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Ajeje Brazorf
06-04-2018, 03:38 PM
Eurogenes EUtest V2 K15 Admixture Proportions

Eurogenes EUtest V2 K15 Admixture Proportions

This utility uses the Eurogenes EUtest V2 K15 model, created by Davidski (Polako). Questions and comments about this model
should be directed to him at his Project Blog.

Kit Number: M611023 Elapsed Time: 14.45 seconds


Population
North_Sea 13.64
Atlantic 2.50
Baltic 5.75
Eastern_Euro 12.10
West_Med -
West_Asian 23.60
East_Med 1.39
Red_Sea -
South_Asian 38.43
Southeast_Asian -
Siberian -
Amerindian 1.53
Oceanian 0.89
Northeast_African -
Sub-Saharan 0.17









Web site and contents ©Copyright 2011-2018 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions 'calculator' model remains the property of its developer.

164661 SNPs used in this evaluation

Oracle

GEDmatch.Com Oracle
This version of GEDmatch Oracle is based on 'Oracle v1' by Dienekes Pontikos. His original program was developed as part of the Dodecad Ancestry Project. More information on Dienekes' orignal program can be found here.

Many thanks also to Zack Ajmal for helping us get this web version of Dienekes' Oracle program developed.

Eurogenes EUtest V2 K15 Oracle results:
Kit M611023

Admix Results (sorted):

# Population Percent
1 South_Asian 38.43
2 West_Asian 23.6
3 North_Sea 13.64
4 Eastern_Euro 12.1
5 Baltic 5.75
6 Atlantic 2.5
7 Amerindian 1.53
8 East_Med 1.39
9 Oceanian 0.89
10 Sub-Saharan 0.17

Single Population Sharing:

# Population (source) Distance
1 Punjabi_Jat 8.59
2 Pathan 10.23
3 Kalash 11.69
4 Burusho 13.66
5 Sindhi 14.45
6 Afghan_Pashtun 15.65
7 Balochi 18.76
8 Brahui 19.46
9 Brahmin_UP 20.78
10 Tadjik 21.96
11 Makrani 22.09
12 Gujarati 22.62
13 Afghan_Uzbeki 23.87
14 Kshatriya 23.98
15 Afghan_Tadjik 23.99
16 Bangladeshi 27.2
17 Turkmen 30.37
18 Dharkar 31.77
19 Kanjar 32.88
20 Tabassaran 34.56

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 86.2% Punjabi_Jat + 13.8% Swedish @ 3.76
2 86% Punjabi_Jat + 14% North_Swedish @ 3.8
3 86.7% Punjabi_Jat + 13.3% West_Norwegian @ 3.84
4 86.3% Punjabi_Jat + 13.7% Norwegian @ 3.87
5 86% Punjabi_Jat + 14% Finnish @ 4.18
6 86.7% Punjabi_Jat + 13.3% North_Dutch @ 4.26
7 86.3% Punjabi_Jat + 13.7% Southwest_Finnish @ 4.35
8 86.7% Punjabi_Jat + 13.3% Danish @ 4.38
9 86.1% Punjabi_Jat + 13.9% West_German @ 4.41
10 87.1% Punjabi_Jat + 12.9% Orcadian @ 4.43
11 86.4% Punjabi_Jat + 13.6% North_German @ 4.46
12 86.8% Punjabi_Jat + 13.2% Estonian @ 4.52
13 87.3% Punjabi_Jat + 12.7% West_Scottish @ 4.58
14 86% Punjabi_Jat + 14% East_German @ 4.59
15 86.3% Punjabi_Jat + 13.7% East_Finnish @ 4.61
16 87.3% Punjabi_Jat + 12.7% Irish @ 4.63
17 85.6% Punjabi_Jat + 14.4% Hungarian @ 4.64
18 85.9% Punjabi_Jat + 14.1% Ukrainian_Lviv @ 4.66
19 86.1% Punjabi_Jat + 13.9% Ukrainian @ 4.7
20 87.2% Punjabi_Jat + 12.8% Southeast_English @ 4.71


Oracle-4

Kit Num: M611023
Threshold of components set to 1.000
Threshold of method set to 0.25%
Personal data has been read. 20 approximations mode.
Gedmatch.Com
Eurogenes EUtest V2 K15 4-Ancestors Oracle
This program is based on 4-Ancestors Oracle Version 0.96 by Alexandr Burnashev.
Questions about results should be sent to him at: Alexandr.Burnashev@gmail.com
Original concept proposed by Sergey Kozlov.
Many thanks to Alexandr for helping us get this web version developed.

Admix Results (sorted):

# Population Percent
1 South_Asian 38.43
2 West_Asian 23.60
3 North_Sea 13.64
4 Eastern_Euro 12.10
5 Baltic 5.75
6 Atlantic 2.50
7 Amerindian 1.53
8 East_Med 1.39


Finished reading population data. 207 populations found.
15 components mode.

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

Least-squares method.

Using 1 population approximation:
1 Punjabi_Jat @ 9.728746
2 Pathan @ 11.876847
3 Kalash @ 13.645540
4 Burusho @ 15.058822
5 Sindhi @ 16.619198
6 Afghan_Pashtun @ 17.801937
7 Balochi @ 21.876165
8 Brahui @ 22.722078
9 Brahmin_UP @ 23.462679
10 Tadjik @ 23.961880
11 Gujarati @ 25.414402
12 Makrani @ 25.663717
13 Afghan_Uzbeki @ 25.700094
14 Afghan_Tadjik @ 25.825968
15 Kshatriya @ 27.041960
16 Bangladeshi @ 30.253101
17 Turkmen @ 34.015148
18 Dharkar @ 35.823830
19 Kanjar @ 37.040459
20 Afghan_Hazara @ 37.533955

Using 2 populations approximation:
1 50% Kol +50% Tabassaran @ 8.626623


Using 3 populations approximation:
1 50% Kalash +25% North_Swedish +25% Velamas @ 5.441526


Using 4 populations approximation:
++++++++++++++++++++++++++++++++++++++++++++++++++ +++++++++++++++++++++++++++++++++++++++++++++
1 Kalash + Kalash + North_Swedish + Velamas @ 5.441526
2 Kalash + Kalash + Kurumba + North_Swedish @ 5.677960
3 Kalash + Kalash + Swedish + Velamas @ 5.705999
4 Kalash + Kalash + North_Swedish + Piramalai @ 5.831436
5 Kalash + Kalash + Kurumba + Swedish @ 5.896211
6 Kalash + Kalash + Norwegian + Velamas @ 5.951341
7 Finnish + Kalash + Kalash + Velamas @ 5.961473
8 Kalash + Kalash + Piramalai + Swedish @ 6.006743
9 Dusadh + Kalash + Kalash + North_Swedish @ 6.083641
10 Gujarati + Kalash + North_Swedish + Sindhi @ 6.084063
11 Kalash + Kalash + Kol + North_Swedish @ 6.147500
12 Kalash + Kalash + Kurumba + Norwegian @ 6.153365
13 Kalash + Kalash + Velamas + West_Norwegian @ 6.171648
14 Finnish + Kalash + Kalash + Kurumba @ 6.174935
15 Kalash + Kalash + Kanjar + North_Swedish @ 6.196017
16 Kalash + Kalash + Kanjar + Swedish @ 6.233309
17 Dusadh + Kalash + Kalash + Swedish @ 6.252823
18 Kalash + Kalash + Norwegian + Piramalai @ 6.262583
19 Dharkar + Kalash + Kalash + North_Swedish @ 6.274601
20 Kalash + Kalash + Kol + Swedish @ 6.289981

Done.

Elapsed time 1.3478 seconds.

HarappaWorld Admixture Proportions

HarappaWorld Admixture Proportions

This utility uses the HarappaWorld model, created by Zack. Questions and comments about this model
should be directed to him at harappa@zackvision.com or to his HarappaWorld blog.
We appreciate him making this excellent tool available here.

Kit Number: M611023 Elapsed Time: 17.60 seconds


Population
S-Indian 24.87
Baloch 35.54
Caucasian 10.76
NE-Euro 20.38
SE-Asian -
Siberian 0.72
NE-Asian -
Papuan 1.09
American 1.79
Beringian -
Mediterranean 4.21
SW-Asian 0.59
San -
E-African -
Pygmy -
W-African -









Web site and contents ©Copyright 2011-2018 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions 'calculator' model remains the property of its developer.

164594 SNPs used in this evaluation

Oracle

GEDmatch.Com Oracle
This version of GEDmatch Oracle is based on 'Oracle v1' by Dienekes Pontikos. His original program was developed as part of the Dodecad Ancestry Project. More information on Dienekes' orignal program can be found here.

Many thanks also to Zack Ajmal for helping us get this web version of Dienekes' Oracle program developed.

HarappaWorld Oracle results:
23 April 2013 - Oracle reference population percentages revised.

Kit M611023

Admix Results (sorted):

# Population Percent
1 Baloch 35.54
2 S-Indian 24.87
3 NE-Euro 20.38
4 Caucasian 10.76
5 Mediterranean 4.21
6 American 1.79
7 Papuan 1.09
8 Siberian 0.72
9 SW-Asian 0.59
10 Beringian 0.04

Single Population Sharing:

# Population (source) Distance
1 haryana-jatt (harappa) 3.86
2 punjabi-jatt-sikh (harappa) 9.24
3 punjabi-khatri (harappa) 11.13
4 pathan (hgdp) 11.59
5 kashmiri (harappa) 12.75
6 sindhi (harappa) 12.82
7 nepalese-a (xing) 12.96
8 bhatia (harappa) 13.14
9 punjabi-brahmin (harappa) 13.31
10 punjabi-jatt-muslim (harappa) 13.36
11 kashmiri-pandit (reich) 13.46
12 burusho (hgdp) 13.59
13 singapore-indian-c (sgvp) 13.8
14 pashtun (harappa) 14.01
15 punjabi (harappa) 14.05
16 kalash (hgdp) 14.31
17 up-muslim (harappa) 14.72
18 punjabi-ramgarhia (harappa) 15.05
19 kashmiri-pahari (harappa) 15.36
20 punjabi-arain (xing) 15.55

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 93.6% haryana-jatt (harappa) + 6.4% ukranian (yunusbayev) @ 1.72
2 93.2% haryana-jatt (harappa) + 6.8% slovenian (xing) @ 1.73
3 93.2% haryana-jatt (harappa) + 6.8% hungarian (behar) @ 1.77
4 94.1% haryana-jatt (harappa) + 5.9% russian (behar) @ 1.8
5 94.1% haryana-jatt (harappa) + 5.9% belorussian (behar) @ 1.81
6 77.8% punjabi-arain (xing) + 22.2% russian (behar) @ 1.84
7 92.9% haryana-jatt (harappa) + 7.1% romanian-a (behar) @ 1.93
8 93.1% haryana-jatt (harappa) + 6.9% bulgarian (yunusbayev) @ 1.96
9 93.8% haryana-jatt (harappa) + 6.2% mordovian (yunusbayev) @ 1.96
10 94.7% haryana-jatt (harappa) + 5.3% lithuanian (behar) @ 2.03
11 93.9% haryana-jatt (harappa) + 6.1% n-european (xing) @ 2.11
12 94% haryana-jatt (harappa) + 6% utahn-white (hapmap) @ 2.16
13 77.9% punjabi-arain (xing) + 22.1% belorussian (behar) @ 2.16
14 94.1% haryana-jatt (harappa) + 5.9% utahn-white (1000genomes) @ 2.21
15 85.8% punjabi-jatt-sikh (harappa) + 14.2% belorussian (behar) @ 2.24
16 94.2% haryana-jatt (harappa) + 5.8% british (1000genomes) @ 2.28
17 95.6% haryana-jatt (harappa) + 4.4% finnish (1000genomes) @ 2.31
18 94.1% haryana-jatt (harappa) + 5.9% french (hgdp) @ 2.32
19 94.3% haryana-jatt (harappa) + 5.7% orcadian (hgdp) @ 2.32
20 85.8% punjabi-jatt-sikh (harappa) + 14.2% russian (behar) @ 2.35


Oracle-4

Kit Num: M611023
Threshold of components set to 1.000
Threshold of method set to 0.25%
Personal data has been read. 20 approximations mode.
Gedmatch.Com
HarappaWorld 4-Ancestors Oracle
This program is based on 4-Ancestors Oracle Version 0.96 by Alexandr Burnashev.
Questions about results should be sent to him at: Alexandr.Burnashev@gmail.com
Original concept proposed by Sergey Kozlov.
Many thanks to Alexandr for helping us get this web version developed.

23 April 2013 - Oracle reference population percentages revised.

Admix Results (sorted):

# Population Percent
1 Baloch 35.54
2 S-Indian 24.87
3 NE-Euro 20.38
4 Caucasian 10.76
5 Mediterranean 4.21
6 American 1.79
7 Papuan 1.09


Finished reading population data. 377 populations found.
16 components mode.

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

Least-squares method.

Using 1 population approximation:
1 haryana-jatt_harappa @ 4.178029
2 punjabi-jatt-sikh_harappa @ 10.125698
3 rajasthani-brahmin_harappa @ 10.341934
4 punjabi-khatri_harappa @ 12.204597
5 pushtikar-brahmin_harappa @ 12.513543
6 pathan_hgdp @ 12.736503
7 nepali_harappa @ 13.087939
8 kashmiri_harappa @ 14.020673
9 sindhi_harappa @ 14.060167
10 nepalese-a_xing @ 14.236837
11 bhatia_harappa @ 14.424397
12 punjabi-jatt-muslim_harappa @ 14.619840
13 punjabi-brahmin_harappa @ 14.622923
14 burusho_hgdp @ 14.774074
15 kashmiri-pandit_reich @ 14.788711
16 singapore-indian-c_sgvp @ 15.175798
17 pashtun_harappa @ 15.423087
18 punjabi_harappa @ 15.442262
19 kalash_hgdp @ 15.770855
20 up-muslim_harappa @ 16.206507

Using 2 populations approximation:
1 50% haryana-jatt_harappa +50% haryana-jatt_harappa @ 4.178029


Using 3 populations approximation:
1 50% bhatia_harappa +25% goan_harappa +25% ukranian_yunusbayev @ 2.404942


Using 4 populations approximation:
++++++++++++++++++++++++++++++++++++++++++++++++++ ++++++++++++++++++++++++++++++++++++++++++++++++++ ++++++++++++++++++++++++++++++++++++++++++++++++++ ++++++++
1 bhatia_harappa + gujarati-a_hapmap + kalash_hgdp + ukranian_yunusbayev @ 2.009669
2 bhatia_harappa + gujarati-a_1000genomes + kalash_hgdp + ukranian_yunusbayev @ 2.115617
3 bhatia_harappa + gujarati-patel_harappa + kalash_hgdp + ukranian_yunusbayev @ 2.145433
4 bhatia_harappa + bhatia_harappa + goan_harappa + ukranian_yunusbayev @ 2.404942
5 bhatia_harappa + haryana-jatt_harappa + kalash_hgdp + singapore-indian-d_sgvp @ 2.487880
6 bhatia_harappa + gujarati-patel_harappa + kalash_hgdp + mordovian_yunusbayev @ 2.488765
7 belorussian_behar + bhatia_harappa + gujarati-patel_harappa + kalash_hgdp @ 2.511551
8 bhatia_harappa + gujarati-a_1000genomes + kalash_hgdp + mordovian_yunusbayev @ 2.528585
9 bhatia_harappa + bhatia_harappa + kerala-nair_harappa + ukranian_yunusbayev @ 2.547066
10 bhatia_harappa + meena_metspalu + punjabi-arain_xing + ukranian_yunusbayev @ 2.557248
11 bhatia_harappa + bhatia_harappa + gujarati-a_1000genomes + ukranian_yunusbayev @ 2.580427
12 belorussian_behar + bhatia_harappa + gujarati-a_hapmap + kalash_hgdp @ 2.583248
13 bhatia_harappa + gujarati-a_hapmap + kalash_hgdp + mordovian_yunusbayev @ 2.602603
14 belorussian_behar + bhatia_harappa + gujarati-a_1000genomes + kalash_hgdp @ 2.608679
15 bhatia_harappa + bhatia_harappa + gujarati-a_hapmap + ukranian_yunusbayev @ 2.609971
16 bhatia_harappa + meena_metspalu + sindhi_hgdp + ukranian_yunusbayev @ 2.638649
17 bhatia_harappa + gujarati-b_hapmap + sindhi_hgdp + ukranian_yunusbayev @ 2.644528
18 bhatia_harappa + haryana-jatt_harappa + pathan_hgdp + singapore-indian-d_sgvp @ 2.652040
19 bhatia_harappa + bhatia_harappa + tn-brahmin_xing + ukranian_yunusbayev @ 2.658134
20 bhatia_harappa + gujarati-patel_harappa + kalash_hgdp + russian_behar @ 2.681278

Done.

Elapsed time 9.3264 seconds.

Eurogenes_ANE K7 Admixture Proportions

Eurogenes_ANE K7 Admixture Proportions

This utility uses the Eurogenes ANE K7 model, created by Davidski (Polako). Questions and comments about this calculator
should be directed to him at his Project Blog. Revised 2014-Sep-12

Kit Number: M611023 Elapsed Time: 10.34 seconds


Population
ANE 29.62
ASE 12.98
WHG-UHG 17.29
East_Eurasian 2.25
West_African 0.98
East_African 1.54
ENF 35.34




Web site and contents ©Copyright 2011-2018 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions 'calculator' model remains the property of its developer.

