 Eskimo_ChaplinSireniki
.01685 Tlingit
.01732 Koryak
.01762 Nogai_Karachay_Cherkessia
.01852 Itelmen
.01920 Aleut
.01930 Burusho
.02019 Tatar_Kazan
.02029 Punjabi
.02034 Chuvash
.02036 GujaratiC
.02043 GujaratiB
.02080 Eskimo_Naukan
.02094 GujaratiD
.02096 Udmurt
.02097 Tajik
.02154 Besermyan
.02163 GujaratiA
.02188 Sindhi_Pakistan
.02210 Jew_Cochin
.02230 Pathan
.02262 Tatar_Mishar
.02459 Abazin
.02471 Balochi
.02486 Mayan
.02492 Kabardinian
.02514 Brahui
.02547 Quechua
.02558 Balkar
.02565 Circassian
.02574 Makrani
.02580 Zapotec
.02583 Iranian_Bandari
.02584 Turkish
.02586 Chukchi1
.02587 Bolivian
.02591 Russian_Archangelsk_Leshukonsky
.02599 Russian_Archangelsk_Krasnoborsky
.02600 Azeri
.02621 Kumyk
.02635 Ossetian
.02654 Karachai
.02655 Mordovian
.02661 Russian_Archangelsk_Pinezhsky
.02666 Iranian
.02666 Turkish_Balikesir
.02708 Adygei
.02726 Mixtec
.02738 Veps
.02740 Karelian
.02749 Finnish
.02775 Yemeni_Desert2
.02780 Ingushian
.02801 Lezgin
.02818 Chechen
.02819 Yemeni
.02821 Russian
.02837 Tabasaran
.02852 Jordanian
.02876 Ezid
.02888 Egyptian
.02896 Avar
.02897 Lebanese_Muslim
.02902 Lebanese
.02907 Syrian
.02908 Gagauz
.02915 BedouinA
.02920 Abkhasian
.02926 Bulgarian
.02941 Hungarian
.02944 Kaitag
.02945 Armenian
.02948 Lak
.02948 Ukrainian
.02950 Tunisian
.02958 Romanian
.02962 Belarusian
.02965 Kalash
.02967 Estonian
.02969 Kurd
.02969 Palestinian
.02972 Libyan
.02976 Sicilian
.02980 Albanian
.02982 Greek
.02982 Moldavian
.02987 Ukrainian_North
.02990 Jew_Ashkenazi
.02993 Czech
.02995 Croatian
.02996 Italian_South
.02998 Georgian
.02999 Assyrian
.02999 Jew_Turkish
.03009 French
.03012 Moroccan
.03018 Darginian
.03019 Lebanese_Christian
.03023 Maltese
.03032 Jew_Moroccan
.03033 Cypriot
.03036 Spanish
.03040 Norwegian
.03051 Armenian_Hemsheni
.03053 Canary_Islander
.03059 Italian_North
.03060 Jew_Georgian
.03061 Jew_Iranian
.03065 Yemeni_Highlands
.03069 English
.03072 Scottish
.03076 Jew_Iraqi
.03076 Yemeni_Northwest
.03079 Yemeni_Highlands_Raymah
.03081 Icelandic
.03087 Orcadian
.03099 Druze
.03099 Mixe
.03102 Lithuanian
.03173 Jew_Libyan
.03175 Spanish_North
.03189 Saudi
.03192 Jew_Tunisian
.03230 Jew_Yemenite
.03248 Kubachinian
.03248 Piapoco
.03254 Eritrea
.03269 Basque
.03297 Mozabite
.03305 Yemeni_Desert
.03313 Algerian
.03318 Pima
.03328 Jew_Ethiopian
.03362 Saharawi
.03369 Sardinian
.03531 BedouinB
.03620 Nasioi
.03708 Somali
.03929 Datog
.04183 Masai
.04327 Karitiana
.04433 Kikuyu
.04522 Australian
.04554 AA
.04730 Papuan
.04859 Surui
.05135 Luhya
.05242 Luo
.05255 Gambian
.05285 BantuKenya
.05467 Malawi_Tumbuka
.05508 Mandenka
.05517 Malawi_Yao
.05518 Malawi_Chewa
.05523 Yoruba
.05526 Malawi_Ngoni
.05541 Mende
.05591 Esan
.05649 BantuSA
.05712 Namibia_Bantu_Herero
.06405 Khomani
.06411 Biaka
.06794 Hadza1
.07333 Mbuti
.08088 Ju_hoan_North
f2 distance to Korean:
.00012 Mongola
.00040 Han
.00052 Yugur
.00054 Tujia
.00055 Japanese
.00062 Xibo
.00089 Tu
.00104 Dungan
.00126 Dongxiang
.00129 Bonan
.00129 Daur
.00168 Salar
.00177 Yi
.00178 Qiang
.00188 Hezhen
.00204 Miao
.00207 Tibetan
.00211 Dong
.00212 Naxi
.00225 Kinh
.00234 Zhuang
.00237 Burmese
.00238 Mongol
.00240 Vietnamese
.00243 Oroqen
.00271 She
.00290 Mulam
.00308 Kalmyk
.00331 Tagalog
.00333 Magar
.00334 Gurung
.00337 Maonan
.00360 Khamnegan
.00363 Dai
.00364 Buryat
.00366 Gelao
.00386 Sherpa
.00389 Tamang
.00393 Li
.00396 Evenk_FarEast
.00405 Nanai
.00423 Rai
.00426 Cambodian
.00437 Negidal
.00464 Kyrgyz_Kyrgyzstan
.00468 Kazakh_China
.00485 Malay
.00491 Kyrgyz_China
.00493 Ulchi
.00496 Tuvinian
.00519 Thai
.00530 Visayan
.00535 Kyrgyz_Tajikistan