162931 SNPs used in this evaluation

Eurogenes K13 Admixture Proportions

Eurogenes K13 Admixture Proportions

This utility uses the Eurogenes K13 model (rev 21 Nov 2013), created by Davidski (Polako). Questions and comments about this model
should be directed to him at his Project Blog.

Kit Number: M611023 Elapsed Time: 12.85 seconds


Population
North_Atlantic 13.74
Baltic 13.41
West_Med -
West_Asian 32.33
East_Med 0.38
Red_Sea -
South_Asian 36.42
East_Asian -
Siberian 0.29
Amerindian 1.85
Oceanian 1.30
Northeast_African -
Sub-Saharan 0.28









Web site and contents ©Copyright 2011-2018 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions 'calculator' model remains the property of its developer.

162838 SNPs used in this evaluation

Oracle

GEDmatch.Com Oracle
This version of GEDmatch Oracle is based on 'Oracle v1' by Dienekes Pontikos. His original program was developed as part of the Dodecad Ancestry Project. More information on Dienekes' orignal program can be found here.

Many thanks also to Zack Ajmal for helping us get this web version of Dienekes' Oracle program developed.

Eurogenes K13 Oracle results:
K13 Oracle ref data revised 21 Nov 2013

Kit M611023

Admix Results (sorted):

# Population Percent
1 South_Asian 36.42
2 West_Asian 32.33
3 North_Atlantic 13.74
4 Baltic 13.41
5 Amerindian 1.85
6 Oceanian 1.3
7 East_Med 0.38
8 Siberian 0.29
9 Sub-Saharan 0.28

Single Population Sharing:

# Population (source) Distance
1 Punjabi_Jat 8.84
2 Pathan 11.61
3 Kalash 12.16
4 Burusho 13.91
5 Afghan_Pashtun 14.93
6 Sindhi 16.26
7 Brahmin_UP 19.72
8 Tadjik 20.83
9 Gujarati 22.3
10 Kshatriya 23.35
11 Afghan_Tadjik 23.67
12 Balochi 23.68
13 Makrani 24.8
14 Brahui 24.91
15 Bangladeshi 27.56
16 Dharkar 31.37
17 Tabassaran 31.69
18 Turkmen 31.77
19 Kanjar 32.16
20 Lezgin 34

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 86.1% Punjabi_Jat + 13.9% Swedish @ 2.47
2 86.3% Punjabi_Jat + 13.7% Norwegian @ 2.5
3 85.6% Punjabi_Jat + 14.4% North_German @ 2.66
4 86.2% Punjabi_Jat + 13.8% North_Dutch @ 2.66
5 86% Punjabi_Jat + 14% Danish @ 2.7
6 86.3% Punjabi_Jat + 13.7% North_Swedish @ 2.73
7 86.3% Punjabi_Jat + 13.7% Irish @ 2.77
8 86.5% Punjabi_Jat + 13.5% West_Scottish @ 2.85
9 86.4% Punjabi_Jat + 13.6% Orcadian @ 2.86
10 86.5% Punjabi_Jat + 13.5% Southeast_English @ 3.08
11 86.7% Punjabi_Jat + 13.3% Southwest_English @ 3.15
12 85.7% Punjabi_Jat + 14.3% West_German @ 3.4
13 86.9% Punjabi_Jat + 13.1% Southwest_Finnish @ 3.42
14 86% Punjabi_Jat + 14% South_Dutch @ 3.49
15 85.7% Punjabi_Jat + 14.3% East_German @ 3.49
16 87.3% Punjabi_Jat + 12.7% La_Brana-1 @ 3.51
17 85.6% Punjabi_Jat + 14.4% Austrian @ 3.53
18 85.4% Punjabi_Jat + 14.6% Hungarian @ 3.79
19 87.2% Punjabi_Jat + 12.8% Finnish @ 3.84
20 86.2% Punjabi_Jat + 13.8% South_Polish @ 3.96


Oracle-4

Kit Num: M611023
Threshold of components set to 1.000
Threshold of method set to 0.25%
Personal data has been read. 20 approximations mode.
Gedmatch.Com
Eurogenes K13 4-Ancestors Oracle
This program is based on 4-Ancestors Oracle Version 0.96 by Alexandr Burnashev.
Questions about results should be sent to him at: Alexandr.Burnashev@gmail.com
Original concept proposed by Sergey Kozlov.
Many thanks to Alexandr for helping us get this web version developed.

K13 Oracle ref data revised 21 Nov 2013

Admix Results (sorted):

# Population Percent
1 South_Asian 36.42
2 West_Asian 32.33
3 North_Atlantic 13.74
4 Baltic 13.41
5 Amerindian 1.85
6 Oceanian 1.30


Finished reading population data. 204 populations found.
13 components mode.

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

Least-squares method.

Using 1 population approximation:
1 Punjabi_Jat @ 10.012922
2 Pathan @ 13.273455
3 Kalash @ 14.014497
4 Burusho @ 15.225742
5 Afghan_Pashtun @ 16.891771
6 Sindhi @ 18.547487
7 Brahmin_UP @ 22.343407
8 Tadjik @ 22.801920
9 Gujarati @ 25.181982
10 Afghan_Tadjik @ 25.759953
11 Kshatriya @ 26.438486
12 Balochi @ 27.230818
13 Makrani @ 28.387526
14 Brahui @ 28.652039
15 Bangladeshi @ 30.864504
16 Dharkar @ 35.525352
17 Turkmen @ 35.527325
18 Tabassaran @ 35.990669
19 Kanjar @ 36.438408
20 Aghan_Hazara @ 37.966511

Using 2 populations approximation:
1 50% Kanjar +50% Tabassaran @ 8.979199


Using 3 populations approximation:
1 50% Kalash +25% North_German +25% Velamas @ 5.080889


Using 4 populations approximation:
++++++++++++++++++++++++++++++++++++++++++++++++++ +++++++++++++++++++++++++++++
1 Balochi + Kalash + North_Swedish + Piramalai @ 4.655146
2 Brahui + Kalash + North_Swedish + Piramalai @ 4.733434
3 Balochi + Kalash + Kurumba + North_Swedish @ 4.744216
4 Balochi + Kalash + North_Swedish + Velamas @ 4.752587
5 Brahui + Kalash + Kurumba + North_Swedish @ 4.817048
6 Balochi + Kalash + Piramalai + Swedish @ 4.843473
7 Brahui + Kalash + North_Swedish + Velamas @ 4.847542
8 Brahui + Kalash + Piramalai + Swedish @ 4.922954
9 North_Swedish + Sindhi + Sindhi + Sindhi @ 4.995813
10 Balochi + Gujarati + North_Swedish + Sindhi @ 5.005823
11 Balochi + Kalash + Kurumba + Swedish @ 5.039134
12 Balochi + Kalash + Swedish + Velamas @ 5.058499
13 Kalash + Kalash + North_German + Velamas @ 5.080889
14 Balochi + Dusadh + Kalash + North_Swedish @ 5.089122
15 Brahui + Gujarati + North_Swedish + Sindhi @ 5.095685
16 Brahui + Kalash + Kurumba + Swedish @ 5.107737
17 Brahui + Kalash + North_Kannadi + Swedish @ 5.126956
18 Gujarati + Kalash + Sindhi + Swedish @ 5.131131
19 Balochi + Kalash + North_Kannadi + Swedish @ 5.132797
20 Brahui + Dusadh + Kalash + North_Swedish @ 5.144651

Done.

Elapsed time 0.6696 seconds.

Eurogenes Hunter_Gatherer vs. Farmer Admixture Proportions

Eurogenes Hunter_Gatherer vs. Farmer Admixture Proportions

This utility uses the Hunter_Gatherer vs. Farmer model, created by Davidski (Polako). Questions and comments about this model
should be directed to him at his Eurogenes blog. We appreciate him making this excellent tool available here.

A map showing the HGvF populations is available HERE.

Population descriptions are available HERE.

Kit Number: M611023 Elapsed Time: 12.59 seconds


Population
Anatolian Farmer 31.65
Baltic Hunter Gatherer 24.53
Middle Eastern Herder -
East Asian Farmer -
South American Hunter Gatherer 1.39
South Asian Hunter Gatherer 40.95
North Eurasian Hunter Gatherer 0.34
East African Pastoralist -
Oceanian Hunter Gatherer 0.77
Mediterranean Farmer 0.06
Pygmy Hunter Gatherer 0.31
Bantu Farmer -




Web site and contents ©Copyright 2011-2018 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions 'calculator' model remains the property of its developer.

153569 SNPs used in this evaluation

World9 Admixture Proportions

World9 Admixture Proportions

The World9 admixture calculator is courtesy of Dienekes Pontikos and was developed as part of the Dodecad Ancestry Project; more information here.

Kit Number: M611023 Elapsed Time: 10.31 seconds


Population
Amerindian 1.80
East_Asian -
African -
Atlantic_Baltic 23.31
Australasian 1.11
Siberian 0.87
Caucasus_Gedrosia 38.76
Southern 3.33
South_Asian 30.82









Web site and contents ©Copyright 2011-2018 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions 'calculator' model remains the property of its developer.

149171 SNPs used in this evaluation

Oracle

GEDmatch.Com Oracle
This version of GEDmatch Oracle is based on 'Oracle v1' by Dienekes Pontikos. His original program was developed as part of the Dodecad Ancestry Project. More information on Dienekes' orignal program can be found here.

Many thanks also to Zack Ajmal for helping us get this web version of Dienekes' Oracle program developed.

World9 Oracle results:
Kit M611023

Admix Results (sorted):

# Population Percent
1 Caucasus_Gedrosia 38.76
2 South_Asian 30.82
3 Atlantic_Baltic 23.31
4 Southern 3.33
5 Amerindian 1.8
6 Australasian 1.11
7 Siberian 0.87

Single Population Sharing:

# Population (source) Distance
1 Pathan (HGDP) 13.82
2 Burusho (HGDP) 15.62
3 Sindhi (HGDP) 18.84
4 Tajiks (Yunusbayev) 20.23
5 Brahmins_from_Uttar_Pradesh (Metspalu) 20.38
6 Indian (Dodecad) 23.67
7 Kshatriya (Metspalu) 23.81
8 Bnei_Menashe_Jews 23.89
9 Cochin_Jews (Behar) 26.3
10 Balochi (HGDP) 26.73
11 Brahmins_from_Tamil_Nadu (Metspalu) 27.37
12 Turkmens (Yunusbayev) 27.4
13 Kalash 27.72
14 Brahui (HGDP) 28.32
15 GIH30 (Dodecad) 29.03
16 Tharus (Metspalu) 29.09
17 Makrani 29.37
18 Lezgins (Behar) 31.86
19 Muslim (Metspalu) 32.09
20 Chechens (Yunusbayev) 32.15

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 77.7% Sindhi (HGDP) + 22.3% Lithuanian (Dodecad) @ 3.11
2 77.8% Sindhi (HGDP) + 22.2% Lithuanians @ 3.16
3 75.9% Sindhi (HGDP) + 24.1% Russian_B (Behar) @ 3.56
4 76.4% Sindhi (HGDP) + 23.6% Belorussian (Behar) @ 3.58
5 77.3% Sindhi (HGDP) + 22.7% Swedish (Dodecad) @ 3.61
6 77.4% Sindhi (HGDP) + 22.6% FIN30 (1000Genomes) @ 3.61
7 77.6% Sindhi (HGDP) + 22.4% Finnish (Dodecad) @ 3.64
8 75.7% Sindhi (HGDP) + 24.3% Russian (Dodecad) @ 3.67
9 77.4% Sindhi (HGDP) + 22.6% Norwegian (Dodecad) @ 3.74
10 76.3% Sindhi (HGDP) + 23.7% Polish (Dodecad) @ 3.81
11 74.6% Sindhi (HGDP) + 25.4% Mordovians (Yunusbayev) @ 4
12 75.2% Sindhi (HGDP) + 24.8% Ukranians (Yunusbayev) @ 4.06
13 76.4% Sindhi (HGDP) + 23.6% Argyll (1000 Genomes) @ 4.1
14 76.9% Sindhi (HGDP) + 23.1% Orkney (1000 Genomes) @ 4.14
15 76.7% Sindhi (HGDP) + 23.3% Orcadian (HGDP) @ 4.14
16 76.7% Sindhi (HGDP) + 23.3% Irish (Dodecad) @ 4.17
17 76.7% Sindhi (HGDP) + 23.3% British_Isles (Dodecad) @ 4.41
18 76.3% Sindhi (HGDP) + 23.7% CEU30 (1000Genomes) @ 4.52
19 76.5% Sindhi (HGDP) + 23.5% British (Dodecad) @ 4.53
20 76.2% Sindhi (HGDP) + 23.8% German (Dodecad) @ 4.53


Oracle-4

Kit Num: M611023
Threshold of components set to 1.000
Threshold of method set to 0.25%
Personal data has been read. 20 approximations mode.
Gedmatch.Com
World9 4-Ancestors Oracle
This program is based on 4-Ancestors Oracle Version 0.96 by Alexandr Burnashev.
Questions about results should be sent to him at: Alexandr.Burnashev@gmail.com
Original concept proposed by Sergey Kozlov.
Many thanks to Alexandr for helping us get this web version developed.

Admix Results (sorted):

# Population Percent
1 Caucasus_Gedrosia 38.76
2 South_Asian 30.82
3 Atlantic_Baltic 23.31
4 Southern 3.33
5 Amerindian 1.80
6 Australasian 1.11


Finished reading population data. 250 populations found.
9 components mode.

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

Least-squares method.

Using 1 population approximation:
1 Pathan_HGDP @ 15.440923
2 Burusho_HGDP @ 17.350962
3 Sindhi_HGDP @ 21.053453
4 Tajiks_Yunusbayev @ 22.687044
5 Brahmins_from_Uttar_Pradesh_Metspalu @ 23.244612
6 Meena_Metspalu @ 26.196613
7 Bnei_Menashe_Jews @ 26.281055
8 Indian_Dodecad @ 26.961868
9 Kshatriya_Metspalu @ 27.153036
10 Balochi_HGDP @ 29.748793
11 Cochin_Jews_Behar @ 29.760729
12 Turkmens_Yunusbayev @ 30.359697
13 Kalash @ 30.982412
14 Brahmins_from_Tamil_Nadu_Metspalu @ 31.172920
15 Brahui_HGDP @ 31.483091
16 Brahmins_from_Uttaranchal_Metspalu @ 32.144516
17 Makrani @ 32.225765
18 Velamas_Metspalu @ 32.727127
19 GIH30_Dodecad @ 33.094093
20 Tharus_Metspalu @ 33.188179

Using 2 populations approximation:
1 50% Tajiks_Yunusbayev +50% Brahmins_from_Uttar_Pradesh_Metspalu @ 9.330204


Using 3 populations approximation:
1 50% Kalash +25% North_Kannadi +25% Cornwall_1000 Genomes @ 1.522910


Using 4 populations approximation:
++++++++++++++++++++++++++++++++++++++++++++++++++ +++++++++++++++++
1 Polish_Dodecad + Kalash + Sindhi_HGDP + Meghawal_Metspalu @ 1.213342
2 Kalash + Orcadian_HGDP + Sindhi_HGDP + Meghawal_Metspalu @ 1.230752
3 Kalash + Sindhi_HGDP + Orkney_1000 Genomes + Meghawal_Metspalu @ 1.251209
4 Kalash + Sindhi_HGDP + Argyll_1000 Genomes + Meghawal_Metspalu @ 1.263933
5 Irish_Dodecad + Kalash + Sindhi_HGDP + Meghawal_Metspalu @ 1.268889
6 Norwegian_Dodecad + Kalash + Sindhi_HGDP + Meghawal_Metspalu @ 1.300030
7 Swedish_Dodecad + Kalash + Sindhi_HGDP + Meghawal_Metspalu @ 1.322359
8 Kalash + Sindhi_HGDP + Argyll_1000 Genomes + Kurmi_Metspalu @ 1.338163
9 Kalash + Sindhi_HGDP + Belorussian_Behar + Meghawal_Metspalu @ 1.380847
10 Kalash + Orcadian_HGDP + Sindhi_HGDP + Kurmi_Metspalu @ 1.385676
11 Irish_Dodecad + Kalash + Sindhi_HGDP + Kurmi_Metspalu @ 1.386766
12 Kalash + Sindhi_HGDP + Orkney_1000 Genomes + Kurmi_Metspalu @ 1.404922
13 Polish_Dodecad + Kalash + Sindhi_HGDP + INS30_SGVP @ 1.413442
14 Polish_Dodecad + Kalash + Sindhi_HGDP + Kurmi_Metspalu @ 1.434496
15 British_Isles_Dodecad + Kalash + Kalash + North_Kannadi @ 1.441517
16 Kalash + Pathan_HGDP + Ukranians_Yunusbayev + Kurumba_Metspalu @ 1.461688
17 Lithuanian_Dodecad + Brahui_HGDP + Kalash + North_Kannadi @ 1.480433
18 Kalash + Sindhi_HGDP + INS30_SGVP + Argyll_1000 Genomes @ 1.483671
19 Balochi_HGDP + Kalash + Lithuanians + North_Kannadi @ 1.502457
20 Lithuanian_Dodecad + Brahui_HGDP + Kalash + Chamar_Metspalu @ 1.518879

Done.