.00558 Altaian
.00579 Ilocano
.00584 Kazakh
.00607 Dolgan
.00611 China_Lahu
.00613 Tibetan_Yunnan
.00665 Yakut
.00670 Tharu
.00671 Khakass_Kachin
.00721 Newar
.00724 Dusun
.00728 Uyghur
.00735 Even
.00737 Khakass
.00756 Karakalpak
.00810 Ami
.00810 Nogai_Astrakhan
.00815 Hazara
.00846 Yukagir_Tundra
.00880 Murut
.00919 Nivh
.00921 Nogai_Stavropol
.00973 Evenk_Transbaikal
.00987 Todzin
.01062 Kusunda
.01092 Tatar_Siberian
.01097 Kankanaey
.01132 Tubalar
.01147 Shor_Mountain
.01158 Yukagir_Forest
.01201 Tofalar
.01225 Uzbek
.01278 Altaian_Chelkan
.01302 Enets
.01342 Selkup
.01387 Atayal
.01398 Bahun
.01420 Tatar_Siberian_Zabolotniye
.01421 Turkmen
.01431 Ket
.01457 Mansi
.01462 Nganasan
.01464 Shor_Khakassia
.01481 Chukchi
.01517 Bashkir
.01592 Bengali
.01599 Eskimo_ChaplinSireniki
.01640 Tlingit
.01692 Koryak
.01713 Nogai_Karachay_Cherkessia
.01814 Itelmen
.01893 Burusho
.01897 Aleut
.01977 Tatar_Kazan
.02008 Chuvash
.02024 Eskimo_Naukan
.02027 Punjabi
.02033 GujaratiB
.02044 GujaratiC
.02060 Udmurt
.02065 Tajik
.02079 GujaratiD
.02106 GujaratiA
.02136 Besermyan
.02178 Sindhi_Pakistan
.02185 Jew_Cochin
.02212 Pathan
.02230 Tatar_Mishar
.02437 Abazin
.02438 Mayan
.02452 Balochi
.02462 Kabardinian
.02485 Quechua
.02504 Brahui
.02538 Balkar
.02540 Bolivian
.02545 Circassian
.02550 Russian_Archangelsk_Leshukonsky
.02551 Zapotec
.02559 Makrani
.02561 Turkish
.02562 Chukchi1
.02566 Azeri
.02573 Iranian_Bandari
.02575 Kumyk
.02581 Russian_Archangelsk_Krasnoborsky
.02611 Ossetian
.02627 Karachai
.02631 Russian_Archangelsk_Pinezhsky
.02634 Mordovian
.02638 Turkish_Balikesir
.02641 Iranian
.02679 Mixtec
.02682 Adygei
.02700 Karelian
.02704 Veps
.02719 Finnish
.02735 Ingushian
.02746 Yemeni_Desert2
.02779 Lezgin
.02785 Chechen
.02794 Russian
.02815 Yemeni
.02829 Tabasaran
.02830 Jordanian
.02855 Egyptian
.02857 Ezid
.02859 Lebanese
.02874 Gagauz
.02880 Lebanese_Muslim
.02881 Avar
.02886 BedouinA
.02890 Abkhasian
.02909 Syrian
.02912 Hungarian
.02914 Bulgarian
.02917 Ukrainian
.02921 Tunisian
.02922 Armenian
.02922 Romanian
.02928 Kalash
.02935 Lak
.02936 Estonian
.02938 Belarusian
.02938 Libyan
.02939 Kaitag
.02939 Palestinian
.02942 Ukrainian_North
.02957 Jew_Turkish
.02962 Assyrian
.02964 Greek
.02966 Albanian
.02966 Moldavian
.02966 Sicilian
.02967 Kurd
.02970 Czech
.02971 Italian_South
.02973 Jew_Ashkenazi
.02980 Georgian
.02985 French
.02988 Croatian
.02990 Maltese
.02994 Moroccan
.02999 Jew_Moroccan
.03003 Darginian
.03003 Lebanese_Christian
.03008 Cypriot
.03013 Spanish
.03021 Canary_Islander
.03024 Italian_North
.03027 Armenian_Hemsheni
.03029 Norwegian
.03032 Jew_Georgian
.03034 Jew_Iranian
.03037 Yemeni_Highlands
.03038 Yemeni_Highlands_Raymah
.03047 Yemeni_Northwest
.03053 English
.03054 Scottish
.03066 Druze
.03067 Orcadian
.03068 Icelandic
.03069 Jew_Iraqi
.03078 Mixe
.03079 Lithuanian
.03152 Jew_Libyan
.03156 Saudi
.03161 Jew_Tunisian
.03166 Spanish_North
.03188 Piapoco
.03189 Jew_Yemenite
.03226 Eritrea
.03243 Basque
.03252 Kubachinian
.03266 Mozabite
.03270 Yemeni_Desert
.03291 Pima
.03301 Algerian
.03305 Jew_Ethiopian
.03346 Saharawi
.03348 Sardinian
.03489 BedouinB
.03612 Nasioi
.03686 Somali
.03907 Datog
.04160 Masai
.04291 Karitiana
.04406 Kikuyu
.04531 Australian
.04534 AA
.04747 Papuan
.04808 Surui
.05098 Luhya
.05215 Luo
.05258 BantuKenya
.05268 Gambian
.05447 Malawi_Tumbuka
.05486 Mandenka
.05500 Malawi_Chewa
.05502 Malawi_Yao
.05505 Malawi_Ngoni
.05507 Yoruba
.05519 Mende
.05556 Esan
.05617 BantuSA
.05722 Namibia_Bantu_Herero
.06366 Khomani
.06370 Biaka
.06767 Hadza1
.07295 Mbuti
.08052 Ju_hoan_North
Compare to Euros....
f2 distance to English:
.000205 French
.000318 Cordona_German
.000478 Hungarian
.000513 Cordona_British
.000560 Norwegian
.000651 Czech
.000773 Bulgarian
.000778 Spanish
.000831 Icelandic
.000940 Croatian
.000946 Russian_Tver
.000984 Gagauz
.001045 Ukrainian
.001095 Russian_Orel
.001106 Russian_Ryazan
.001148 Orcadian
.001161 Italian_North
.001172 Russian_Kursk
.001311 Russian_Belgorod
.001397 Ukrainian_North
.001455 Belarusian
.001474 Russian_Yaroslavl
.001525 Romanian
.001587 Scottish
.001592 Russian_Smolensk
.001621 Estonian
.001667 Greek
.001689 Albanian
.001696 Russian_Archangelsk_Krasnoborsky
.001709 Russian_Pskov
.001720 Russian_Kaluga
.001732 Russian_Vologda
.001777 Cordona_Italian
.001799 Mordovian
.001814 Moldavian
.001919 Italian_South
.001937 Sicilian
.001945 Spanish_North
.002101 Lithuanian
.002156 Cordona_Mordva
.002188 Finnish
.002276 Canary_Islander
.002565 Tatar_Kazan
.002699 Tatar_Mishar
.002771 Basque
.002900 Turkish
.002906 Kabardinian
.002939 Karelian
.003011 Maltese
.003013 Kumyk
.003075 Jew_Turkish
.003126 Jew_Ashkenazi
.003143 Cordona_Turk
.003153 Abazin
.003299 Circassian
.003419 Lezgin
.003582 Balkar
.003619 Cypriot
.003650 Veps
.003655 Adygei
.003714 Azeri
.003787 Russian_Archangelsk_Pinezhsky
.003901 Armenian
.003909 Jew_Moroccan
.003969 Ossetian
.003991 Sardinian
.003999 Nogai_Karachay_Cherkessia
.004025 Lebanese_Muslim
.004038 Chuvash
.004067 Chechen
.004107 Tajik
.004165 Lebanese_Christian
.004172 Tabasaran
.004273 Iranian
.004348 Cordona_Iranian
.004478 Georgian
.004505 Lebanese
.004594 Kaitag
.004674 Abkhasian
.004721 Russian_Archangelsk_Leshukonsky
.004740 Ingushian
.004950 Armenian_Hemsheni
.004981 Jordanian
.005032 Karachai
.005049 Syrian
.005072 Assyrian
.005075 Ezid
.005095 Cordona_Avar
.005310 Bashkir
.005341 Avar
.005441 Lak
.005589 Druze
.005693 Palestinian
.005696 Jew_Iraqi
.005815 Cordona_Turkmen
.005918 BedouinA
.006033 Pathan
.006085 Besermyan
.006121 Jew_Tunisian
.006133 Jew_Iranian
.006151 Iranian_Bandari
.006157 Jew_Libyan
.006279 Jew_Georgian
.006283 Darginian
.006457 Egyptian
.006573 Cordona_Tajik
.006664 Kurd
.006715 Turkmen
.006780 Yemeni
.006840 Cordona_Egyptian
.006901 Uzbek
.007101 Cordona_Mari
.007172 Balochi
.007247 Udmurt
.007357 Makrani
.007405 Libyan
.007572 Cordona_Komi
.007674 Brahui
.007765 GujaratiA
.007769 Tunisian
.007774 Sindhi_Pakistan
.007879 Yemeni_Northwest
.007888 Yemeni_Highlands
.007913 Saudi
.008154 Turkish_Balikesir
.008374 Yukagir_Forest
.008753 Burusho
.008784 Nogai_Stavropol
.008788 Jew_Yemenite
.008875 Tatar_Siberian
.008900 Yemeni_Highlands_Raymah
.008990 GujaratiB
.008993 Kubachinian
.009322 Moroccan
.009854 Jew_Cochin
.010140 Yemeni_Desert2
.010172 Aleut
.010750 Uyghur
.010862 Bahun
.010900 Nogai_Astrakhan
.011061 Karakalpak
.011171 GujaratiC
.011288 Mozabite
.011600 Yemeni_Desert
.011958 Punjabi
.012395 Hazara
.012556 Cordona_Uygur
.012684 Algerian
.012877 Cordona_Kazakh
.013022 BedouinB
.013022 Saharawi
.013185 Bengali
.013408 Tlingit
.013669 GujaratiD
.013898 Cordona_Sri_Lankan
.014181 Cordona_Indian
.014300 Kazakh
.015213 Kalash
.015271 Tatar_Siberian_Zabolotniye
.015381 Kyrgyz_Tajikistan
.015609 Mansi
.016026 Cordona_Khant
.016105 Kyrgyz_Kyrgyzstan
.016533 Kyrgyz_China
.017077 Khakass
.017209 Altaian_Chelkan
.017444 Cordona_Teleut
.017567 Eritrea
.017785 Even
.018181 Tubalar
.018205 Newar
.018853 Shor_Mountain
.019073 Kazakh_China
.019351 Tharu
.020031 Jew_Ethiopian
.020219 Altaian
.020585 Cordona_Altai_Kizhi
.021067 Cordona_Ket
.021440 Khakass_Kachin
.022266 Selkup
.022467 Cordona_Tundra_Nentsi
.022869 Kalmyk
.023152 Shor_Khakassia
.023634 Cordona_Selkup
.024327 Evenk_FarEast
.024863 Mongol
.025025 Tuvinian
.025341 Salar
.025495 Ket
.025593 Cordona_Mongol
.025750 Dongxiang
.025966 Cordona_Buryat
.026133 Burmese
.026466 Cordona_Dolgan
.026516 Buryat
.026618 Dungan
.027293 Somali
.027525 Tamang
.027630 Khamnegan
.027941 Magar
.028140 Dolgan
.028167 Enets
.029072 Cordona_Forest_Nentsi
.029325 Malay
.029479 Tu
.029540 Bonan
.029976 Cordona_Even
.030276 Cambodian
.030287 Yakut
.030493 Gurung
.030592 Thai
.030654 Yugur
.030708 Mongola
.031108 Cordona_Yakut
.031154 Kusunda
.031466 Xibo
.031703 Daur
.031973 Tibetan
.032061 Tagalog
.032527 Datog
.032773 Cordona_Tibetan
.032824 Todzin
.033127 Oroqen
.033470 Cordona_Indonesia_Java
.033676 Tofalar
.033725 Yi
.033823 Hezhen
.033855 Rai
.033870 Cordona_Manchu
.034089 Naxi
.034200 Cordona_Vietnamese
.034320 Kinh
.034391 Qiang
.034392 Vietnamese
.034402 Sherpa
.034404 Han
.034583 Korean
.034794 Tujia
.034957 Visayan
.035085 Yukagir_Tundra
.035129 Cordona_Korean
.035146 Japanese
.035414 Cordona_Han_South
.035619 Zhuang
.035765 Miao
.035805 Cordona_Koryak
.035854 Dong
.035976 Mulam
.036158 Dai
.036420 Nanai
.036467 Gelao