Elapsed time 0.3122 seconds.

Eurogenes K36 Admixture Proportions

Eurogenes K36 Admixture Proportions

This utility uses the Eurogenes K36 model, created by Davidski (Polako). Questions and comments about this model
should be directed to him at his Eurogenes Genetic Ancestry Project blog.

Kit Number: M611023 Elapsed Time: 28.02 seconds


Population
Amerindian 0.68
Arabian -
Armenian 1.14
Basque -
Central_African -
Central_Euro 1.15
East_African -
East_Asian -
East_Balkan -
East_Central_Asian -
East_Central_Euro 4.44
East_Med -
Eastern_Euro 2.43
Fennoscandian 1.63
French 1.47
Iberian -
Indo-Chinese -
Italian -
Malayan -
Near_Eastern -
North_African -
North_Atlantic 7.71
North_Caucasian 11.92
North_Sea 4.61
Northeast_African -
Oceanian 0.79
Omotic -
Pygmy -
Siberian -
South_Asian 25.56
South_Central_Asian 35.46
South_Chinese -
Volga-Ural 0.37
West_African -
West_Caucasian 0.63
West_Med -




Web site and contents ©Copyright 2011-2018 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions 'calculator' model remains the property of its developer.

147380 SNPs used in this evaluation

Dodecad K12b Admixture Proportions

Dodecad K12b Admixture Proportions

The K12b admixture calculator is courtesy of Dienekes Pontikos and was developed as part of the Dodecad Ancestry Project; more information here.

Kit Number: M611023 Elapsed Time: 11.40 seconds


Population
Gedrosia 35.41
Siberian 1.61
Northwest_African -
Southeast_Asian -
Atlantic_Med 5.85
North_European 20.97
South_Asian 26.26
East_African -
Southwest_Asian 0.59
East_Asian -
Caucasus 9.31
Sub_Saharan -









Web site and contents ©Copyright 2011-2018 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions 'calculator' model remains the property of its developer.

146104 SNPs used in this evaluation

Oracle

GEDmatch.Com Oracle
This version of GEDmatch Oracle is based on 'Oracle v1' by Dienekes Pontikos. His original program was developed as part of the Dodecad Ancestry Project. More information on Dienekes' orignal program can be found here.

Many thanks also to Zack Ajmal for helping us get this web version of Dienekes' Oracle program developed.

Dodecad K12b Oracle results:
The GEDmatch version of Oracle may give slightly different results from Dienekes version. The GEDmatch version uses FST weighting in its calculations.

Kit M611023

Admix Results (sorted):

# Population Percent
1 Gedrosia 35.41
2 South_Asian 26.26
3 North_European 20.97
4 Caucasus 9.31
5 Atlantic_Med 5.85
6 Siberian 1.61
7 Southwest_Asian 0.59

Single Population Sharing:

# Population (source) Distance
1 Pathan (HGDP) 12.54
2 Jatt (Dodecad) 12.64
3 Burusho (HGDP) 15.06
4 Brahmins_from_Uttar_Pradesh (Metspalu) 19.63
5 Sindhi (HGDP) 21.18
6 Tajiks (Yunusbayev) 22.17
7 Kshatriya (Metspalu) 24.5
8 Bnei_Menashe_Jews (Behar) 25.46
9 Cochin_Jews (Behar) 26.47
10 Brahmins_from_Tamil_Nadu (Metspalu) 27.19
11 Indian (Dodecad) 27.79
12 Iyer (Dodecad) 28.98
13 Iyengar (Dodecad) 29.64
14 Turkmens (Yunusbayev) 31.04
15 GIH30 (Dodecad) 33.1
16 Tharus (Metspalu) 33.18
17 Dharkars (Metspalu) 33.71
18 INS30 (SGVP) 33.96
19 Muslim (Metspalu) 34.14
20 Kanjars (Metspalu) 34.36

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 82.3% Jatt (Dodecad) + 17.7% Ukranians (Yunusbayev) @ 3.76
2 79.7% Jatt (Dodecad) + 20.3% Romanians (Behar) @ 3.8
3 80.6% Jatt (Dodecad) + 19.4% Hungarians (Behar) @ 3.91
4 80.4% Jatt (Dodecad) + 19.6% Bulgarians (Yunusbayev) @ 3.97
5 79.9% Jatt (Dodecad) + 20.1% Bulgarian (Dodecad) @ 4.05
6 82.8% Jatt (Dodecad) + 17.2% Mixed_Slav (Dodecad) @ 4.21
7 82.8% Jatt (Dodecad) + 17.2% Polish (Dodecad) @ 4.26
8 83.1% Jatt (Dodecad) + 16.9% Russian_B (Behar) @ 4.26
9 83.5% Jatt (Dodecad) + 16.5% Belorussian (Behar) @ 4.44
10 73.9% Sindhi (HGDP) + 26.1% Russian_B (Behar) @ 4.57
11 83.1% Jatt (Dodecad) + 16.9% Russian (Dodecad) @ 4.6
12 82.3% Jatt (Dodecad) + 17.7% Mordovians (Yunusbayev) @ 4.62
13 73.1% Sindhi (HGDP) + 26.9% Ukranians (Yunusbayev) @ 4.65
14 82.9% Jatt (Dodecad) + 17.1% Russian (HGDP) @ 4.81
15 73.5% Sindhi (HGDP) + 26.5% Mixed_Slav (Dodecad) @ 4.88
16 74.4% Sindhi (HGDP) + 25.6% Belorussian (Behar) @ 4.95
17 72.6% Sindhi (HGDP) + 27.4% Mordovians (Yunusbayev) @ 5.1
18 73.7% Sindhi (HGDP) + 26.3% Russian (Dodecad) @ 5.11
19 84.6% Jatt (Dodecad) + 15.4% Lithuanian (Dodecad) @ 5.16
20 73.6% Sindhi (HGDP) + 26.4% Polish (Dodecad) @ 5.2


Oracle-4

Kit Num: M611023
Threshold of components set to 1.000
Threshold of method set to 0.25%
Personal data has been read. 20 approximations mode.
Gedmatch.Com
Dodecad K12b 4-Ancestors Oracle
This program is based on 4-Ancestors Oracle Version 0.96 by Alexandr Burnashev.
Questions about results should be sent to him at: Alexandr.Burnashev@gmail.com
Original concept proposed by Sergey Kozlov.
Many thanks to Alexandr for helping us get this web version developed.

The GEDmatch version of Oracle may give slightly different results from Dienekes version. The GEDmatch version uses FST weighting in its calculations.

Admix Results (sorted):

# Population Percent
1 Gedrosia 35.41
2 South_Asian 26.26
3 North_European 20.97
4 Caucasus 9.31
5 Atlantic_Med 5.85
6 Siberian 1.61


Finished reading population data. 223 populations found.
12 components mode.

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

Least-squares method.

Using 1 population approximation:
1 Pathan_HGDP @ 13.647705
2 Jatt_Dodecad @ 13.774203
3 Burusho_HGDP @ 15.800796
4 Brahmins_from_Uttar_Pradesh_Metspalu @ 20.832718
5 Sindhi_HGDP @ 23.072018
6 Tajiks_Yunusbayev @ 23.132807
7 Meena_Metspalu @ 25.206604
8 Kshatriya_Metspalu @ 26.039419
9 Bnei_Menashe_Jews_Behar @ 27.668301
10 Cochin_Jews_Behar @ 28.265888
11 Brahmins_from_Tamil_Nadu_Metspalu @ 28.967028
12 Indian_Dodecad @ 29.595428
13 Brahmins_from_Uttaranchal_Metspalu @ 30.782465
14 Iyer_Dodecad @ 30.910006
15 Iyengar_Dodecad @ 31.539608
16 Turkmens_Yunusbayev @ 33.280460
17 Bengali_Metspalu @ 33.560066
18 Lambadi_Metspalu @ 33.650719
19 Tharus_Metspalu @ 35.158775
20 GIH30_Dodecad @ 35.193085

Using 2 populations approximation:
1 50% Brahmins_from_Uttar_Pradesh_Metspalu +50% Tajiks_Yunusbayev @ 7.615635


Using 3 populations approximation:
1 50% Meena_Metspalu +25% Pathan_HGDP +25% Ukranians_Yunusbayev @ 3.839429


Using 4 populations approximation:
++++++++++++++++++++++++++++++++++++++++++++++++++ +++++++++++++++++++++++++++++++++++++++++++++
1 Indian_Dodecad + Pathan_HGDP + Sindhi_HGDP + Ukranians_Yunusbayev @ 2.801229
2 Meena_Metspalu + Pathan_HGDP + Sindhi_HGDP + Ukranians_Yunusbayev @ 2.809582
3 Brahmins_from_Tamil_Nadu_Metspalu + Pathan_HGDP + Sindhi_HGDP + Ukranians_Yunusbayev @ 2.870598
4 Indian_Dodecad + Mixed_Slav_Dodecad + Pathan_HGDP + Sindhi_HGDP @ 2.871462
5 Brahmins_from_Tamil_Nadu_Metspalu + Mixed_Slav_Dodecad + Pathan_HGDP + Sindhi_HGDP @ 2.893095
6 Iyer_Dodecad + Pathan_HGDP + Sindhi_HGDP + Ukranians_Yunusbayev @ 2.953984
7 Brahmins_from_Tamil_Nadu_Metspalu + Mordovians_Yunusbayev + Pathan_HGDP + Sindhi_HGDP @ 3.019083
8 Indian_Dodecad + Pathan_HGDP + Polish_Dodecad + Sindhi_HGDP @ 3.025726
9 Indian_Dodecad + Mordovians_Yunusbayev + Pathan_HGDP + Sindhi_HGDP @ 3.045687
10 Brahmins_from_Tamil_Nadu_Metspalu + Pathan_HGDP + Polish_Dodecad + Sindhi_HGDP @ 3.072819
11 Iyer_Dodecad + Mordovians_Yunusbayev + Pathan_HGDP + Sindhi_HGDP @ 3.110224
12 GIH30_Dodecad + Pathan_HGDP + Sindhi_HGDP + Ukranians_Yunusbayev @ 3.110262
13 GIH30_Dodecad + Mixed_Slav_Dodecad + Pathan_HGDP + Sindhi_HGDP @ 3.133598
14 Iyer_Dodecad + Mixed_Slav_Dodecad + Pathan_HGDP + Sindhi_HGDP @ 3.137213
15 Meena_Metspalu + Mixed_Slav_Dodecad + Pathan_HGDP + Sindhi_HGDP @ 3.177813
16 Brahmins_from_Tamil_Nadu_Metspalu + Pathan_HGDP + Russian_Dodecad + Sindhi_HGDP @ 3.194440
17 Iyengar_Dodecad + Pathan_HGDP + Sindhi_HGDP + Ukranians_Yunusbayev @ 3.212884
18 Indian_Dodecad + Pathan_HGDP + Russian_Dodecad + Sindhi_HGDP @ 3.218665
19 Indian_Dodecad + Pathan_HGDP + Russian_B_Behar + Sindhi_HGDP @ 3.247561
20 Brahmins_from_Tamil_Nadu_Metspalu + Pathan_HGDP + Russian_B_Behar + Sindhi_HGDP @ 3.257986

Done.

Elapsed time 1.5725 seconds.

Dodecad V3 Admixture Proportions

Dodecad V3 Admixture Proportions

The Dodecad V3 (dv3) admixture calculator is courtesy of Dienekes Pontikos and was developed as part of the Dodecad Ancestry Project; more information here.

Kit Number: M611023 Elapsed Time: 10.69 seconds


Population
East_European 9.52
West_European 21.11
Mediterranean 6.69
Neo_African -
West_Asian 21.97
South_Asian 35.99
Northeast_Asian 3.31
Southeast_Asian 0.44
East_African -
Southwest_Asian 0.96
Northwest_African -
Palaeo_African -









Web site and contents ©Copyright 2011-2018 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions 'calculator' model remains the property of its developer.

144923 SNPs used in this evaluation

Oracle

GEDmatch.Com Oracle
This version of GEDmatch Oracle is based on 'Oracle v1' by Dienekes Pontikos. His original program was developed as part of the Dodecad Ancestry Project. More information on Dienekes' orignal program can be found here.

Many thanks also to Zack Ajmal for helping us get this web version of Dienekes' Oracle program developed.

Dodecad V3 Oracle results:
The GEDmatch version of Oracle may give slightly different results from Dienekes version. The GEDmatch version uses FST weighting in its calculations.

Kit M611023

Admix Results (sorted):

# Population Percent
1 South_Asian 35.99
2 West_Asian 21.97
3 West_European 21.11
4 East_European 9.52
5 Mediterranean 6.69
6 Northeast_Asian 3.31
7 Southwest_Asian 0.96
8 Southeast_Asian 0.44

Single Population Sharing:

# Population (source) Distance
1 Pathan (HGDP) 9.57
2 Burusho (HGDP) 13.07
3 Pakistani (Xing) 13.58
4 Kashmiri_Pandit (Reich) 14.18
5 Sindhi (HGDP) 15.06
6 Balochi (HGDP) 18.01
7 Brahui (HGDP) 19.11
8 Bnei_Menashe_Jews (Behar) 19.94
9 Vaish (Reich) 20.21
10 Makrani (HGDP) 21.71
11 Kalash (HGDP) 21.97
12 Meghawal (Reich) 22.33
13 Cochin_Jews (Behar) 23.35
14 TN_Brahmin (Xing) 25.62
15 AP_Brahmin (Xing) 26.07
16 Srivastava (Reich) 26.2
17 Indian (Dodecad) 27.8
18 Nepalese (Xing) 27.92
19 Tharu (Reich) 30.8
20 Velama (Reich) 32.14

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 85.8% Pathan (HGDP) + 14.2% FIN (1000Genomes) @ 4.04
2 86.4% Pathan (HGDP) + 13.6% Swedish (Dodecad) @ 4.24
3 86.8% Pathan (HGDP) + 13.2% Norwegian (Dodecad) @ 4.38
4 80.9% Pakistani (Xing) + 19.1% Swedish (Dodecad) @ 4.44
5 86.4% Pathan (HGDP) + 13.6% Finnish (Dodecad) @ 4.73
6 81.5% Pakistani (Xing) + 18.5% Norwegian (Dodecad) @ 4.73
7 80.4% Pakistani (Xing) + 19.6% FIN (1000Genomes) @ 4.9
8 78.6% Sindhi (HGDP) + 21.4% FIN (1000Genomes) @ 5.12
9 87.5% Pathan (HGDP) + 12.5% Irish (Dodecad) @ 5.16
10 80.5% Kashmiri_Pandit (Reich) + 19.5% Swedish (Dodecad) @ 5.19
11 81% Kashmiri_Pandit (Reich) + 19% Norwegian (Dodecad) @ 5.2
12 79.4% Sindhi (HGDP) + 20.6% Swedish (Dodecad) @ 5.26
13 87.4% Pathan (HGDP) + 12.6% British_Isles (Dodecad) @ 5.27
14 79.5% Pakistani (Xing) + 20.5% Argyll (1000 Genomes) @ 5.28
15 85.7% Pathan (HGDP) + 14.3% German (Dodecad) @ 5.29
16 80.4% Pakistani (Xing) + 19.6% Mixed_Germanic (Dodecad) @ 5.31
17 79.2% Pakistani (Xing) + 20.8% German (Dodecad) @ 5.31
18 86% Pathan (HGDP) + 14% Argyll (1000 Genomes) @ 5.34
19 87.4% Pathan (HGDP) + 12.6% British (Dodecad) @ 5.35
20 86.3% Pathan (HGDP) + 13.7% Orkney (1000 Genomes) @ 5.38


Oracle-4

Kit Num: M611023
Threshold of components set to 1.000
Threshold of method set to 0.25%
Personal data has been read. 20 approximations mode.
Gedmatch.Com
Dodecad V3 4-Ancestors Oracle
This program is based on 4-Ancestors Oracle Version 0.96 by Alexandr Burnashev.
Questions about results should be sent to him at: Alexandr.Burnashev@gmail.com
Original concept proposed by Sergey Kozlov.
Many thanks to Alexandr for helping us get this web version developed.

The GEDmatch version of Oracle may give slightly different results from Dienekes version. The GEDmatch version uses FST weighting in its calculations.

Admix Results (sorted):

# Population Percent
1 South_Asian 35.99
2 West_Asian 21.97
3 West_European 21.11
4 East_European 9.52
5 Mediterranean 6.69
6 Northeast_Asian 3.31


Finished reading population data. 227 populations found.
12 components mode.

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

Least-squares method.