.036732 Maonan
.036766 Evenk_Transbaikal
.036854 Ulchi
.036868 Masai
.036884 Li
.036949 Negidal
.037413 She
.037749 Cordona_Evenk
.038146 Ilocano
.038832 Dusun
.038952 Tibetan_Yunnan
.039156 China_Lahu
.039578 Quechua
.039947 Chukchi
.040182 Eskimo_ChaplinSireniki
.040455 Mayan
.040529 Kikuyu
.041198 Murut
.041280 AA
.041382 Cordona_Nganasan
.042294 Bolivian
.042535 Ami
.042698 Nivh
.043002 Nganasan
.043103 Cordona_Yukagir
.043466 Koryak
.044013 Zapotec
.044643 Eskimo_Naukan
.045156 Itelmen
.045726 Mixtec
.046227 Kankanaey
.050085 Atayal
.052193 Luhya
.052747 Mixe
.052851 Luo
.053333 Chukchi1
.053857 Pima
.054108 BantuKenya
.054649 Piapoco
.055004 Cordona_Dinka
.055258 Gambian
.055333 Nasioi
.056297 Malawi_Tumbuka
.056375 Malawi_Ngoni
.056572 Mandenka
.056752 Malawi_Yao
.056802 Malawi_Chewa
.056932 Yoruba
.057086 Mende
.057665 Cordona_PNG_Highland
.057666 BantuSA_Ovambo
.057839 Esan
.058946 BantuSA
.059151 Namibia_Bantu_Herero
.062537 Australian
.063758 Khomani
.065939 Papuan
.067706 Biaka
.069471 Karitiana
.071497 Hadza1
.075917 Surui
.078496 Mbuti
.084350 Ju_hoan_North
f2 distance to Norwegian:
000511 Cordona_German
.000560 English
.000742 French
.000780 Hungarian
.000835 Czech
.000855 Cordona_British
.000917 Icelandic
.001073 Bulgarian
.001140 Russian_Tver
.001233 Croatian
.001274 Russian_Kursk
.001275 Ukrainian
.001378 Spanish
.001394 Orcadian
.001412 Russian_Ryazan
.001450 Russian_Orel
.001477 Russian_Belgorod
.001501 Ukrainian_North
.001535 Russian_Archangelsk_Krasnoborsky
.001538 Estonian
.001588 Russian_Pskov
.001590 Gagauz
.001617 Russian_Smolensk
.001640 Belarusian
.001649 Russian_Kaluga
.001703 Russian_Yaroslavl
.001718 Russian_Vologda
.001806 Italian_North
.001999 Finnish
.002013 Romanian
.002015 Mordovian
.002130 Scottish
.002141 Lithuanian
.002222 Albanian
.002284 Moldavian
.002408 Cordona_Italian
.002429 Greek
.002463 Sicilian
.002566 Spanish_North
.002583 Cordona_Mordva
.002654 Italian_South
.002677 Tatar_Mishar
.002688 Tatar_Kazan
.002823 Karelian
.003039 Canary_Islander
.003367 Basque
.003398 Kumyk
.003453 Jew_Turkish
.003579 Kabardinian
.003605 Abazin
.003607 Turkish
.003611 Veps
.003626 Cordona_Turk
.003659 Maltese
.003899 Russian_Archangelsk_Pinezhsky
.003922 Jew_Ashkenazi
.003993 Lezgin
.004080 Circassian
.004094 Balkar
.004213 Adygei
.004301 Russian_Archangelsk_Leshukonsky
.004305 Chuvash
.004449 Ossetian
.004486 Tajik
.004501 Nogai_Karachay_Cherkessia
.004619 Azeri
.004647 Tabasaran
.004686 Cypriot
.004739 Chechen
.004776 Jew_Moroccan
.004791 Lebanese_Muslim
.004879 Armenian
.004916 Iranian
.004936 Sardinian
.004973 Cordona_Iranian
.005002 Lebanese_Christian
.005043 Ingushian
.005062 Kaitag
.005243 Georgian
.005362 Cordona_Avar
.005391 Bashkir
.005423 Abkhasian
.005425 Lebanese
.005657 Karachai
.005658 Ezid
.005716 Jordanian
.005731 Avar
.005733 Lak
.005804 Assyrian
.005978 Armenian_Hemsheni
.006063 Syrian
.006162 Druze
.006222 Cordona_Turkmen
.006324 Besermyan
.006448 Cordona_Tajik
.006480 Pathan
.006569 Palestinian
.006730 Jew_Iraqi
.006736 Darginian
.006798 BedouinA
.006941 Turkmen
.006980 Iranian_Bandari
.007013 Jew_Iranian
.007037 Jew_Libyan
.007055 Cordona_Komi
.007073 Jew_Georgian
.007091 Uzbek
.007169 Egyptian
.007187 Jew_Tunisian
.007208 Udmurt
.007304 Kurd
.007448 Cordona_Mari
.007532 Balochi
.007712 GujaratiA
.007712 Makrani
.007713 Yemeni
.007865 Cordona_Egyptian
.008130 Brahui
.008193 Sindhi_Pakistan
.008352 Turkish_Balikesir
.008417 Libyan
.008647 Yukagir_Forest
.008703 Yemeni_Northwest
.008791 Yemeni_Highlands
.008805 Nogai_Stavropol
.008832 Tunisian
.008918 Burusho
.008940 Saudi
.009070 Tatar_Siberian
.009112 Yemeni_Highlands_Raymah
.009268 Kubachinian
.009785 GujaratiB
.009846 Jew_Yemenite
.009847 Aleut
.010173 Jew_Cochin
.010253 Moroccan
.010656 Bahun
.010792 Nogai_Astrakhan
.010912 Karakalpak
.010931 Yemeni_Desert2
.010977 Uyghur
.011658 GujaratiC
.012234 Mozabite
.012312 Punjabi
.012372 Yemeni_Desert
.012463 Hazara
.012626 Cordona_Uygur
.012874 Cordona_Kazakh
.013079 Tlingit
.013278 Bengali
.013604 Algerian
.013868 BedouinB
.014085 GujaratiD
.014279 Saharawi
.014292 Kazakh
.014325 Cordona_Sri_Lankan
.014399 Cordona_Indian
.015177 Kyrgyz_Tajikistan
.015226 Tatar_Siberian_Zabolotniye
.015517 Mansi
.015673 Kalash
.015742 Cordona_Khant
.016083 Kyrgyz_Kyrgyzstan
.016359 Kyrgyz_China
.016868 Khakass
.017244 Altaian_Chelkan
.017332 Even
.017441 Cordona_Teleut
.017964 Tubalar
.018544 Eritrea
.018718 Newar
.018752 Shor_Mountain
.019072 Kazakh_China
.019317 Tharu
.020229 Altaian
.020405 Cordona_Altai_Kizhi
.020680 Cordona_Ket
.020933 Khakass_Kachin
.021252 Jew_Ethiopian
.021802 Selkup
.022054 Cordona_Tundra_Nentsi
.022878 Kalmyk
.022998 Shor_Khakassia
.023237 Cordona_Selkup
.024322 Evenk_FarEast
.024811 Mongol
.024873 Tuvinian
.025121 Ket
.025291 Salar
.025300 Cordona_Mongol
.025689 Dongxiang
.025878 Cordona_Buryat
.026122 Burmese
.026331 Buryat
.026420 Cordona_Dolgan
.026626 Dungan
.027700 Khamnegan
.027806 Magar
.027808 Tamang
.027831 Dolgan
.028161 Enets
.028442 Somali
.028575 Cordona_Forest_Nentsi
.029287 Cordona_Even
.029334 Tu
.029407 Malay
.029602 Bonan
.030007 Yakut
.030380 Thai
.030395 Cambodian
.030516 Yugur
.030581 Mongola
.030842 Cordona_Yakut
.030848 Gurung
.031175 Kusunda
.031475 Xibo
.031521 Daur
.031821 Tibetan
.031875 Tagalog
.032237 Todzin
.032749 Cordona_Tibetan
.032777 Oroqen
.033265 Hezhen
.033536 Tofalar
.033561 Cordona_Indonesia_Java
.033584 Yi
.033752 Cordona_Manchu
.033835 Rai
.033950 Datog
.034114 Kinh
.034128 Sherpa
.034174 Qiang
.034242 Han
.034245 Korean
.034275 Naxi
.034344 Vietnamese
.034359 Cordona_Vietnamese
.034620 Tujia
.034645 Visayan
.034904 Yukagir_Tundra
.034962 Japanese
.034970 Cordona_Korean
.035294 Cordona_Han_South
.035668 Miao
.035703 Zhuang
.035711 Dong
.035813 Mulam
.035915 Cordona_Koryak
.036160 Dai
.036299 Negidal
.036303 Evenk_Transbaikal
.036382 Gelao
.036421 Nanai
.036451 Ulchi
.036492 Maonan
.036857 Li
.037189 Cordona_Evenk
.037555 She
.038046 Masai
.038057 Ilocano
.038405 Dusun
.038977 Tibetan_Yunnan
.039204 China_Lahu
.039561 Quechua
.039729 Chukchi
.040070 Eskimo_ChaplinSireniki
.040271 Mayan
.040612 Cordona_Nganasan
.040957 Murut
.041775 Kikuyu
.041984 Bolivian
.042200 Ami
.042251 AA
.042330 Nivh
.042415 Nganasan
.042813 Cordona_Yukagir
.043247 Koryak
.043836 Zapotec
.044439 Eskimo_Naukan
.044654 Itelmen
.045500 Mixtec
.046108 Kankanaey
.050027 Atayal
.052446 Mixe
.053173 Chukchi1
.053452 Pima
.053519 Luhya
.054119 Piapoco
.054176 Luo
.055253 BantuKenya
.055674 Nasioi
.056035 Cordona_Dinka
.056302 Gambian
.057230 Malawi_Ngoni
.057471 Malawi_Tumbuka
.057832 Mandenka
.057957 Cordona_PNG_Highland
.057995 Malawi_Yao
.058317 Malawi_Chewa
.058320 Yoruba
.058331 Mende
.058776 BantuSA_Ovambo
.059151 Esan
.060029 Namibia_Bantu_Herero
.060030 BantuSA
.062833 Australian
.064654 Khomani
.066425 Papuan
.068764 Karitiana
.068933 Biaka
.073164 Hadza1
.075393 Surui
.079528 Mbuti
.085457 Ju_hoan_North
f2 distance to Hungarian:
.000075 Czech
.000212 Bulgarian
.000225 Cordona_German
.000225 Russian_Tver
.000253 Russian_Kursk
.000263 Russian_Orel
.000378 Russian_Belgorod
.000389 Ukrainian_North
.000400 Ukrainian
.000403 French
.000444 Russian_Smolensk
.000464 Belarusian
.000478 English
.000518 Gagauz
.000536 Russian_Ryazan
.000546 Croatian
.000604 Russian_Yaroslavl
.000610 Cordona_British
.000702 Russian_Pskov
.000739 Russian_Kaluga
.000780 Norwegian
.000823 Spanish
.000906 Italian_North
.000913 Russian_Archangelsk_Krasnoborsky
.000920 Russian_Vologda
.000927 Estonian
.000983 Mordovian
.000988 Romanian
.001006 Greek
.001024 Albanian
.001132 Cordona_Mordva
.001174 Lithuanian
.001175 Icelandic
.001221 Moldavian
.001288 Cordona_Italian
.001414 Orcadian
.001490 Sicilian
.001505 Finnish
.001609 Italian_South
.001939 Tatar_Mishar
.001943 Tatar_Kazan
.001964 Spanish_North
.002192 Scottish
.002208 Cordona_Turk
.002227 Turkish
.002239 Karelian
.002261 Canary_Islander
.002294 Kabardinian
.002332 Kumyk
.002477 Jew_Turkish
.002493 Abazin
.002515 Maltese
.002748 Jew_Ashkenazi
.002751 Circassian
.002803 Cypriot
.002932 Basque
.002944 Balkar
.002947 Adygei
.002968 Lezgin
.003173 Lebanese_Muslim
.003195 Armenian
.003236 Veps
.003256 Russian_Archangelsk_Pinezhsky
.003279 Azeri
.003310 Nogai_Karachay_Cherkessia
.003400 Chuvash
.003403 Lebanese_Christian
.003484 Ossetian
.003520 Chechen
.003548 Iranian
.003578 Tajik
.003642 Jew_Moroccan
.003703 Lebanese
.003740 Cordona_Iranian
.003815 Tabasaran
.003879 Russian_Archangelsk_Leshukonsky
.003940 Sardinian
.003983 Ingushian
.003999 Abkhasian
.004058 Georgian
.004175 Jordanian
.004321 Armenian_Hemsheni
.004354 Ezid
.004407 Kaitag
.004508 Assyrian
.004533 Syrian
.004537 Bashkir
.004554 Karachai
.004621 Cordona_Avar
.004818 Palestinian
.004826 Druze
.005022 Avar
.005037 Cordona_Turkmen
.005164 Lak
.005181 Jew_Iraqi
.005249 BedouinA
.005354 Jew_Iranian
.005494 Pathan
.005565 Iranian_Bandari
.005576 Egyptian
.005614 Jew_Georgian
.005633 Besermyan
.005687 Cordona_Tajik
.005723 Kurd
.005750 Jew_Tunisian
.005832 Jew_Libyan
.005887 Turkmen
.005922 Uzbek
.006067 Cordona_Egyptian
.006096 Darginian
.006356 Yemeni
.006421 Cordona_Komi
.006504 Udmurt
.006528 Cordona_Mari
.006543 Balochi
.006575 Makrani
.006726 Libyan
.006915 Yemeni_Northwest
.007093 Tunisian
.007104 Yemeni_Highlands
.007116 Brahui
.007149 Sindhi_Pakistan
.007155 GujaratiA
.007169 Saudi
.007182 Turkish_Balikesir
.007536 Yukagir_Forest
.007771 Yemeni_Highlands_Raymah
.007810 Nogai_Stavropol
.008010 Burusho
.008025 Jew_Yemenite
.008053 Tatar_Siberian