Using 1 population approximation:
1 Pathan_HGDP @ 10.620770
2 Burusho_HGDP @ 13.751746
3 Pakistani_Xing @ 14.940428
4 Kashmiri_Pandit_Reich @ 15.437400
5 Sindhi_HGDP @ 16.503302
6 Balochi_HGDP @ 20.148165
7 Brahui_HGDP @ 21.380598
8 Bnei_Menashe_Jews_Behar @ 22.006826
9 Vaish_Reich @ 22.062916
10 Makrani_HGDP @ 24.003454
11 Meghawal_Reich @ 24.483562
12 Kalash_HGDP @ 24.854380
13 Cochin_Jews_Behar @ 25.585155
14 Nepalese_Xing @ 27.843395
15 TN_Brahmin_Xing @ 28.133883
16 AP_Brahmin_Xing @ 28.570765
17 Srivastava_Reich @ 28.613340
18 Indian_Dodecad @ 30.536018
19 Tharu_Reich @ 33.472000
20 Velama_Reich @ 35.246300

Using 2 populations approximation:
1 50% GIH_HapMap +50% Stalskoe_Xing @ 9.099011


Using 3 populations approximation:
1 50% GIH_HapMap +25% Lezgins_Behar +25% Slovenian_Xing @ 3.782596


Using 4 populations approximation:
++++++++++++++++++++++++++++++++++++++++++++++++++ +++++++++++++++++++++++++++++++++
1 Balochi_HGDP + FIN_1000Genomes + GIH_HapMap + Kalash_HGDP @ 2.476054
2 Brahui_HGDP + FIN_1000Genomes + GIH_HapMap + Kalash_HGDP @ 2.573900
3 FIN_1000Genomes + Kalash_HGDP + Pathan_HGDP + Velama_Reich @ 3.011649
4 FIN_1000Genomes + GIH_HapMap + Kalash_HGDP + Makrani_HGDP @ 3.134482
5 Balochi_HGDP + FIN_1000Genomes + INS_SGVP + Kalash_HGDP @ 3.201520
6 Adygei_HGDP + FIN_1000Genomes + GIH_HapMap + GIH_HapMap @ 3.233095
7 Brahui_HGDP + FIN_1000Genomes + INS_SGVP + Kalash_HGDP @ 3.291386
8 Balochi_HGDP + FIN_1000Genomes + Indian_Dodecad + Kalash_HGDP @ 3.297297
9 Burusho_HGDP + German_Dodecad + Indian_Dodecad + Kalash_HGDP @ 3.335942
10 German_Dodecad + Indian_Dodecad + Kalash_HGDP + Kashmiri_Pandit_Reich @ 3.365782
11 German_Dodecad + Indian_Dodecad + Kalash_HGDP + Pathan_HGDP @ 3.376734
12 German_Dodecad + Kalash_HGDP + Pakistani_Xing + Meghawal_Reich @ 3.413150
13 German_Dodecad + Kalash_HGDP + Pakistani_Xing + Srivastava_Reich @ 3.468611
14 Brahui_HGDP + FIN_1000Genomes + Indian_Dodecad + Kalash_HGDP @ 3.480638
15 German_Dodecad + Indian_Dodecad + Kalash_HGDP + Pakistani_Xing @ 3.508936
16 FIN_1000Genomes + Indian_Dodecad + Kalash_HGDP + Pathan_HGDP @ 3.517378
17 German_Dodecad + Kalash_HGDP + Sindhi_HGDP + Meghawal_Reich @ 3.546621
18 German_Dodecad + Kalash_HGDP + Sindhi_HGDP + Srivastava_Reich @ 3.558657
19 German_Dodecad + GIH_HapMap + Kalash_HGDP + Pathan_HGDP @ 3.561780
20 German_Dodecad + Kalash_HGDP + Pakistani_Xing + TN_Brahmin_Xing @ 3.562238

Done.

Elapsed time 0.6074 seconds.

EUtest Admixture Proportions

EUtest Admixture Proportions

This utility uses the Eurogenes EUtest model, created by Davidski (Polako). Questions and comments about this model
should be directed to him at his Eurogenes Ancestry Project blog.

Kit Number: M611023 Elapsed Time: 11.97 seconds


Population
SOUTH_BALTIC 6.04
EAST_EURO 14.38
NORTH-CENTRAL_EURO 8.54
ATLANTIC 5.21
WEST_MED -
EAST_MED 2.40
WEST_ASIAN 22.81
MIDDLE_EASTERN -
SOUTH_ASIAN 40.41
EAST_AFRICAN -
EAST_ASIAN -
SIBERIAN 0.19
WEST_AFRICAN -









Web site and contents ©Copyright 2011-2018 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions 'calculator' model remains the property of its developer.

141360 SNPs used in this evaluation

Oracle

GEDmatch.Com Oracle
This version of GEDmatch Oracle is based on 'Oracle v1' by Dienekes Pontikos. His original program was developed as part of the Dodecad Ancestry Project. More information on Dienekes' orignal program can be found here.

Many thanks also to Zack Ajmal for helping us get this web version of Dienekes' Oracle program developed.

EUtest Oracle results:
EUtest Oracle population reference data revised 06 Nov 2012.

Kit M611023

Admix Results (sorted):

# Population Percent
1 SOUTH_ASIAN 40.41
2 WEST_ASIAN 22.81
3 EAST_EURO 14.38
4 NORTH-CENTRAL_EURO 8.54
5 SOUTH_BALTIC 6.04
6 ATLANTIC 5.21
7 EAST_MED 2.4
8 SIBERIAN 0.19
9 WEST_AFRICAN 0.03

Single Population Sharing:

# Population (source) Distance
1 Burusho 12.65
2 Kalash 12.66
3 Sindhi 14.03
4 Balochi 20.42
5 Brahui 21.09
6 IN 23.95
7 Gujarati 27.13
8 Bangladeshi 28.52
9 Lezgin 39.43
10 IR 40.8
11 Kurdish 43.43
12 TR 45.59
13 Serbian 45.7
14 RO 46.04
15 HU 46.55
16 AT 46.93
17 Udmurt 47.05
18 East_Russian 47.42
19 South_Indian 47.6
20 Erzya 48.16

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 78.9% Sindhi + 21.1% North_Swedish @ 4.9
2 79.2% Sindhi + 20.8% South_Finnish @ 5
3 79.2% Sindhi + 20.8% South_&_Central_Swedish @ 5.15
4 79.6% Sindhi + 20.4% EE @ 5.17
5 79.4% Sindhi + 20.6% NO @ 5.23
6 79% Sindhi + 21% East_Finnish @ 5.32
7 79.6% Sindhi + 20.4% DK @ 5.77
8 79% Sindhi + 21% West_Russian @ 5.79
9 78.7% Sindhi + 21.3% East_Russian @ 5.83
10 80.6% Sindhi + 19.4% LIT @ 5.89
11 79.7% Sindhi + 20.3% Belorussian @ 5.91
12 79.3% Sindhi + 20.7% PL @ 5.91
13 79.7% Sindhi + 20.3% IE @ 5.95
14 79.8% Sindhi + 20.2% Orcadian @ 5.95
15 79% Sindhi + 21% Erzya @ 5.98
16 80.1% Sindhi + 19.9% Scottish @ 6
17 79.4% Sindhi + 20.6% North_Russian @ 6
18 80.2% Sindhi + 19.8% Northwest_Russian @ 6.02
19 79.1% Sindhi + 20.9% Ukrainian-Russian @ 6.14
20 79.4% Sindhi + 20.6% UA @ 6.23


Oracle-4

Kit Num: M611023
Threshold of components set to 1.000
Threshold of method set to 0.25%
Personal data has been read. 20 approximations mode.
Gedmatch.Com
EUtest 4-Ancestors Oracle
This program is based on 4-Ancestors Oracle Version 0.96 by Alexandr Burnashev.
Questions about results should be sent to him at: Alexandr.Burnashev@gmail.com
Original concept proposed by Sergey Kozlov.
Many thanks to Alexandr for helping us get this web version developed.

EUtest Oracle population reference data revised 06 Nov 2012.

Admix Results (sorted):

# Population Percent
1 SOUTH_ASIAN 40.41
2 WEST_ASIAN 22.81
3 EAST_EURO 14.38
4 NORTH-CENTRAL_EURO 8.54
5 SOUTH_BALTIC 6.04
6 ATLANTIC 5.21
7 EAST_MED 2.40


Finished reading population data. 78 populations found.
13 components mode.

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

Least-squares method.

Using 1 population approximation:
1 Burusho @ 12.943749
2 Kalash @ 14.431000
3 Sindhi @ 15.548518
4 Balochi @ 23.646452
5 Brahui @ 24.427879
6 IN @ 25.689844
7 Gujarati @ 29.042265
8 Bangladeshi @ 29.992252
9 Lezgin @ 43.094360
10 IR @ 45.854649
11 Kurdish @ 48.798050
12 Serbian @ 49.515755
13 RO @ 49.889900
14 Udmurt @ 50.106464
15 HU @ 50.354832
16 TR @ 50.438099
17 AT @ 50.978699
18 Komi @ 50.996265
19 South_Indian @ 51.233082
20 East_Russian @ 51.384666

Using 2 populations approximation:
1 50% Kalash +50% Sindhi @ 11.927919


Using 3 populations approximation:
1 50% Kalash +25% North_Swedish +25% South_Indian @ 5.297345


Using 4 populations approximation:
+++++++++++++++++++++++++++++++++++++++++++++
1 Gujarati + Kalash + North_Swedish + Sindhi @ 4.320499
2 Gujarati + Kalash + Sindhi + South_&_Central_Swedish @ 4.610767
3 Gujarati + Kalash + NO + Sindhi @ 4.834973
4 Gujarati + Kalash + Sindhi + South_Finnish @ 4.874959
5 IN + Kalash + North_Swedish + Sindhi @ 4.926076
6 IN + Kalash + Sindhi + South_&_Central_Swedish @ 5.208840
7 EE + Gujarati + Kalash + Sindhi @ 5.263737
8 Gujarati + Kalash + PL + Sindhi @ 5.273301
9 East_Finnish + Gujarati + Kalash + Sindhi @ 5.274107
10 Kalash + Kalash + North_Swedish + South_Indian @ 5.297345
11 Gujarati + Kalash + Sindhi + West_Russian @ 5.351830
12 IN + Kalash + Sindhi + South_Finnish @ 5.380657
13 DK + Gujarati + Kalash + Sindhi @ 5.388185
14 IN + Kalash + NO + Sindhi @ 5.417751
15 Kalash + Kalash + South_&_Central_Swedish + South_Indian @ 5.475104
16 Gujarati + Kalash + Sindhi + West_&_Central_German @ 5.570788
17 Gujarati + Kalash + NL + Sindhi @ 5.661067
18 Kalash + Kalash + NO + South_Indian @ 5.662679
19 Gujarati + Kalash + Sindhi + UA @ 5.674891
20 Gujarati + Kalash + Orcadian + Sindhi @ 5.677062

Done.

Elapsed time 0.0849 seconds.

Eurogenes K9b Admixture Proportions

Eurogenes K9b Admixture Proportions

This utility uses the Eurogenes K9b model, created by Davidski (Polako). This model approximates the Geno 2.0 analysis. Questions and comments about this model
should be directed to him at his Project Blog.

Kit Number: M611023 Elapsed Time: 9.20 seconds


Population
Southwest_Asian 56.51
Native_American 3.02
Northeast_Asian 0.50
Mediterranean 5.12
North_European 20.97
Southeast_Asian 7.91
Oceanian 4.15
South_African 0.82
Sub-Saharan_African 1.00




Web site and contents ©Copyright 2011-2018 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions 'calculator' model remains the property of its developer.

107787 SNPs used in this evaluation

Ajeje Brazorf
06-04-2018, 03:38 PM
puntDNAL K13 Global Admixture Proportions

puntDNAL K13 Global Admixture Proportions

This calculator will be periodically updated as new data becomes available. Questions and comments about this calculator should be directed to Abdullahi Warsame at puntdnalking@gmail.com

Kit Number: M611023 Elapsed Time: 12.98 seconds


Population
West_Asia 34.15
NE_Europe 23.20
Americas 2.28
Siberia 1.17
Oceania 1.73
South_Asia 29.37
NE_Asia -
East_Africa 0.19
SE_Asia -
SW_Europe 6.40
SW_Asia 0.29
West_Africa 0.67
South_Africa 0.56









Web site and contents ©Copyright 2011-2018 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions 'calculator' model remains the property of its developer.

98681 SNPs used in this evaluation

Oracle

GEDmatch.Com Oracle
This version of GEDmatch Oracle is based on 'Oracle v1' by Dienekes Pontikos. His original program was developed as part of the Dodecad Ancestry Project. More information on Dienekes' orignal program can be found here.

Many thanks also to Zack Ajmal for helping us get this web version of Dienekes' Oracle program developed.

puntDNAL K13 Global Oracle results:
puntDNAL K13 Oracle

Kit M611023

Admix Results (sorted):

# Population Percent
1 West_Asia 34.15
2 South_Asia 29.37
3 NE_Europe 23.2
4 SW_Europe 6.4
5 Americas 2.28
6 Oceania 1.73
7 Siberia 1.17
8 West_Africa 0.67
9 South_Africa 0.56
10 SW_Asia 0.29
11 East_Africa 0.19

Single Population Sharing:

# Population (source) Distance
1 Pakistan_Pashtun 11.74
2 Burusho 12.11
3 Afghan_Pashtun 12.59
4 Kashmir_Pandit 12.72
5 Pathan 13.61
6 Punjabi 14.93
7 Sindhi 15.76
8 Tadjik 17.23
9 Balochi 18.33
10 Makrani 19.56
11 Brahui 20.03
12 Romani 22.35
13 Afghan_Uzbeki 22.77
14 Tamil_Nadu_Brahmin 24.42
15 Bengali 26.6
16 Kumyk 28.56
17 Chechen 29.13
18 Dagestan_Azeri 30.58
19 Nogay 31.08
20 Iranian 31.17

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 78% Punjabi + 22% Belarusian @ 3.36
2 79.4% Punjabi + 20.6% Estonian @ 3.39
3 78.7% Punjabi + 21.3% Polish @ 3.41
4 79.7% Punjabi + 20.3% Lithuanian @ 3.55
5 78.1% Punjabi + 21.9% Russian @ 3.57
6 77.3% Punjabi + 22.7% Mordovian @ 3.61
7 78.6% Punjabi + 21.4% Swedish @ 3.63
8 79.7% Punjabi + 20.3% Latvian @ 3.65
9 78.2% Punjabi + 21.8% Norwegian @ 3.71
10 77% Punjabi + 23% Ukrainian @ 3.75
11 80.3% Kashmir_Pandit + 19.7% Mordovian @ 4.02
12 81.6% Kashmir_Pandit + 18.4% Polish @ 4.02
13 77.5% Punjabi + 22.5% German_North @ 4.06
14 81.1% Kashmir_Pandit + 18.9% Russian @ 4.09
15 81% Kashmir_Pandit + 19% Belarusian @ 4.1
16 82.3% Kashmir_Pandit + 17.7% Estonian @ 4.14
17 82.5% Kashmir_Pandit + 17.5% Lithuanian @ 4.16
18 82.6% Kashmir_Pandit + 17.4% Latvian @ 4.19
19 80.1% Kashmir_Pandit + 19.9% Ukrainian @ 4.19
20 76.5% Punjabi + 23.5% Slovak @ 4.32


Oracle-4

Kit Num: M611023
Threshold of components set to 1.000
Threshold of method set to 0.25%
Personal data has been read. 20 approximations mode.
Gedmatch.Com
puntDNAL K13 Global 4-Ancestors Oracle
This program is based on 4-Ancestors Oracle Version 0.96 by Alexandr Burnashev.
Questions about results should be sent to him at: Alexandr.Burnashev@gmail.com
Original concept proposed by Sergey Kozlov.
Many thanks to Alexandr for helping us get this web version developed.

puntDNAL K13 Oracle

Admix Results (sorted):

# Population Percent
1 West_Asia 34.15
2 South_Asia 29.37
3 NE_Europe 23.20
4 SW_Europe 6.40
5 Americas 2.28
6 Oceania 1.73
7 Siberia 1.17


Finished reading population data. 191 populations found.
13 components mode.

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

Least-squares method.

Using 1 population approximation:
1 Pakistan_Pashtun @ 12.749736
2 Burusho @ 13.080748
3 Afghan_Pashtun @ 13.728794
4 Kashmir_Pandit @ 13.924621
5 Pathan @ 14.756171
6 Punjabi @ 16.290731
7 Sindhi @ 17.113295
8 Tadjik @ 18.863594
9 Balochi @ 19.965839
10 Makrani @ 21.245049
11 Brahui @ 21.819517
12 Romani @ 24.093121
13 Afghan_Uzbeki @ 24.687178
14 Tamil_Nadu_Brahmin @ 26.862020
15 Bengali @ 29.219336
16 Kumyk @ 31.250198
17 Chechen @ 31.976048
18 Dagestan_Azeri @ 33.443516
19 Iranian @ 33.876598
20 Nogay @ 33.885201

Using 2 populations approximation:
1 50% Kashmir_Pandit +50% Tadjik @ 9.013331


Using 3 populations approximation:
1 50% Punjabi +25% Punjabi +25% Ukrainian @ 3.886300


Using 4 populations approximation:
++++++++++++++++++++++++++++++++++++++++++++++++++ ++++++++++++++++++++++++++++++++++++++
1 Belarusian + Punjabi + Punjabi + Punjabi @ 3.843580
2 Mordovian + Punjabi + Punjabi + Punjabi @ 3.855141
3 Punjabi + Punjabi + Punjabi + Ukrainian @ 3.886300
4 Kashmir_Pandit + Mordovian + Punjabi + Punjabi @ 4.068404
5 Kashmir_Pandit + Punjabi + Punjabi + Ukrainian @ 4.089509
6 Punjabi + Punjabi + Punjabi + Russian @ 4.114704
7 Polish + Punjabi + Punjabi + Punjabi @ 4.250413
8 Norwegian + Punjabi + Punjabi + Punjabi @ 4.275606
9 Belarusian + Kashmir_Pandit + Punjabi + Punjabi @ 4.278569
10 Balochi + Mordovian + Punjabi + Tamil_Nadu_Brahmin @ 4.307015
11 Makrani + Mordovian + Punjabi + Tamil_Nadu_Brahmin @ 4.347906
12 German_North + Punjabi + Punjabi + Punjabi @ 4.361727
13 Punjabi + Punjabi + Punjabi + Swedish @ 4.369121
14 Balochi + Punjabi + Russian + Tamil_Nadu_Brahmin @ 4.414511
15 Brahui + Mordovian + Punjabi + Tamil_Nadu_Brahmin @ 4.416202
16 Punjabi + Punjabi + Punjabi + Slovak @ 4.439336
17 Brahui + Punjabi + Russian + Tamil_Nadu_Brahmin @ 4.452137
18 Kashmir_Pandit + Punjabi + Punjabi + Russian @ 4.457644
19 Balochi + Latvian + Punjabi + Velamas @ 4.469537
20 Makrani + Punjabi + Russian + Tamil_Nadu_Brahmin @ 4.478455

Done.