.008525 Kubachinian
.008641 GujaratiB
.008703 Moroccan
.009116 Aleut
.009169 Jew_Cochin
.009279 Yemeni_Desert2
.009793 Uyghur
.009905 Nogai_Astrakhan
.009925 Bahun
.009939 Karakalpak
.010555 GujaratiC
.010750 Yemeni_Desert
.010799 Mozabite
.011276 Hazara
.011498 Punjabi
.011537 Cordona_Uygur
.011713 Cordona_Kazakh
.011954 BedouinB
.012000 Algerian
.012364 Bengali
.012387 Tlingit
.012798 Saharawi
.013121 Kazakh
.013143 GujaratiD
.013148 Cordona_Sri_Lankan
.013435 Cordona_Indian
.014434 Tatar_Siberian_Zabolotniye
.014588 Mansi
.014625 Kyrgyz_Tajikistan
.014672 Kalash
.015065 Cordona_Khant
.015081 Kyrgyz_Kyrgyzstan
.015383 Kyrgyz_China
.016009 Khakass
.016307 Even
.016468 Cordona_Teleut
.016511 Eritrea
.016574 Altaian_Chelkan
.017139 Newar
.017529 Tubalar
.017560 Kazakh_China
.018074 Tharu
.018084 Shor_Mountain
.019019 Jew_Ethiopian
.019080 Altaian
.019412 Cordona_Altai_Kizhi
.020080 Cordona_Ket
.020086 Khakass_Kachin
.021163 Selkup
.021236 Cordona_Tundra_Nentsi
.021579 Kalmyk
.022212 Shor_Khakassia
.022638 Cordona_Selkup
.022730 Evenk_FarEast
.023516 Mongol
.023749 Tuvinian
.023958 Salar
.024114 Cordona_Mongol
.024407 Dongxiang
.024422 Cordona_Buryat
.024452 Ket
.024764 Burmese
.024968 Buryat
.025051 Cordona_Dolgan
.025375 Dungan
.026312 Tamang
.026348 Khamnegan
.026453 Magar
.026505 Dolgan
.026508 Somali
.027167 Enets
.027857 Cordona_Forest_Nentsi
.027932 Tu
.028155 Malay
.028244 Bonan
.028356 Cordona_Even
.028732 Yakut
.028973 Cambodian
.029110 Mongola
.029111 Thai
.029202 Yugur
.029301 Gurung
.029765 Cordona_Yakut
.029889 Kusunda
.029934 Xibo
.030276 Daur
.030410 Tibetan
.030766 Tagalog
.030930 Todzin
.031223 Cordona_Tibetan
.031461 Oroqen
.031989 Datog
.032226 Yi
.032227 Hezhen
.032278 Cordona_Indonesia_Java
.032375 Cordona_Manchu
.032388 Tofalar
.032516 Sherpa
.032554 Rai
.032625 Naxi
.032703 Kinh
.032736 Qiang
.032837 Korean
.032905 Han
.033050 Cordona_Vietnamese
.033182 Vietnamese
.033325 Tujia
.033383 Visayan
.033624 Japanese
.033692 Yukagir_Tundra
.033715 Cordona_Korean
.034010 Cordona_Han_South
.034232 Zhuang
.034243 Miao
.034257 Dong
.034579 Mulam
.034729 Cordona_Koryak
.034760 Dai
.034876 Nanai
.035040 Negidal
.035147 Maonan
.035150 Gelao
.035185 Evenk_Transbaikal
.035283 Ulchi
.035574 Li
.036045 Masai
.036059 She
.036245 Cordona_Evenk
.036916 Ilocano
.037463 Dusun
.037479 Tibetan_Yunnan
.037838 China_Lahu
.038776 Chukchi
.039144 Eskimo_ChaplinSireniki
.039175 Quechua
.039743 Cordona_Nganasan
.039831 Mayan
.039887 Murut
.039956 Kikuyu
.040644 AA
.040912 Ami
.040972 Nivh
.041404 Nganasan
.041441 Bolivian
.041456 Cordona_Yukagir
.042232 Koryak
.043390 Zapotec
.043415 Eskimo_Naukan
.043568 Itelmen
.044943 Kankanaey
.044969 Mixtec
.048724 Atayal
.051648 Luhya
.051938 Mixe
.052081 Chukchi1
.052140 Luo
.053175 Pima
.053446 BantuKenya
.054160 Cordona_Dinka
.054175 Piapoco
.054347 Nasioi
.054507 Gambian
.055524 Malawi_Ngoni
.055762 Malawi_Tumbuka
.056002 Malawi_Yao
.056022 Mandenka
.056271 Malawi_Chewa
.056291 Mende
.056314 Yoruba
.056728 Cordona_PNG_Highland
.056896 BantuSA_Ovambo
.056991 Esan
.058199 BantuSA
.058212 Namibia_Bantu_Herero
.061759 Australian
.062894 Khomani
.065071 Papuan
.067187 Biaka
.068490 Karitiana
.070847 Hadza1
.074741 Surui
.077878 Mbuti
.083395 Ju_hoan_North
f2 distance to Ukrainian:
-.000262 Russian_Belgorod
-.000128 Russian_Orel
-.000106 Russian_Kursk
-.000044 Russian_Tver
-.000022 Russian_Kaluga
.000014 Russian_Ryazan
.000065 Russian_Smolensk
.000103 Belarusian
.000207 Czech
.000292 Ukrainian_North
.000351 Russian_Pskov
.000400 Hungarian
.000476 Russian_Archangelsk_Krasnoborsky
.000500 Croatian
.000531 Russian_Vologda
.000547 Estonian
.000552 Russian_Yaroslavl
.000585 Bulgarian
.000607 Mordovian
.000618 Cordona_German
.000670 Lithuanian
.000817 Gagauz
.000969 French
.001045 English
.001046 Cordona_Mordva
.001151 Cordona_British
.001275 Norwegian
.001336 Romanian
.001380 Finnish
.001454 Icelandic
.001506 Albanian
.001555 Spanish
.001616 Moldavian
.001701 Tatar_Kazan
.001797 Orcadian
.001812 Italian_North
.001887 Greek
.001924 Karelian
.001959 Tatar_Mishar
.002168 Cordona_Italian
.002495 Sicilian
.002528 Italian_South
.002537 Russian_Archangelsk_Pinezhsky
.002660 Spanish_North
.002736 Scottish
.002814 Kumyk
.002935 Veps
.002975 Kabardinian
.003027 Abazin
.003075 Turkish
.003138 Chuvash
.003152 Cordona_Turk
.003254 Circassian
.003326 Balkar
.003390 Canary_Islander
.003454 Maltese
.003468 Jew_Turkish
.003532 Lezgin
.003578 Adygei
.003585 Russian_Archangelsk_Leshukonsky
.003603 Jew_Ashkenazi
.003637 Nogai_Karachay_Cherkessia
.003799 Basque
.003885 Tajik
.004020 Azeri
.004063 Ossetian
.004083 Cypriot
.004196 Chechen
.004227 Tabasaran
.004278 Iranian
.004348 Lebanese_Muslim
.004377 Armenian
.004410 Bashkir
.004473 Cordona_Iranian
.004525 Lebanese_Christian
.004654 Ingushian
.004669 Jew_Moroccan
.004686 Kaitag
.004761 Lebanese
.004798 Abkhasian
.004867 Georgian
.005010 Karachai
.005074 Sardinian
.005105 Cordona_Avar
.005157 Jordanian
.005181 Ezid
.005221 Armenian_Hemsheni
.005297 Avar
.005376 Assyrian
.005463 Besermyan
.005498 Lak
.005527 Cordona_Turkmen
.005641 Syrian
.005770 Pathan
.005924 Palestinian
.005976 Cordona_Tajik
.005994 Druze
.006000 Cordona_Mari
.006156 Uzbek
.006176 Cordona_Komi
.006291 Jew_Iraqi
.006318 BedouinA
.006338 Iranian_Bandari
.006435 Turkmen
.006441 Udmurt
.006487 Darginian
.006533 Jew_Iranian
.006617 Jew_Georgian
.006650 Kurd
.006836 Egyptian
.006888 Jew_Libyan
.006940 Jew_Tunisian
.007029 Balochi
.007194 GujaratiA
.007234 Makrani
.007380 Yemeni
.007422 Cordona_Egyptian
.007501 Yukagir_Forest
.007635 Brahui
.007670 Sindhi_Pakistan
.007816 Libyan
.007836 Turkish_Balikesir
.007945 Nogai_Stavropol
.007952 Tatar_Siberian
.008254 Burusho
.008342 Yemeni_Northwest
.008396 Yemeni_Highlands
.008425 Tunisian
.008528 Saudi
.008552 Aleut
.008926 GujaratiB
.009135 Kubachinian
.009406 Yemeni_Highlands_Raymah
.009415 Jew_Yemenite
.009705 Jew_Cochin
.009954 Uyghur
.010009 Moroccan
.010022 Karakalpak
.010098 Nogai_Astrakhan
.010284 Yemeni_Desert2
.010315 Bahun
.010739 GujaratiC
.011530 Hazara
.011706 Cordona_Uygur
.011734 Punjabi
.011799 Mozabite
.011813 Cordona_Kazakh
.012040 Yemeni_Desert
.012192 Tlingit
.012334 Bengali
.013095 GujaratiD
.013125 BedouinB
.013294 Kazakh
.013298 Cordona_Sri_Lankan
.013319 Algerian
.013522 Cordona_Indian
.014017 Saharawi
.014159 Tatar_Siberian_Zabolotniye
.014396 Kyrgyz_Tajikistan
.014689 Mansi
.014878 Cordona_Khant
.015012 Kalash
.015058 Kyrgyz_Kyrgyzstan
.015446 Kyrgyz_China
.015998 Khakass
.016322 Even
.016391 Cordona_Teleut
.016400 Altaian_Chelkan
.017383 Newar
.017472 Tubalar
.017675 Kazakh_China
.017995 Eritrea
.017995 Shor_Mountain
.018327 Tharu
.019210 Altaian
.019468 Cordona_Altai_Kizhi
.019680 Cordona_Ket
.020101 Khakass_Kachin
.020231 Jew_Ethiopian
.021023 Selkup
.021201 Cordona_Tundra_Nentsi
.021713 Kalmyk
.022202 Shor_Khakassia
.022319 Cordona_Selkup
.022664 Evenk_FarEast
.023587 Mongol
.023819 Tuvinian
.023999 Ket
.024203 Salar
.024220 Cordona_Mongol
.024459 Dongxiang
.024672 Cordona_Buryat
.024836 Burmese
.025122 Cordona_Dolgan
.025200 Buryat
.025506 Dungan
.026427 Khamnegan
.026520 Dolgan
.026635 Magar
.026797 Tamang
.026914 Enets
.027439 Somali
.027689 Cordona_Forest_Nentsi
.027912 Tu
.028168 Malay
.028383 Bonan
.028461 Cordona_Even
.028915 Yakut
.028927 Cambodian
.029040 Thai
.029309 Yugur
.029371 Mongola
.029495 Gurung
.029824 Cordona_Yakut
.029863 Kusunda
.029898 Xibo
.030450 Daur
.030545 Tibetan
.030776 Tagalog
.031107 Todzin
.031285 Cordona_Tibetan
.031424 Oroqen
.032256 Hezhen
.032275 Cordona_Indonesia_Java
.032477 Yi
.032478 Tofalar
.032532 Cordona_Manchu
.032674 Rai
.032778 Kinh
.032845 Naxi
.032883 Datog
.032894 Sherpa
.032929 Qiang
.032957 Korean
.032977 Han
.033157 Cordona_Vietnamese
.033249 Vietnamese
.033351 Tujia
.033444 Visayan
.033668 Yukagir_Tundra
.033694 Japanese
.033925 Cordona_Korean
.034016 Cordona_Han_South
.034317 Dong
.034335 Zhuang
.034363 Miao
.034694 Mulam
.034787 Dai
.034858 Cordona_Koryak
.034993 Negidal
.035072 Evenk_Transbaikal
.035222 Gelao
.035223 Nanai
.035251 Maonan
.035388 Ulchi
.035734 Li
.036108 She
.036254 Cordona_Evenk
.036886 Masai
.036917 Ilocano
.037222 Dusun
.037670 Tibetan_Yunnan
.037920 China_Lahu
.038650 Chukchi
.038674 Quechua
.039036 Eskimo_ChaplinSireniki
.039565 Cordona_Nganasan
.039588 Mayan
.039962 Murut
.040716 Kikuyu
.040956 Ami
.041201 Nivh
.041219 AA
.041254 Bolivian
.041342 Nganasan
.041736 Cordona_Yukagir
.042224 Koryak
.043168 Zapotec
.043304 Eskimo_Naukan
.043561 Itelmen
.044633 Mixtec
.044954 Kankanaey
.048864 Atayal
.051641 Mixe
.052391 Chukchi1
.052446 Luhya
.052801 Luo
.052866 Pima
.053329 Piapoco
.053937 BantuKenya
.054187 Nasioi
.054990 Cordona_Dinka
.055082 Gambian
.056361 Malawi_Ngoni
.056505 Malawi_Tumbuka
.056519 Mandenka
.056748 Malawi_Yao
.056867 Cordona_PNG_Highland
.056885 Mende
.057024 Yoruba
.057102 Malawi_Chewa
.057175 BantuSA_Ovambo
.057528 Esan
.059021 Namibia_Bantu_Herero
.059070 BantuSA
.061692 Australian
.063347 Khomani
.065442 Papuan
.067688 Biaka
.068019 Karitiana
.071690 Hadza1
.074333 Surui
.078495 Mbuti
.084087 Ju_hoan_North
Yes all of them have corrupted millions of minds and caused a very skewed view of population histories, but the reason I have a beef with G25 is because it’s so readily available and easy to use that every other lay person uses it. It along other amateur tools have so brainwashed people that people will not recognize accurate ancestry analysis anymore even if it hits them on the face.