Elapsed time 0.6125 seconds.

puntDNAL K15 Admixture Proportions

puntDNAL K15 Admixture Proportions

This calculator focuses primarily on Africa (particularly East Africa), West Asia, and Europe. If you are mostly African, West Asian, or European, then you will find it useful and Accurate. It will be periodically updated as new data becomes available. Questions and comments about this calculator should be directed to Abdullahi Warsame at puntdnalking@gmail.com

Click here for additional information.

Kit Number: M611023 Elapsed Time: 11.39 seconds


Population
S_Indian 32.25
Mediterranean 5.42
Siberian 1.46
Wht_Nile_River 0.82
Amerindian 1.59
S_African -
E_Asian -
Caucasian 31.60
NE_European 24.57
Omo_River -
W_African -
Horn_Of_Africa -
Oceanian 1.37
Beringian 0.12
SW_Asian 0.80









Web site and contents ©Copyright 2011-2018 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions 'calculator' model remains the property of its developer.

98464 SNPs used in this evaluation

Oracle

GEDmatch.Com Oracle
This version of GEDmatch Oracle is based on 'Oracle v1' by Dienekes Pontikos. His original program was developed as part of the Dodecad Ancestry Project. More information on Dienekes' orignal program can be found here.

Many thanks also to Zack Ajmal for helping us get this web version of Dienekes' Oracle program developed.

puntDNAL K15 Oracle results:
puntDNAL K15 Oracle

Kit M611023

Admix Results (sorted):

# Population Percent
1 S_Indian 32.25
2 Caucasian 31.6
3 NE_European 24.57
4 Mediterranean 5.42
5 Amerindian 1.59
6 Siberian 1.46
7 Oceanian 1.37
8 Wht_Nile_River 0.82
9 SW_Asian 0.8
10 Beringian 0.12

Single Population Sharing:

# Population (source) Distance
1 Pathan 12.37
2 Kashmiri 14.3
3 Pashtun 15.46
4 Burusho 15.63
5 Sindhi 18.89
6 UP_Brahmin 19.7
7 Tadjik 21.29
8 UP_Muslim 23.17
9 Romani 23.79
10 Tamil_Nadu_Brahmin 24.3
11 Balochi 27.89
12 Brahui 28.23
13 Turkmen 28.62
14 Bengali 29.39
15 Uzbek 29.43
16 Makrani 29.91
17 Kanjar 30.57
18 Tharus 32.2
19 Chechen 33.33
20 Iranian 34.08

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 74.5% Sindhi + 25.5% Finnish @ 2.64
2 74.1% Sindhi + 25.9% Karelian @ 2.69
3 74.1% Sindhi + 25.9% Russian @ 2.77
4 75.6% Sindhi + 24.4% Lithuanian @ 2.81
5 74.6% Sindhi + 25.4% Belarusian @ 2.88
6 80.5% Kashmiri + 19.5% Lithuanian @ 3.04
7 74.2% Sindhi + 25.8% Mordovian @ 3.06
8 79.8% Kashmiri + 20.2% Belarusian @ 3.36
9 79.4% Kashmiri + 20.6% Karelian @ 3.51
10 79.4% Kashmiri + 20.6% Russian @ 3.56
11 79.8% Kashmiri + 20.2% Finnish @ 3.59
12 74.2% Sindhi + 25.8% Polish @ 3.73
13 79.5% Kashmiri + 20.5% Mordovian @ 3.79
14 74% Sindhi + 26% Swedish @ 4.28
15 79.6% Kashmiri + 20.4% Polish @ 4.29
16 73.8% Sindhi + 26.2% Norwegian @ 4.75
17 79.6% Kashmiri + 20.4% Swedish @ 4.87
18 73.4% Sindhi + 26.6% North_German @ 4.97
19 72.4% Sindhi + 27.6% Slovenian @ 5.25
20 73.9% Sindhi + 26.1% Scottish @ 5.28


Oracle-4

Kit Num: M611023
Threshold of components set to 1.000
Threshold of method set to 0.25%
Personal data has been read. 20 approximations mode.
Gedmatch.Com
puntDNAL K15 4-Ancestors Oracle
This program is based on 4-Ancestors Oracle Version 0.96 by Alexandr Burnashev.
Questions about results should be sent to him at: Alexandr.Burnashev@gmail.com
Original concept proposed by Sergey Kozlov.
Many thanks to Alexandr for helping us get this web version developed.

puntDNAL K15 Oracle

Admix Results (sorted):

# Population Percent
1 S_Indian 32.25
2 Caucasian 31.60
3 NE_European 24.57
4 Mediterranean 5.42
5 Amerindian 1.59
6 Siberian 1.46
7 Oceanian 1.37


Finished reading population data. 157 populations found.
15 components mode.

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

Least-squares method.

Using 1 population approximation:
1 Pathan @ 13.750090
2 Kashmiri @ 15.899520
3 Burusho @ 17.126610
4 Pashtun @ 17.159285
5 Sindhi @ 21.053852
6 UP_Brahmin @ 22.039696
7 Tadjik @ 23.611940
8 UP_Muslim @ 25.915567
9 Romani @ 25.983809
10 Tamil_Nadu_Brahmin @ 27.180019
11 Balochi @ 31.169155
12 Uzbek @ 31.217499
13 Turkmen @ 31.383003
14 Brahui @ 31.522604
15 Bengali @ 32.837875
16 Makrani @ 33.339806
17 Kanjar @ 34.246941
18 Tharus @ 36.057312
19 Chechen @ 37.243031
20 Iranian @ 37.887501

Using 2 populations approximation:
1 50% Tadjik +50% UP_Brahmin @ 9.420666


Using 3 populations approximation:
1 50% Tadjik +25% UP_Brahmin +25% UP_Brahmin @ 9.420666


Using 4 populations approximation:
++++++++++++++++++++++++++++++++++++++++++++++++++ +++++++
1 Lithuanian + Kashmiri + Balochi + Tharus @ 2.592567
2 Karelian + Kashmiri + Sindhi + Sindhi @ 2.668069
3 Finnish + Sindhi + Sindhi + Sindhi @ 2.681161
4 Lithuanian + Kashmiri + Brahui + Tharus @ 2.692699
5 Karelian + Kashmiri + Brahui + Kanjar @ 2.770035
6 Finnish + Kashmiri + Sindhi + Sindhi @ 2.777050
7 Russian + Kashmiri + Sindhi + Sindhi @ 2.786286
8 Lithuanian + Sindhi + Balochi + Tharus @ 2.797095
9 Russian + UP_Brahmin + Tamil_Nadu_Brahmin + Brahui @ 2.824942
10 Russian + UP_Brahmin + Sindhi + Sindhi @ 2.827673
11 Karelian + UP_Brahmin + Tamil_Nadu_Brahmin + Balochi @ 2.829259
12 Russian + UP_Brahmin + Tamil_Nadu_Brahmin + Balochi @ 2.831790
13 Karelian + UP_Brahmin + Tamil_Nadu_Brahmin + Brahui @ 2.832106
14 Karelian + Sindhi + Sindhi + Sindhi @ 2.838252
15 Lithuanian + Sindhi + Balochi + Kanjar @ 2.840882
16 Karelian + UP_Brahmin + UP_Muslim + Balochi @ 2.843058
17 Russian + UP_Brahmin + UP_Muslim + Balochi @ 2.845082
18 Russian + UP_Brahmin + UP_Muslim + Brahui @ 2.855786
19 Karelian + UP_Brahmin + UP_Muslim + Brahui @ 2.874776
20 Belarusian + Kashmiri + Sindhi + Sindhi @ 2.877430

Done.

Elapsed time 0.2617 seconds.

Gedrosia K12 Admixture Proportions

Gedrosia K12 Admixture Proportions

This calculator has been designed for individuals of predominately South Asian and West Asian ancestry for inferring gedrosian Balochi admixture. Since those populations were mostly used to source allele frequencies, individuals with majority ancestry from outside those regions will most likely find this calculator less accurate and informative.

Many Indian tribal populations were used to source S. Indian allele frequencies. Although the West Asian populations used are adequate, an update may be released in the future which will include a few more W Asian populations.

The Balochi signal peaks in the Balochi/Brahui/Makrani populations of Pakistan. The Bronze age Sintashta Steppe Herder signal in this calculator reflects genetic Eurasian steppe admixture in excess of what is included in the Caucasus or Balochi signals.

Also, since the genotype rate has been optimized for 23andMe users, users genotyped with FTDNA or Ancestry DNA will have slightly lower accurate results than 23andMe users.

For further questions, please contact the calculator creator at Dilawerkh4@gmail.com.

Click here for additional information.

Kit Number: M611023 Elapsed Time: 7.86 seconds


Population
S_INDIAN 29.17
SUB_SAHARAN -
EARLY_EUROPEAN_FARMERS 6.52
SW_ASIAN 1.96
W_SIBERIAN 0.47
SE_ASIAN -
BALOCHI 24.70
SINTASHTA_STEPPE_HERDERS 18.85
INDO_TIBETAN 0.81
CAUCASUS 15.14
E_AFRICAN -
E_SIBERIAN 2.38









Web site and contents ©Copyright 2011-2018 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions 'calculator' model remains the property of its developer.

89641 SNPs used in this evaluation

Oracle

GEDmatch.Com Oracle
This version of GEDmatch Oracle is based on 'Oracle v1' by Dienekes Pontikos. His original program was developed as part of the Dodecad Ancestry Project. More information on Dienekes' orignal program can be found here.

Many thanks also to Zack Ajmal for helping us get this web version of Dienekes' Oracle program developed.

Gedrosia K12 Oracle results:
Gedrosia K12 Oracle

Kit M611023

Admix Results (sorted):

# Population Percent
1 S_INDIAN 29.17
2 BALOCHI 24.7
3 SINTASHTA_STEPPE_HERDERS 18.85
4 CAUCASUS 15.14
5 EARLY_EUROPEAN_FARMERS 6.52
6 E_SIBERIAN 2.38
7 SW_ASIAN 1.96
8 INDO_TIBETAN 0.81
9 W_SIBERIAN 0.47

Single Population Sharing:

# Population (source) Distance
1 Pathan 12.27
2 GujaratiA 15.3
3 Punjabi_Sikh 15.49
4 Nepali 15.8
5 Sindhi 17.43
6 Kurds_SE 17.76
7 Pashtun_Afghan 18.9
8 Tajik_Pomiri 19
9 Tajik_Afghan 22.45
10 Uzbek_Afghan 22.57
11 GujaratiB 23.89
12 UP_Brahmin 24.41
13 Turkmen_Afghan 30.53
14 GujaratiC 32.55
15 Uzbek 32.88
16 Kurds_C 32.98
17 Kurds_F 34.83
18 Kurds_N 35.43
19 Kurds_E 35.57
20 Iranian 36.08

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 76.6% Sindhi + 23.4% Russian @ 5.07
2 76.2% Sindhi + 23.8% Norwegian @ 5.4
3 78% Sindhi + 22% Finnish @ 5.54
4 79% Sindhi + 21% Estonian @ 5.76
5 79.3% Sindhi + 20.7% Lithuanian @ 5.88
6 85.3% Pathan + 14.7% Estonian @ 6.04
7 56.2% GujaratiA + 43.8% Tajik_Pomiri @ 6.11
8 84.6% Pathan + 15.4% Finnish @ 6.12
9 85.6% Pathan + 14.4% Lithuanian @ 6.15
10 83.3% Pathan + 16.7% Norwegian @ 6.17
11 56.2% Tajik_Pomiri + 43.8% GujaratiB @ 6.32
12 56.8% Tajik_Pomiri + 43.2% UP_Brahmin @ 6.35
13 83.8% Pathan + 16.2% Russian @ 6.35
14 73.8% Tajik_Pomiri + 26.2% Piramalai @ 6.43
15 68% Tajik_Pomiri + 32% Meghawal @ 6.53
16 72% Tajik_Pomiri + 28% UP_Caste @ 6.63
17 70.7% Tajik_Pomiri + 29.3% Velamas @ 6.66
18 64.2% Tajik_Pomiri + 35.8% GujaratiC @ 6.74
19 76.9% GujaratiA + 23.1% Greek @ 6.74
20 72.7% Tajik_Pomiri + 27.3% Kurumba @ 6.76


Oracle-4

Kit Num: M611023
Threshold of components set to 1.000
Threshold of method set to 0.25%
Personal data has been read. 20 approximations mode.
Gedmatch.Com
Gedrosia K12 4-Ancestors Oracle
This program is based on 4-Ancestors Oracle Version 0.96 by Alexandr Burnashev.
Questions about results should be sent to him at: Alexandr.Burnashev@gmail.com
Original concept proposed by Sergey Kozlov.
Many thanks to Alexandr for helping us get this web version developed.

Gedrosia K12 Oracle

Admix Results (sorted):

# Population Percent
1 S_INDIAN 29.17
2 BALOCHI 24.70
3 SINTASHTA_STEPPE_HERDERS 18.85
4 CAUCASUS 15.14
5 EARLY_EUROPEAN_FARMERS 6.52
6 E_SIBERIAN 2.38
7 SW_ASIAN 1.96


Finished reading population data. 87 populations found.
12 components mode.

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

Least-squares method.

Using 1 population approximation:
1 Pathan @ 13.502405
2 GujaratiA @ 17.063900
3 Nepali @ 17.315796
4 Punjabi_Sikh @ 17.551556
5 Sindhi @ 19.282909
6 Kurds_SE @ 19.533035
7 Pashtun_Afghan @ 21.050352
8 Tajik_Pomiri @ 21.212429
9 Tajik_Afghan @ 23.886370
10 Uzbek_Afghan @ 24.309582
11 GujaratiB @ 26.751730
12 UP_Brahmin @ 27.517494
13 Turkmen_Afghan @ 32.189926
14 Uzbek @ 34.115074
15 GujaratiC @ 36.469120
16 Kurds_C @ 36.596535
17 Kurds_F @ 38.564587
18 Kurds_N @ 39.323654
19 Kurds_E @ 39.466106
20 Iranian @ 39.959415

Using 2 populations approximation:
1 50% GujaratiA +50% Tajik_Pomiri @ 6.962771


Using 3 populations approximation:
1 50% Kurds_SE +25% Russian +25% Velamas @ 4.452767


Using 4 populations approximation:
++++++++++++++++++++++++++++++++++++++++++++++++++ ++++++++++++
1 GujaratiC + Kurds_SE + Norwegian + Sindhi @ 4.359428
2 Kurds_SE + Kurds_SE + Russian + Velamas @ 4.452767
3 Kurds_SE + Meghawal + Norwegian + Pathan @ 4.487666
4 GujaratiC + Norwegian + Pashtun_Afghan + Sindhi @ 4.530982
5 GujaratiC + Kurds_SE + Russian + Sindhi @ 4.574636
6 Kurds_SE + Meghawal + Pathan + Russian @ 4.577322
7 GujaratiD + Kurds_SE + Norwegian + Pathan @ 4.583745
8 Greek + Punjabi_Sikh + Punjabi_Sikh + UP_Brahmin @ 4.603737
9 Meghawal + Norwegian + Pashtun_Afghan + Sindhi @ 4.664014
10 Nepali + Norwegian + Pathan + Sindhi @ 4.699599
11 GujaratiB + Kurds_SE + Norwegian + Sindhi @ 4.705339
12 GujaratiC + Kurds_SE + Norwegian + Pathan @ 4.709670
13 Kurds_SE + Pathan + Russian + Velamas @ 4.724498
14 Kurds_SE + Norwegian + Pathan + Velamas @ 4.724968
15 Nepali + Norwegian + Sindhi + Sindhi @ 4.734778
16 Meghawal + Pashtun_Afghan + Russian + Sindhi @ 4.737566
17 Kurds_SE + Kurds_SE + Norwegian + Velamas @ 4.750503
18 GujaratiB + Norwegian + Pathan + Sindhi @ 4.803952
19 Kurds_SE + Meghawal + Russian + Sindhi @ 4.842753
20 Kurds_SE + Kurds_SE + Kurumba + Russian @ 4.861632

Done.

Elapsed time 0.1356 seconds.

MDLP K23b Admixture Proportions

MDLP K23b Admixture Proportions

This utility uses the MDLP K23b calculator, created by Vadim Verenich. Questions and comments about this calculator
should be directed to him at vadimverenich@gmail.com or visit his Project Blog.

Kit Number: M611023 Elapsed Time: 10.43 seconds


Population
Amerindian -
Ancestral_Altaic 8.79
South_Central_Asian 31.30
Arctic 1.13
South_Indian 25.42
Australoid 0.93
Austronesian -
Caucasian 14.12
Archaic_Human 0.18
East_African -
East_Siberian -
European_Early_Farmers 1.33
Khoisan -
Melano_Polynesian 0.43
Archaic_African -
Near_East 1.33
North_African -
Paleo_Siberian 1.07
African_Pygmy -
South_East_Asian -
Subsaharian -
Tungus-Altaic -
European_Hunters_Gatherers 13.92









Web site and contents ©Copyright 2011-2018 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions 'calculator' model remains the property of its developer.

87794 SNPs used in this evaluation

Oracle

GEDmatch.Com Oracle
This version of GEDmatch Oracle is based on 'Oracle v1' by Dienekes Pontikos. His original program was developed as part of the Dodecad Ancestry Project. More information on Dienekes' orignal program can be found here.

Many thanks also to Zack Ajmal for helping us get this web version of Dienekes' Oracle program developed.

MDLP K23b Oracle results:
MDLP K23b Oracle Rev 2014 Sep 16

Kit M611023

Admix Results (sorted):

# Population Percent
1 South_Central_Asian 31.3
2 South_Indian 25.42
3 Caucasian 14.12
4 European_Hunters_Gatherers 13.92
5 Ancestral_Altaic 8.79
6 Near_East 1.33
7 European_Early_Farmers 1.33
8 Arctic 1.13
9 Paleo_Siberian 1.07
10 Australoid 0.93
11 Melano_Polynesian 0.43
12 Archaic_Human 0.18
13 Archaic_African 0.04
14 Khoisan 0.01

Single Population Sharing:

# Population (source) Distance
1 Pakistani_Pushtun ( ) 8.76
2 Pathan ( ) 9.31
3 Jatt_Haryana ( ) 9.39
4 Jatt_Pahari ( ) 10.68
5 Burusho ( ) 12.87
6 Punjabi_Gujjar ( ) 14.73
7 Pashtun_Afghani ( ) 15
8 Tajik_Pomiri_Ishkashim ( ) 15.92
9 Afghan_Pushtun ( ) 16.41
10 Jatt_Muslim ( ) 16.73
11 Mumbai_Jew ( ) 17.1
12 Cochin_Jew ( ) 17.3
13 Pakistani ( ) 18.36
14 Sindhi ( ) 19.3
15 GujaratiA_GIH ( ) 19.62
16 Tajik_Pomiri_Shugnan ( ) 20.05
17 Uzbek_Afghan ( ) 20.68
18 Tajik_Afghan ( ) 21.18
19 Tajik_Pomiri_Rushan ( ) 21.86
20 Tiwari ( ) 23.27

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 57.1% Tiwari ( ) + 42.9% Tajik_Yagnobi ( ) @ 2.2
2 51.1% Kshatriya ( ) + 48.9% Tajik_Yagnobi ( ) @ 2.36
3 70.5% Jatt_Haryana ( ) + 29.5% Tajik_Pomiri_Rushan ( ) @ 2.42
4 73.5% Tajik_Pomiri_Shugnan ( ) + 26.5% Kamsali ( ) @ 2.49
5 72% Tajik_Pomiri_Shugnan ( ) + 28% Scheduled_Caste_Tamil_Nadu ( ) @ 2.51
6 71% Tajik_Pomiri_Shugnan ( ) + 29% Lodhi ( ) @ 2.58
7 74.5% Tajik_Pomiri_Shugnan ( ) + 25.5% Sakilli ( ) @ 2.58
8 71.9% Tajik_Pomiri_Shugnan ( ) + 28.1% Dusadh ( ) @ 2.59
9 73.2% Tajik_Pomiri_Shugnan ( ) + 26.8% Kol ( ) @ 2.59
10 68.8% Jatt_Haryana ( ) + 31.2% Tajik_Pomiri_Shugnan ( ) @ 2.61
11 73.3% Tajik_Pomiri_Shugnan ( ) + 26.7% Vishwabrahmin ( ) @ 2.61
12 66.4% Tajik_Pomiri_Shugnan ( ) + 33.6% Srivastava ( ) @ 2.66
13 67.1% Tajik_Pomiri_Shugnan ( ) + 32.9% Muslim_India ( ) @ 2.68
14 72.7% Tajik_Pomiri_Shugnan ( ) + 27.3% Vysya ( ) @ 2.69
15 54.1% Hindi ( ) + 45.9% Tajik_Yagnobi ( ) @ 2.73
16 71.8% Tajik_Pomiri_Shugnan ( ) + 28.2% Scheduled_Caste_UP ( ) @ 2.73
17 77.4% Jatt_Haryana ( ) + 22.6% Tajik_Yagnobi ( ) @ 2.74
18 64.4% Tajik_Pomiri_Rushan ( ) + 35.6% Srivastava ( ) @ 2.77
19 71% Tajik_Pomiri_Shugnan ( ) + 29% Bhili ( ) @ 2.78
20 58.6% Tajik_Pomiri_Rushan ( ) + 41.4% Brahmins_UP ( ) @ 2.78


Oracle-4

Kit Num: M611023
Threshold of components set to 1.000
Threshold of method set to 0.25%
Personal data has been read. 20 approximations mode.
Gedmatch.Com
MDLP K23b 4-Ancestors Oracle
This program is based on 4-Ancestors Oracle Version 0.96 by Alexandr Burnashev.
Questions about results should be sent to him at: Alexandr.Burnashev@gmail.com
Original concept proposed by Sergey Kozlov.
Many thanks to Alexandr for helping us get this web version developed.

MDLP K23b Oracle Rev 2014 Sep 16

Admix Results (sorted):

# Population Percent
1 South_Central_Asian 31.30
2 South_Indian 25.42
3 Caucasian 14.12
4 European_Hunters_Gatherers 13.92
5 Ancestral_Altaic 8.79
6 Near_East 1.33
7 European_Early_Farmers 1.33
8 Arctic 1.13
9 Paleo_Siberian 1.07


Finished reading population data. 620 populations found.
23 components mode.

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

Least-squares method.

Using 1 population approximation:
1 Jatt_Haryana_ @ 9.190867
2 Pakistani_Pushtun_ @ 9.673857
3 Pathan_ @ 12.659650
4 Jatt_Pahari_ @ 13.974616
5 Afghan_Pushtun_ @ 14.276898
6 Pashtun_Afghani_ @ 14.588700
7 Tajik_Pomiri_Ishkashim_ @ 14.948660
8 Burusho_ @ 15.242933
9 Jatt_Muslim_ @ 16.618174
10 GujaratiA_GIH_ @ 17.478216
11 Punjabi_Gujjar_ @ 17.809448
12 Tajik_Pomiri_Shugnan_ @ 18.313629
13 Tajik_Pomiri_Rushan_ @ 19.539289
14 Pakistani_ @ 19.545677
15 Sindhi_ @ 20.502462
16 Tiwari_ @ 20.813353
17 Uzbek_Afghan_ @ 21.003252
18 Mumbai_Jew_ @ 21.118610
19 Tajik_Afghan_ @ 21.490572
20 Cochin_Jew_ @ 21.524839

Using 2 populations approximation:
1 50% Tajik_Pomiri_Rushan_ +50% Tiwari_ @ 3.688388


Using 3 populations approximation:
1 50% Jatt_Haryana_ +25% Jatt_Haryana_ +25% Tajik_Pomiri_Rushan_ @ 3.614710


Using 4 populations approximation:
++++++++++++++++++++++++++++++++++++++++++++++++++ ++++++++++++++++++++++++++++++++++++++++++++++++++ ++++++++++++++++++++++++++++++++++++++++++++++++++ ++++++++++++++++++++++++++++++++++++++++++++++++++ ++++++++++++++++++++++++++
1 Brahmins_UP_ + Jatt_Haryana_ + Tajik_Pomiri_Rushan_ + Tajik_Pomiri_Rushan_ @ 3.570931
2 Jatt_Haryana_ + Jatt_Haryana_ + Jatt_Haryana_ + Tajik_Pomiri_Rushan_ @ 3.614710
3 Brahmins_UP_ + Jatt_Haryana_ + Tajik_Pomiri_Rushan_ + Tajik_Pomiri_Shugnan_ @ 3.616963
4 Jatt_Haryana_ + Tajik_Pomiri_Rushan_ + Tajik_Pomiri_Shugnan_ + Vaish_ @ 3.622496
5 Tajik_Pomiri_Rushan_ + Tajik_Pomiri_Rushan_ + Tiwari_ + Tiwari_ @ 3.688388
6 Jatt_Haryana_ + Tajik_Pomiri_Rushan_ + Tajik_Pomiri_Rushan_ + Vaish_ @ 3.713558
7 Tajik_Pomiri_Rushan_ + Tajik_Yagnobi_ + Tiwari_ + Tiwari_ @ 3.725312
8 Jatt_Haryana_ + Jatt_Haryana_ + Jatt_Haryana_ + Tajik_Yagnobi_ @ 3.752720
9 Jatt_Haryana_ + Tajik_Pomiri_Shugnan_ + Tajik_Pomiri_Shugnan_ + Vaish_ @ 3.755380
10 Tajik_Pomiri_Shugnan_ + Tajik_Yagnobi_ + Tiwari_ + Tiwari_ @ 3.772592
11 Jatt_Haryana_ + Srivastava_ + Tajik_Pomiri_Rushan_ + Tajik_Pomiri_Rushan_ @ 3.797115
12 Tajik_Pomiri_Rushan_ + Tajik_Pomiri_Shugnan_ + Tiwari_ + Tiwari_ @ 3.810190
13 Brahmins_UP_ + Jatt_Haryana_ + Tajik_Pomiri_Shugnan_ + Tajik_Pomiri_Shugnan_ @ 3.864945
14 Sakilli_ + Tajik_Pomiri_Rushan_ + Tajik_Pomiri_Shugnan_ + Tajik_Pomiri_Shugnan_ @ 3.870371
15 Dharkar_ + Jatt_Haryana_ + Tajik_Pomiri_Rushan_ + Tajik_Pomiri_Rushan_ @ 3.891831
16 Kol_ + Tajik_Pomiri_Ishkashim_ + Tajik_Pomiri_Rushan_ + Tajik_Pomiri_Shugnan_ @ 3.901889
17 Kol_ + Tajik_Pomiri_Rushan_ + Tajik_Pomiri_Shugnan_ + Tajik_Pomiri_Shugnan_ @ 3.908777
18 Jatt_Haryana_ + Srivastava_ + Tajik_Pomiri_Rushan_ + Tajik_Yagnobi_ @ 3.913238
19 Tajik_Pomiri_Rushan_ + Tajik_Yagnobi_ + Tiwari_ + Vaish_ @ 3.918337
20 Jatt_Pahari_ + Punjabi_Gujjar_ + Punjabi_Gujjar_ + Tatar_Kryashen_ @ 3.918780

Done.

Elapsed time 84.5530 seconds.

MDLP K11 Modern Admixture Proportions

MDLP K11 Modern Admixture Proportions

The K11 model of Admixture - waiting full description

Kit Number: M611023 Elapsed Time: 5.65 seconds


Population
African -
Amerindian 1.63
ASI 32.91
Basal 5.46
Iran-Mesolithic 6.72
Neolithic 4.81
Oceanic 0.86
EHG 33.27
SEA -
Siberian 1.53
WHG 12.82









Web site and contents ©Copyright 2011-2018 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions 'calculator' model remains the property of its developer.

75793 SNPs used in this evaluation

Oracle

GEDmatch.Com Oracle
This version of GEDmatch Oracle is based on 'Oracle v1' by Dienekes Pontikos. His original program was developed as part of the Dodecad Ancestry Project. More information on Dienekes' orignal program can be found here.

Many thanks also to Zack Ajmal for helping us get this web version of Dienekes' Oracle program developed.

MDLP K11 Modern Oracle results:
MDLP K11 2xOracle and OracleX4

Kit M611023

Admix Results (sorted):

# Population Percent
1 EHG 33.27
2 ASI 32.91
3 WHG 12.82
4 Iran-Mesolithic 6.72
5 Basal 5.46
6 Neolithic 4.81
7 Amerindian 1.63
8 Siberian 1.53
9 Oceanic 0.86

ERROR: FST Pops(10) not equal to N(11)

Oracle-4

Kit Num: M611023
Threshold of components set to 1.000
Threshold of method set to 0.25%
Personal data has been read. 20 approximations mode.
Gedmatch.Com
MDLP K11 Modern 4-Ancestors Oracle
This program is based on 4-Ancestors Oracle Version 0.96 by Alexandr Burnashev.
Questions about results should be sent to him at: Alexandr.Burnashev@gmail.com
Original concept proposed by Sergey Kozlov.
Many thanks to Alexandr for helping us get this web version developed.

MDLP K11 2xOracle and OracleX4

Admix Results (sorted):

# Population Percent
1 EHG 33.27
2 ASI 32.91
3 WHG 12.82
4 Iran-Mesolithic 6.72
5 Basal 5.46
6 Neolithic 4.81
7 Amerindian 1.63
8 Siberian 1.53


Finished reading population data. 161 populations found.
11 components mode.

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

Least-squares method.

Using 1 population approximation:
1 Iran_LN @ 28.695463
2 Iran_Mesolithic @ 29.895744
3 Iran_N @ 31.256344
4 Armenia_MBA @ 35.142067
5 Kostenki14_Upper_Paleolithic @ 36.309113
6 Ust_Ishim_Upper_Üaleolothic @ 36.372307
7 Armenia_LBA @ 36.749161
8 Scythian_IA @ 36.905231
9 Armenia_MLBA @ 38.631557
10 Russia_IA @ 39.539940
11 Siberian_Upper_Paleolithic @ 39.956024
12 Iran_Chalcolithic @ 40.199070
13 Oase1_Upper_Paleolithic @ 41.025154
14 Hungary_IronAge @ 41.146126
15 Armenia_Chalcolithic @ 41.317966
16 Mezhovskaya_LBA @ 43.214970
17 Armenia_EBA @ 43.221207
18 Unetice_MBA @ 43.326900
19 Karsdorf_LN @ 43.547989
20 Russia_EBA @ 43.550560

Using 2 populations approximation:
1 50% Iran_Mesolithic +50% Kostenki14_Upper_Paleolithic @ 15.755218


Using 3 populations approximation:
1 50% Iran_Mesolithic +25% Ust_Ishim_Upper_Üaleolothic +25% Vestonice15_Gravettian @ 13.978995


Using 4 populations approximation:
++++++++++++++++++++++++++++++++++++++++++++++++++ ++++++++++++++++++++++++++++++++++++++++++++++++++ +++++++++++++++++++++++++++++++++++++++++++
1 Iran_Mesolithic + Iran_Mesolithic + Ust_Ishim_Upper_Üaleolothic + Vestonice15_Gravettian @ 13.978995
2 Iran_Mesolithic + Iran_Mesolithic + Pavlov1_Gravettian + Ust_Ishim_Upper_Üaleolothic @ 14.079647
3 Iran_Mesolithic + Iran_Mesolithic + Ust_Ishim_Upper_Üaleolothic + Vestonice16_Gravettian @ 14.474164
4 Iran_Mesolithic + Iran_Mesolithic + Oase1_Upper_Paleolithic + Vestonice15_Gravettian @ 14.643650
5 Iran_Mesolithic + Iran_Mesolithic + Kostenki14_Upper_Paleolithic + Ust_Ishim_Upper_Üaleolothic @ 14.656863
6 Iran_Mesolithic + Iran_Mesolithic + Ostuni2_Gravettian + Ust_Ishim_Upper_Üaleolothic @ 14.910824
7 Iran_Mesolithic + Iran_Mesolithic + Oase1_Upper_Paleolithic + Pavlov1_Gravettian @ 15.065591
8 Iran_Mesolithic + Iran_Mesolithic + Kostenki14_Upper_Paleolithic + Oase1_Upper_Paleolithic @ 15.094383
9 Iran_Mesolithic + Iran_Mesolithic + Ust_Ishim_Upper_Üaleolothic + Vestonice13_Gravettian @ 15.153491
10 Iran_Mesolithic + Iran_Mesolithic + Oase1_Upper_Paleolithic + Vestonice16_Gravettian @ 15.277142
11 Iran_Mesolithic + Iran_Mesolithic + Ostuni1_Gravettian + Ust_Ishim_Upper_Üaleolothic @ 15.362681
12 Iran_Mesolithic + Iran_Mesolithic + Oase1_Upper_Paleolithic + Vestonice13_Gravettian @ 15.628398
13 HohleFels79_Magdalenian + Iran_Mesolithic + Iran_Mesolithic + Ust_Ishim_Upper_Üaleolothic @ 15.710736
14 Iran_Mesolithic + Iran_Mesolithic + Paglicci138_Gravettian + Ust_Ishim_Upper_Üaleolothic @ 15.750934
15 Iran_Mesolithic + Iran_Mesolithic + Kostenki14_Upper_Paleolithic + Kostenki14_Upper_Paleolithic @ 15.755218
16 Iran_LN + Iran_Mesolithic + Ust_Ishim_Upper_Üaleolothic + Vestonice15_Gravettian @ 15.878488
17 Iran_Mesolithic + Iran_Mesolithic + Kostenki14_Upper_Paleolithic + Ostuni2_Gravettian @ 15.888276
18 Iran_Mesolithic + Iran_Mesolithic + KremsWA3_Gravettian + Ust_Ishim_Upper_Üaleolothic @ 15.932293
19 Iran_Mesolithic + Iran_Mesolithic + Oase1_Upper_Paleolithic + Ostuni2_Gravettian @ 16.011906
20 Iran_N + Iran_Mesolithic + Ust_Ishim_Upper_Üaleolothic + Vestonice15_Gravettian @ 16.014904

Done.