It’ll be very hard to undo the damage already done to peoples view of population history. Very bad indeed !
It is not like the majority of people are really curious about it and seek this knowledge though, lol.
Yes all of them have corrupted millions of minds and caused a very skewed view of population histories, but the reason I have a beef with G25 is because it’s so readily available and easy to use that every other lay person uses it. It along other amateur tools have so brainwashed people that people will not recognize accurate ancestry analysis anymore even if it hits them on the face.
It’ll be very hard to undo the damage already done to peoples view of population history. Very bad indeed !
It is not like the majority of people are really curious about it and seek this knowledge though, lol.
thunderbolt
11-23-2022, 02:44 PM
Deleted
thunderbolt
11-23-2022, 02:52 PM
Deleted
thunderbolt
11-23-2022, 02:59 PM
Thanks for posting these ! Another piece of evidence to be added to the evidence I have already pointed out so far that G25 shouldn't be taken seriously. Keep posting these because the more proofs people see how G25 is wrong the more they will be convinced it's a joke :D
No it's NOT true that Europeans are closer to West or Central or South- Central Asians than East Asians are to Siberians !
Here's your proof that G25 is wrong.
These are gene to gene comparisons averaged over populations using IBS and 400,000 overlapping SNPs
As you can see Han share more genes with Siberians such as Even (0.733105) and even Mansi (0.71674) than British share with even the closest W. Asians (0.7131) and Pathan (0.7090)
<colgroup width="268"></colgroup> <colgroup width="85" span="2"></colgroup> <tbody>
IBS with HAN_1000G
REGION
AVG-IBS
Chinese_Han_S_1000G
E_Asia
0.742565
Chinese_Han_1000G
E_Asia
0.742465
Japanese_1000G
E_Asia
0.74105
Chinese_Dai_1000G
E_Asia
0.74039
Vietnam_Kinh_1000G
E_Asia
0.73973
Mongola_Simons
E_Asia
0.738855
Even_Simons
Siberia
0.733105
PALEO-SIBERIAN-Kolyma-Mesol-WGS
Siberia
0.729545
Karitiana_Simons
Americas
0.72603
Kyrgyz_Simons
C_Asia
0.725555
Mayan_Simons
Americas
0.72554
Onge_1000G
S_Asia
0.71883
Uyghur
C_Asia
0.71769
Peruvian_1000G
Americas
0.71683
Mansi_Simons
Siberia
0.71674
Uzbek
C_Asia
0.715205
Tatar_Tomsk
E_Europe
0.71519
Turkmen
C_Asia
0.71304
Bengali_1000G
S_Asia
0.71212
Bashkir
E_Europe
0.710635
Tamil_1000G
S_Asia
0.70905
Indian_Telugu_1000G
S_Asia
0.7084
Gujarati_1000G
S_Asia
0.70741
Punjabi_Simons
S_Asia
0.70672
Punjabi_Lahore_1000G
S_Asia
0.70636
Saami_Simons
E_Europe
0.705815
ANS-Yana-UP-WGS
Siberia
0.70572
Tatar_Volga
E_Europe
0.704275
Pathan_Simons
S_Asia
0.70238
Brahui_Simons
S_Asia
0.70056
Finnish_1000G
E_Europe
0.700375
Kurds_IQ
W_Asia
0.699595
Ossetian_Simons
W_Asia
0.699535
Russian_Simons
E_Europe
0.69942
Turkish_Kayseri_Simons
W_Asia
0.69868
YAMNAYA-Karagash-Dipl
E_Europe
0.698655
Finnish_Simons
E_Europe
0.698485
Iranian_South_Simons
W_Asia
0.69765
Abkhasian_Simons
W_Asia
0.69736
Lezgin_Simons
W_Asia
0.697145
Estonian_Simons
E_Europe
0.696935
British_1000G
W_Europe
0.696865
WHG-Loschbour
W_Europe
0.696275
Armenian_Simons
W_Asia
0.69611
Georgian_Simons
W_Asia
0.695625
Iberian_1000G
W_Europe
0.69553
Basque_Simons
W_Europe
0.69529
BedouinB_Simons
W_Asia
0.693955
</tbody>
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<colgroup width="201"></colgroup> <colgroup width="85" span="2"></colgroup> <tbody>
IBS with BRITISH_1000G
REGION
AVG-IBS
British_1000G
W_Europe
0.7181
WHG-Loschbour
W_Europe
0.7179
Finnish_1000G
E_Europe
0.7170
Basque_Simons
W_Europe
0.7169
Finnish_Simons
E_Europe
0.7165
Estonian_Simons
E_Europe
0.7164
Iberian_1000G
W_Europe
0.7161
Russian_Simons
E_Europe
0.7155
YAMNAYA-Karagash-Dipl
E_Europe
0.7154
EEF-Stuttgart
W_Europe
0.7151
Lezgin_Simons
W_Asia
0.7133
Abkhasian_Simons
W_Asia
0.7131
Kurds_IQ
W_Asia
0.7131
Tatar_Volga
E_Europe
0.7131
Armenian_Simons
W_Asia
0.7128
Georgian_Simons
W_Asia
0.7127
Saami_Simons
E_Europe
0.7126
Ossetian_Simons
W_Asia
0.7124
Turkish_Kayseri_Simons
W_Asia
0.7122
Iranian_South_Simons
W_Asia
0.7107
Bashkir
E_Europe
0.7102
BedouinB_Simons
W_Asia
0.7094
Pathan_Simons
S_Asia
0.7090
Brahui_Simons
S_Asia
0.7090
Jordanian_Simons
W_Asia
0.7090
Colombian_1000G
Americas
0.7084
Turkmen
C_Asia
0.7078
Tatar_Tomsk
E_Europe
0.7075
Mansi_Simons
Siberia
0.7070
Punjabi_Lahore_1000G
S_Asia
0.7069
Uzbek
C_Asia
0.7065
Gujarati_1000G
S_Asia
0.7061
Punjabi_Simons
S_Asia
0.7052
</tbody>
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So, am I correct in inferring based on the table that generally speaking, East Eurasians (East Asians, Siberians, Native Americans) are closer genetically to each other than West Eurasians are to each other (including even Europeans to other Europeans)??? Because in that table, Han have higher IBS scores with other E/SE Asians, as well as with neo-siberian Even, paleo-siberian Kolyma, and amerindian Karitiana + Mayan than the British do with even themselves. I think I saw a similar pattern regarding global relationships in the supplementary section of some 2012 Harvard study about Denisovans (there was a table of pairwise differences in one million bases between modern day individuals as well as some ancient Denisovans), but I'm not an expert in this stuff at all so I don't know if I'm interpreting everything correctly because I see different results on different posts.
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