Elapsed time 2.6764 seconds.

MDLP World-22 Admixture Proportions

MDLP World-22 Admixture Proportions

Magnus Ducatus Lituaniae Project MDLP World-22 Populations

For questions or comments about this project or your results, please email vadimverenich@gmail.com or visit the Magnus Ducatus Lituaniae Project or MDLP behind the curtains

Kit Number: M611023 Elapsed Time: 6.99 seconds


Population
Pygmy -
West-Asian 32.60
North-European-Mesolithic 3.91
Indo-Tibetan 1.31
Mesoamerican 1.07
Arctic-Amerind -
South-America_Amerind 0.62
Indian 25.58
North-Siberean -
Atlantic_Mediterranean_Neolithic 5.37
Samoedic 3.92
Indo-Iranian 7.42
East-Siberean -
North-East-European 16.68
South-African -
North-Amerind -
Sub-Saharian -
East-South-Asian -
Near_East -
Melanesian 0.14
Paleo-Siberian -
Austronesian 1.36









Web site and contents ©Copyright 2011-2018 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions 'calculator' model remains the property of its developer.

68874 SNPs used in this evaluation

Oracle

GEDmatch.Com Oracle
This version of GEDmatch Oracle is based on 'Oracle v1' by Dienekes Pontikos. His original program was developed as part of the Dodecad Ancestry Project. More information on Dienekes' orignal program can be found here.

Many thanks also to Zack Ajmal for helping us get this web version of Dienekes' Oracle program developed.

MDLP World-22 Oracle results:
Kit M611023

Admix Results (sorted):

# Population Percent
1 West-Asian 32.6
2 Indian 25.58
3 North-East-European 16.68
4 Indo-Iranian 7.42
5 Atlantic_Mediterranean_Neolithic 5.37
6 Samoedic 3.92
7 North-European-Mesolithic 3.91
8 Austronesian 1.36
9 Indo-Tibetan 1.31
10 Mesoamerican 1.07
11 South-America_Amerind 0.62
12 Melanesian 0.14
13 South-African 0.02

Single Population Sharing:

# Population (source) Distance
1 Pathan (derived) 11.31
2 Burusho (derived) 12.63
3 Pashtun (derived) 14.06
4 Tadjik (derived) 14.7
5 Sindhi (derived) 18.46
6 Balochi (derived) 19.36
7 Makrani (derived) 22.3
8 Brahui (derived) 22.85
9 Turkmen (derived) 23.39
10 Parsi (derived) 23.47
11 Jew_India (derived) 23.72
12 Roma (derived) 23.92
13 Uzbek (derived) 27.38
14 Nogai (derived) 27.47
15 Kumyk (derived) 29.38
16 Tabassaran (derived) 29.89
17 Cirkassian (derived) 30.15
18 Balkarian (derived) 30.54
19 Lak (derived) 30.73
20 Lezgin (derived) 30.96

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 83.4% Pathan (derived) + 16.6% Swedish_V (derived) @ 3.88
2 83.9% Tadjik (derived) + 16.1% Indian (ancestral) @ 4.16
3 83.5% Pathan (derived) + 16.5% Swedish (derived) @ 4.18
4 83.2% Pathan (derived) + 16.8% Norwegian_V (derived) @ 4.32
5 83.4% Pathan (derived) + 16.6% German-North (derived) @ 4.46
6 82.7% Pathan (derived) + 17.3% German (derived) @ 4.48
7 84% Pathan (derived) + 16% Russian_North (derived) @ 4.52
8 84% Pathan (derived) + 16% Finnish (derived) @ 4.55
9 83.6% Pathan (derived) + 16.4% Slovakian (derived) @ 4.61
10 83.2% Pathan (derived) + 16.8% CEU_V (derived) @ 4.62
11 83.6% Pathan (derived) + 16.4% Czech (derived) @ 4.63
12 83.6% Pathan (derived) + 16.4% Welsh (derived) @ 4.63
13 84.1% Pathan (derived) + 15.9% Inkeri (derived) @ 4.64
14 84.6% Pathan (derived) + 15.4% Sorb (derived) @ 4.66
15 84.7% Pathan (derived) + 15.3% Belarusian_V (derived) @ 4.7
16 84.4% Pathan (derived) + 15.6% Russian_V (derived) @ 4.74
17 83.8% Pathan (derived) + 16.2% Orcadian (derived) @ 4.75
18 84.4% Pathan (derived) + 15.6% Karelian (derived) @ 4.75
19 83.3% Pathan (derived) + 16.7% CEU (derived) @ 4.76
20 81.9% Pathan (derived) + 18.1% Komi (derived) @ 4.78


Oracle-4

Kit Num: M611023
Threshold of components set to 1.000
Threshold of method set to 0.25%
Personal data has been read. 20 approximations mode.
Gedmatch.Com
MDLP World-22 4-Ancestors Oracle
This program is based on 4-Ancestors Oracle Version 0.96 by Alexandr Burnashev.
Questions about results should be sent to him at: Alexandr.Burnashev@gmail.com
Original concept proposed by Sergey Kozlov.
Many thanks to Alexandr for helping us get this web version developed.

Admix Results (sorted):

# Population Percent
1 West-Asian 32.60
2 Indian 25.58
3 North-East-European 16.68
4 Indo-Iranian 7.42
5 Atlantic_Mediterranean_Neolithic 5.37
6 Samoedic 3.92
7 North-European-Mesolithic 3.91
8 Austronesian 1.36
9 Indo-Tibetan 1.31
10 Mesoamerican 1.07


Finished reading population data. 276 populations found.
22 components mode.

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

Least-squares method.

Using 1 population approximation:
1 Pathan_derived @ 12.833551
2 Burusho_derived @ 14.262470
3 Pashtun_derived @ 15.983342
4 Tadjik_derived @ 16.608320
5 Sindhi_derived @ 20.620476
6 Balochi_derived @ 21.941339
7 Makrani_derived @ 24.769138
8 Brahui_derived @ 25.969683
9 Turkmen_derived @ 26.130989
10 Parsi_derived @ 26.395330
11 Roma_derived @ 26.410372
12 Jew_India_derived @ 26.856787
13 Uzbek_derived @ 30.519512
14 Nogai_derived @ 30.739826
15 Kumyk_derived @ 33.068768
16 Cirkassian_derived @ 33.792828
17 Tabassaran_derived @ 33.884289
18 Balkarian_derived @ 34.345463
19 Hazara_derived @ 34.833546
20 Lak_derived @ 34.834412

Using 2 populations approximation:
1 50% Hindu_derived +50% Tabassaran_derived @ 9.184277


Using 3 populations approximation:
1 50% Pathan_derived +25% Sindhi_derived +25% Tatar_Kryashen_derived @ 5.055761


Using 4 populations approximation:
++++++++++++++++++++++++++++++++++++++++++++++++++ ++++++++++++++++++++++++++++++++++++++++++++++++++ +++++++++++++
1 Brahui_derived + Hindu_derived + Komi_derived + Pashtun_derived @ 4.577714
2 Hindu_derived + Pashtun_derived + Pashtun_derived + Tatar_derived @ 4.645229
3 Brahui_derived + Hindu_derived + Pashtun_derived + Tartar_Mishar_derived @ 4.765210
4 Balochi_derived + Hindu_derived + Pashtun_derived + Tartar_Mishar_derived @ 4.793893
5 Brahui_derived + Hindu_derived + Pashtun_derived + Tatar_Kryashen_derived @ 4.833039
6 Balochi_derived + Hindu_derived + Komi_derived + Pashtun_derived @ 4.933137
7 Hindu_derived + Pashtun_derived + Pathan_derived + Tatar_derived @ 4.949373
8 Brahui_derived + Hindu_derived + Pashtun_derived + Tatar_derived @ 4.994383
9 Balochi_derived + Hindu_derived + Pashtun_derived + Tatar_derived @ 5.003666
10 Balochi_derived + Hindu_derived + Pashtun_derived + Tatar_Kryashen_derived @ 5.026418
11 Pathan_derived + Pathan_derived + Sindhi_derived + Tatar_Kryashen_derived @ 5.055761
12 Hindu_derived + Pashtun_derived + Pashtun_derived + Tartar_Mishar_derived @ 5.081414
13 Pathan_derived + Sindhi_derived + Sindhi_derived + Tatar_Kryashen_derived @ 5.086592
14 Jew_India_derived + Komi_derived + Pashtun_derived + Sindhi_derived @ 5.098156
15 Hindu_derived + Sindhi_derived + Tabassaran_derived + Tatar_derived @ 5.110692
16 Hindu_derived + Pashtun_derived + Pashtun_derived + Tatar_Kryashen_derived @ 5.117664
17 Hindu_derived + Lak_derived + Sindhi_derived + Tatar_derived @ 5.139207
18 Burusho_derived + German_derived + Pathan_derived + Sindhi_derived @ 5.147106
19 Burusho_derived + German_derived + Sindhi_derived + Sindhi_derived @ 5.182534
20 Hindu_derived + Pashtun_derived + Pathan_derived + Tartar_Mishar_derived @ 5.193472

Done.

Elapsed time 4.9838 seconds.

MDLP K16 Modern Admixture Proportions

MDLP K16 Modern Admixture Proportions

The K16 model of Admixture K16 focuses primarily on 16 worldwide basic, distich components of modern human ancestry, which have been discovered and detailed in Haak et al. (2014), Lazaridis et al. (2016). These components were empirically 'learned' in ADMIXTURE software from allele frequencies of learning merged dataset (116463 SNPs) of human populations, which, in their turn, had been converted into 'synthetic groups of individuals', with each of them representing one (of 16) ancestral populations. Then, the rest of dataset ('reference') was projected unto those ancestral populations with SNPWEIGHTS software: the results of component projection were averaged per each modern group of human population, and taken as 'population reference values' of component membership in 2xOracle and OracleX4.

These 16 component are briefly described below as follows:

Amerindian - a component, which is modal (i.e has a peak) in various native American groups of North and South America, as well as in ancient DNA of Native Americans (Clovis, Kennewick man, etc).

Ancestor - an archaic component, detected in modern African Pygmy populations (such as Mbuties and Biaka) and Khoisan hunter-gatherers.

Steppe - a component which was sourced from ancient genome of European Bronze Age pastoralists: it roughly approximates levels of ancient North Eurasian hunter-gatherers' heritage, which was subsequently shown to have an influence in later eastern hunter-gatherers and to have spread into Europe via an incursion of Steppe herders beginning ∼4,500 years ago.

Indian - a component of ancestry harboured by populations of Indian subcontinent

Arctic - a component displayed in genomes of Eskimo Inuits from Greenland and shared with Siberian Chukchis/Koryaks.

Australian - a component of aboriginal ancestry assigned to Australian aborigens.

Caucasian - a major component of ancestry of modern inhabitants of Caucasus, Iran and northern Indian : it was derived from genomes of mesolithic Caucasian Hunter-gatherers: a major ancestral component linked to CHG was carried west and east by migrating herders from the Eurasian Steppe.

EastAfrican - a very dilluted component being inherited specififically from ancient inhabitants of Ethiopia and African Horn

NorthEastEuropean - a fancy moniker for a dominant type of ancestry in North-Eastern Europe based on older type of ancestry (WHG, west European Hunter-Gatherer), today this type of ancestry peaks in the Baltic region and Scandinavia

NearEast - a component harboured and later carried by ancient populations of Near East, in our time it reaches the maximum among Bedoins and Saudi Arabians; the component seems to carry an excess of Eurasian Basal component relative to Neolithic component.

Neolithic - a component, modeled on genomes of first neolithic farmers of Anatolia (West Asia), these farmers from West Asia migrated to Europe during the Neolithic and carried this component with them.

NorthAfrican - a local component of ancestry found in North Africans: this local North African genetic component is very different from the one found in the populations in the south of the Sahara (Subsaharian component, see below).

Oceanic - a component of aboriginal ancestry assigned to aborigens of Melanesia and Papua-New-Guinea.

Siberian - a component, which is rougly ascribed to Central Siberian (found at highest frequency in Nganasan)

SouthEastAsian - a dominant component of South East Asians: being highest among the Dai, Cambodians, Lahu and Malay, this is the most common East Asian component among South Asians.

Subsaharian - a main component of ancestry seen in Yoruba, Mandenka and Luhya populations.

Kit Number: M611023 Elapsed Time: 6.54 seconds


Population
Amerindian 0.66
Ancestor 0.38
Steppe 13.15
Indian 41.93
Arctic 3.02
Australian 1.42
Caucasian 23.60
EastAfrican -
NorthEastEuropean 9.70
NearEast 0.71
Neolithic 4.08
NorthAfrican -
Oceanic 1.07
Siberian 0.27
SouthEastAsian -
Subsaharian -









Web site and contents ©Copyright 2011-2018 by GEDmatch, Inc.
Genealogy and DNA data remains the property of the submitter.
Each Admixture Proportions 'calculator' model remains the property of its developer.

67300 SNPs used in this evaluation

Oracle

GEDmatch.Com Oracle
This version of GEDmatch Oracle is based on 'Oracle v1' by Dienekes Pontikos. His original program was developed as part of the Dodecad Ancestry Project. More information on Dienekes' orignal program can be found here.

Many thanks also to Zack Ajmal for helping us get this web version of Dienekes' Oracle program developed.

MDLP K16 Modern Oracle results:
MDLP K16 2xOracle and OracleX4

Kit M611023

Admix Results (sorted):

# Population Percent
1 Indian 41.93
2 Caucasian 23.6
3 Steppe 13.15
4 NorthEastEuropean 9.7
5 Neolithic 4.08
6 Arctic 3.02
7 Australian 1.42
8 Oceanic 1.07
9 NearEast 0.71
10 Amerindian 0.66
11 Ancestor 0.38
12 Siberian 0.27

Single Population Sharing:

# Population (source) Distance
1 Jatt (Haryana) 7.1
2 Pathan (Punjab) 9.74
3 Pashtun (Pakistan) 9.88
4 Jatt (Pahari) 10.47
5 Kashmiri_Pandit (Kashmir) 11.83
6 Pashtun (Afganistan) 12.13
7 Jatt (Muslim) 12.73
8 Pashtun (Afghanistan) 12.94
9 Ishkasim (Gorno-Badakhshan) 13.11
10 Brahmin (India) 13.42
11 Tajik (Pomiri_Tajikistan) 14.16
12 Burusho (Pakistan) 14.24
13 Jew (Mumbai) 14.3
14 Gujjar (Punjab) 14.3
15 Shugnan (Badachshan) 14.31
16 Rushanvanch (Gorno-Badakhshan) 15.67
17 Balochi (Baluchistan) 16.5
18 Kshatriya (India) 16.74
19 Brahui (Baluchistan) 16.75
20 Jew (Cochin) 17.2

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 83.5% Pathan (Punjab) + 16.5% Latvian_Cesis (Cesis) @ 3.54
2 83.9% Pathan (Punjab) + 16.1% Latvian_Dobele (Dobele) @ 3.55
3 83.9% Pathan (Punjab) + 16.1% Estonian (Estonia) @ 3.73
4 84% Pathan (Punjab) + 16% Latvian (Latvia) @ 3.77
5 82.6% Pathan (Punjab) + 17.4% Ukrainians_north (NorthUkraine) @ 3.79
6 82.9% Pathan (Punjab) + 17.1% Cossack (Kuban) @ 3.8
7 83.9% Pathan (Punjab) + 16.1% Lithuanian (Lithuania) @ 3.81
8 83.7% Pathan (Punjab) + 16.3% Ingrians (Ingermanland) @ 3.82
9 83.5% Pathan (Punjab) + 16.5% Russians-West (WestRussian) @ 3.86
10 83.4% Pathan (Punjab) + 16.6% Finn (WestFinland) @ 3.88
11 83.9% Pathan (Punjab) + 16.1% Norwegian (Norwegia) @ 3.89
12 83.9% Pathan (Punjab) + 16.1% Icelandic (Iceland) @ 3.91
13 83.4% Pathan (Punjab) + 16.6% Belarusian (Belarus) @ 3.95
14 56.7% Shugnan (Badachshan) + 43.3% GujaratiA (Gujarat) @ 3.97
15 83.7% Pathan (Punjab) + 16.3% Finn (EastFinland) @ 3.98
16 83.2% Pathan (Punjab) + 16.8% Ukrainians_east (EastUkraine) @ 3.98
17 83.3% Pathan (Punjab) + 16.7% Pole (WestPoland) @ 4
18 83.1% Pathan (Punjab) + 16.9% Russian (Tver) @ 4
19 83.4% Pathan (Punjab) + 16.6% Russian (CentralRussia) @ 4
20 82.7% Pathan (Punjab) + 17.3% Belarusian_East (EastBelarus) @ 4.01


Oracle-4

Kit Num: M611023
Threshold of components set to 1.000
Threshold of method set to 0.25%
Personal data has been read. 20 approximations mode.
Gedmatch.Com
MDLP K16 Modern 4-Ancestors Oracle
This program is based on 4-Ancestors Oracle Version 0.96 by Alexandr Burnashev.
Questions about results should be sent to him at: Alexandr.Burnashev@gmail.com
Original concept proposed by Sergey Kozlov.
Many thanks to Alexandr for helping us get this web version developed.

MDLP K16 2xOracle and OracleX4

Admix Results (sorted):

# Population Percent
1 Indian 41.93
2 Caucasian 23.60
3 Steppe 13.15
4 NorthEastEuropean 9.70
5 Neolithic 4.08
6 Arctic 3.02
7 Australian 1.42
8 Oceanic 1.07


Finished reading population data. 517 populations found.
16 components mode.

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

Least-squares method.

Using 1 population approximation:
1 Jatt_Haryana @ 7.242921
2 Pashtun_Pakistan @ 10.685058
3 Pathan_Punjab @ 10.894567
4 Jatt_Pahari @ 11.823330
5 Kashmiri_Pandit_Kashmir @ 12.880397
6 Pashtun_Afganistan @ 14.001331
7 Jatt_Muslim @ 14.291510
8 Pashtun_Afghanistan @ 14.741991
9 Brahmin_India @ 15.103119
10 Ishkasim_Gorno-Badakhshan @ 15.113289
11 Jew_Mumbai @ 15.435000
12 Burusho_Pakistan @ 15.622498
13 Gujjar_Punjab @ 16.295294
14 Tajik_Pomiri_Tajikistan @ 16.585136
15 Shugnan_Badachshan @ 16.784403
16 Rushanvanch_Gorno-Badakhshan @ 18.384787
17 Balochi_Baluchistan @ 18.624205
18 Brahui_Baluchistan @ 18.889759
19 Jew_Cochin @ 18.915646
20 Kshatriya_India @ 19.119747

Using 2 populations approximation:
1 50% GujaratiA_Gujarat +50% Yaghnobi_Zarafshan @ 4.671869


Using 3 populations approximation:
1 50% GujaratiA_Gujarat +25% Shugnan_Badachshan +25% Yaghnobi_Zarafshan @ 4.029422


Using 4 populations approximation:
++++++++++++++++++++++++++++++++++++++++++++++++++ ++++++++++++++++++++++++++++++++++++++++++++++++++ ++++++++++++++++++++++++++++++++++++++++++++++++++ ++++++++++++++++++++++++++++++++++++++++++++++++++ ++++++++++++++++++++++++++++++++++++++++++++++++++ ++++++++++++++++++++++++++++++++++++++++++++++++++
1 GujaratiA_Gujarat + GujaratiA_Gujarat + Shugnan_Badachshan + Yaghnobi_Zarafshan @ 4.029422
2 GujaratiA_Gujarat + Jatt_Pahari + Shugnan_Badachshan + Shugnan_Badachshan @ 4.136041
3 Balochi_Baluchistan + Latvian_Cesis_Cesis + Sindhi_Sindh + Sindhi_Sindh @ 4.148361
4 Brahui_Baluchistan + Latvian_Cesis_Cesis + Sindhi_Sindh + Sindhi_Sindh @ 4.155049
5 Brahui_Baluchistan + Latvian_Cesis_Cesis + Gujjar_Punjab + Sindhi_Sindh @ 4.244230
6 Balochi_Baluchistan + Latvian_Cesis_Cesis + Gujjar_Punjab + Sindhi_Sindh @ 4.254479
7 Brahui_Baluchistan + GujaratiA_Gujarat + Latvian_Cesis_Cesis + Gujjar_Punjab @ 4.303222
8 Balochi_Baluchistan + GujaratiA_Gujarat + Latvian_Cesis_Cesis + Gujjar_Punjab @ 4.326271
9 GujaratiA_Gujarat + GujaratiA_Gujarat + Tajik_Pomiri_Tajikistan + Yaghnobi_Zarafshan @ 4.335070
10 Cossack_Kuban + Pathan_Punjab + Gujjar_Punjab + Sindhi_Sindh @ 4.339111
11 GujaratiA_Gujarat + Jatt_Pahari + Shugnan_Badachshan + Tajik_Pomiri_Tajikistan @ 4.353020
12 Brahui_Baluchistan + Cossack_Kuban + GujaratiA_Gujarat + Gujjar_Punjab @ 4.366462
13 GujaratiA_Gujarat + GujaratiA_Gujarat + Rushanvanch_Gorno-Badakhshan + Yaghnobi_Zarafshan @ 4.375222
14 GujaratiA_Gujarat + Pathan_Punjab + Shugnan_Badachshan + Shugnan_Badachshan @ 4.381486
15 Brahui_Baluchistan + Finn_EastFinland + Gujjar_Punjab + Sindhi_Sindh @ 4.383555
16 Balochi_Baluchistan + Cossack_Kuban + GujaratiA_Gujarat + Gujjar_Punjab @ 4.384739
17 Balochi_Baluchistan + Finn_EastFinland + Gujjar_Punjab + Sindhi_Sindh @ 4.389037
18 Pathan_Punjab + Gujjar_Punjab + Sindhi_Sindh + Ukrainians_north_NorthUkraine @ 4.402833
19 GujaratiA_Gujarat + GujaratiA_Gujarat + Shugnan_Badachshan + Dargin_Urkarah @ 4.417243
20 Belarusian_Kobryn_Brest + Brahui_Baluchistan + GujaratiA_Gujarat + Gujjar_Punjab @ 4.421618

Done.

Elapsed time 101.3172 seconds.

lameduck
06-04-2018, 03:43 PM
strong steppe influence in Jatts

Leto
06-04-2018, 03:44 PM
He seems to have an additional amount of white blood compared to the reference value.

Ajeje Brazorf
06-04-2018, 03:55 PM
He seems to have an additional amount of white blood compared to the reference value.

I think he's fully native:
1 haryana-jatt_harappa @ 4.178029

Also note the purely Steppe nature of this individual:
# Population Percent
1 South_Asian 38.43
2 West_Asian 23.6
3 North_Sea 13.64
4 Eastern_Euro 12.1
5 Baltic 5.75
6 Atlantic 2.5
7 Amerindian 1.53
8 East_Med 1.39
9 Oceanian 0.89
10 Sub-Saharan 0.17

Ajeje Brazorf
06-04-2018, 03:59 PM
strong steppe influence in Jatts

Exactly, they are peasants and apparently have more Steppe than other high-class Indian groups.

Leto
06-04-2018, 04:17 PM
I think he's fully native:
1 haryana-jatt_harappa @ 4.178029

Also note the purely Steppe nature of this individual:
# Population Percent
1 South_Asian 38.43
2 West_Asian 23.6
3 North_Sea 13.64
4 Eastern_Euro 12.1
5 Baltic 5.75
6 Atlantic 2.5
7 Amerindian 1.53
8 East_Med 1.39
9 Oceanian 0.89
10 Sub-Saharan 0.17
I've never seen a South Asian with such a high percentage of European before. Even Afghans usually don't have as much

Atlantic_Med 5.85
North_European 20.97
An average Pashtun is more like 15% NE and 0-3% AM.

Pandit
06-04-2018, 04:21 PM
Either you are a white or You are not.

Mixed people are different now, no point in counting how much "White" blood they have now.

Leto
06-04-2018, 04:26 PM
Either you are a white or You are not.

Mixed people are different now, no point in counting how much "White" blood they have now.
Then there's no point discussing the whole thing at all. By 'white' I half-jokingly mean European, Steppe or Aryan ancestry. Your comment is redundant.

Ajeje Brazorf
06-04-2018, 04:26 PM
I've never seen a South Asian with such a high percentage of European before. Even Afghans usually don't have as much

In the spreadsheet Haryana Jatts have 17% NE-Euro, while this individual has a slightly higher percentage and reaches 20%. Obviously the rest of the South Asians have less.

Pahli
06-04-2018, 04:28 PM
I've never seen a South Asian with such a high percentage of European before. Even Afghans usually don't have as much

An average Pashtun is more like 15% NE and 0-3% AM.

Only Yaghnobis and Pamiris have more NE_Euro and less South Asian

Leto
06-04-2018, 04:28 PM
In the spreadsheet Haryana Jatts have 17% NE-Euro, while this individual has a slightly higher percentage and reaches 20%. Obviously the rest of the South Asians have less.
Any info on his haplogroups?

Leto
06-04-2018, 04:31 PM
Only Yaghnobis and Pamiris have more NE_Euro and less South Asian
Yeah, and mainstream Tajikistanis are seriously mixed with Uzbeks. They are 15-20% mongoloid on average. Even back in the 1920s Tajikistan was like 25% Uzbek.

Pahli
06-04-2018, 04:32 PM
Yeah, and mainstream Tajikistanis are seriously mixed with Uzbeks. They are 15-20% mongoloid on average. Even back in the 1920s Tajikistan was like 25% Uzbek.

Pretty much, Pamiris managed to stay isolated in the East, which is also why they have less Mongoloid but more Steppe

Ajeje Brazorf
06-04-2018, 04:36 PM
Any info on his haplogroups?

I don't know his haplogroups

Leto
06-04-2018, 04:39 PM
Pretty much, Pamiris managed to stay isolated in the East, which is also why they have less Mongoloid but more Steppe
Have you seen the Yamnya guy from Central Kazakhstan (~4,900 years before present)? The sample quality is exceptionally good
https://www.theapricity.com/forum/showthread.php?245810-3-Steppe-GEDmatch-results-from-Damgaard-et-al&p=5161291&viewfull=1#post5161291

Ajeje Brazorf
06-04-2018, 10:23 PM
https://docs.google.com/spreadsheets/d/1XGY-UIBC2GcUWGl1FizNvu9ofle4ZPHvfNmbrVYxGMo
https://docs.google.com/spreadsheets/d/1mTH_BnLv9riKKwHeNpjFmu7flT6_ekTuYij0juxnjb4

lameduck
06-04-2018, 10:32 PM
I've never seen a South Asian with such a high percentage of European before. Even Afghans usually don't have as much

An average Pashtun is more like 15% NE and 0-3% AM.

There are samples from some North Pakistani ethnicities with 19-20 NE Euro on harrapa but even less South Indian than this Jatt.

Purohit ji
06-04-2018, 10:37 PM
Jaats have the highest euro/central asian but there are maNy other groups that are yet to be tested.

lameduck
06-04-2018, 10:45 PM
Jaats have the highest euro/central asian but there are maNy other groups that are yet to be tested.

yeah many groups in Pakistan/India hevent been tested yet.

dperucca
06-04-2018, 10:45 PM
In the spreadsheet Haryana Jatts have 17% NE-Euro, while this individual has a slightly higher percentage and reaches 20%. Obviously the rest of the South Asians have less.

What are the most common halpogroups amongst Punjabi people?

Purohit ji
06-05-2018, 08:07 AM
There are samples from some North Pakistani ethnicities with 19-20 NE Euro on harrapa but even less South Indian than this Jatt.
Which ethnicities . Please post complete result or link

Ajeje Brazorf
06-05-2018, 08:51 AM
What are the most common halpogroups amongst Punjabi people?

302 Jats = L (36.8%), R (28.5%), Q (15.6%), J (9.6%), E, G, H, I, T (9.5%)

Leto
06-05-2018, 09:05 AM
I've seen a few Chitrali Pakistani kits, they had like 15-20% North European too.

Ajeje Brazorf
06-05-2018, 09:27 AM
I've seen a few Chitrali Pakistani kits, they had like 15-20% North European too.

On which calculator?

Leto
06-05-2018, 09:29 AM
On which calculator?
Dodecad K12b for example.

StonyArabia
06-05-2018, 09:55 AM
The Aryans clearly made an impact

Kamal900
06-05-2018, 11:36 AM
The Aryans clearly made an impact

The same is true about the Arabs in the 7th century in the Levant :thumb001:

Ajeje Brazorf
06-05-2018, 01:37 PM
Which ethnicities . Please post complete result or link

The Chitrali with highest NE-Euro I have found is this one:



HarappaWorld
Kit T156535

# Population Percent
1 Baloch 34.72
2 NE-Euro 18.98
3 Caucasian 17.85
4 S-Indian 15.86
5 NE-Asian 4.04
6 Siberian 2.45
7 American 2.09
8 Mediterranean 2
9 Beringian 1.93
10 San 0.08

# Population (source) Distance
1 pashtun (harappa) 9.48
2 tajik (yunusbayev) 10.7
3 pathan (hgdp) 12.38
4 kalash (hgdp) 12.92
5 haryana-jatt (harappa) 13.28
6 burusho (hgdp) 13.73
7 punjabi-khatri (harappa) 15.4
8 sindhi (harappa) 15.59
9 punjabi-jatt-sikh (harappa) 15.68
10 bhatia (harappa) 16
11 kashmiri (harappa) 16.45
12 punjabi-jatt-muslim (harappa) 18.38
13 kashmiri-pandit (reich) 18.97
14 punjabi (harappa) 20
15 punjabi-brahmin (harappa) 20.18
16 turkmen (yunusbayev) 20.47
17 singapore-indian-c (sgvp) 20.8
18 nepalese-a (xing) 20.85
19 punjabi-arain (xing) 21.03
20 gujarati-muslim (harappa) 21.07

# Primary Population (source) Secondary Population (source) Distance
1 55.9% tajik (yunusbayev) + 44.1% haryana-jatt (harappa) @ 3.54
2 81.4% kalash (hgdp) + 18.6% russian (behar) @ 4.81
3 80.2% kalash (hgdp) + 19.8% mordovian (yunusbayev) @ 4.84
4 80.2% kalash (hgdp) + 19.8% ukranian (yunusbayev) @ 4.85
5 72.3% tajik (yunusbayev) + 27.7% up-brahmin (harappa) @ 4.91
6 67.3% tajik (yunusbayev) + 32.7% punjabi-brahmin (harappa) @ 4.92
7 61.1% tajik (yunusbayev) + 38.9% punjabi-jatt-sikh (harappa) @ 4.95
8 74.2% tajik (yunusbayev) + 25.8% brahmin-uttar-pradesh (metspalu) @ 4.98
9 81.7% kalash (hgdp) + 18.3% belorussian (behar) @ 5.04
10 68.5% haryana-jatt (harappa) + 31.5% stalskoe (xing) @ 5.06
11 60.7% tajik (yunusbayev) + 39.3% punjabi-khatri (harappa) @ 5.07
12 78.3% kalash (hgdp) + 21.7% chuvash (behar) @ 5.08
13 79.3% kalash (hgdp) + 20.7% slovenian (xing) @ 5.12
14 69.3% haryana-jatt (harappa) + 30.7% urkarah (xing) @ 5.13
15 68.4% tajik (yunusbayev) + 31.6% nepalese-a (xing) @ 5.22
16 68.3% tajik (yunusbayev) + 31.7% singapore-indian-c (sgvp) @ 5.25
17 79.1% kalash (hgdp) + 20.9% hungarian (behar) @ 5.25
18 71.1% haryana-jatt (harappa) + 28.9% lezgin (behar) @ 5.38
19 66.3% tajik (yunusbayev) + 33.7% kashmiri-pandit (reich) @ 5.44
20 76.3% tajik (yunusbayev) + 23.7% vaish (reich) @ 5.45

Using 1 population approximation:
1 pashtun_harappa @ 10.312273
2 tajik_yunusbayev @ 11.704757
3 pathan_hgdp @ 13.590567
4 kalash_hgdp @ 14.185414
5 haryana-jatt_harappa @ 14.681555
6 burusho_hgdp @ 15.131252
7 punjabi-khatri_harappa @ 16.945095
8 sindhi_harappa @ 17.139486
9 punjabi-jatt-sikh_harappa @ 17.306044
10 bhatia_harappa @ 17.613039
11 kashmiri_harappa @ 18.140388
12 pushtikar-brahmin_harappa @ 18.902483
13 rajasthani-brahmin_harappa @ 19.567549
14 punjabi-jatt-muslim_harappa @ 20.211288
15 nepali_harappa @ 20.505751
16 kashmiri-pandit_reich @ 20.937525
17 punjabi_harappa @ 22.073219
18 punjabi-brahmin_harappa @ 22.291056
19 turkmen_yunusbayev @ 22.530777
20 singapore-indian-c_sgvp @ 22.968975

Using 2 populations approximation:
1 50% haryana-jatt_harappa +50% tajik_yunusbayev @ 4.102673

Using 3 populations approximation:
1 50% haryana-jatt_harappa +25% tajik_yunusbayev +25% tajik_yunusbayev @ 4.102673

Using 4 populations approximation:
1 haryana-jatt_harappa + nepalese-a_xing + tajik_yunusbayev + urkarah_xing @ 3.441797
2 balochi_hgdp + burusho_hgdp + singapore-indian-d_sgvp + urkarah_xing @ 3.838457
3 brahui_hgdp + burusho_hgdp + singapore-indian-d_sgvp + urkarah_xing @ 4.006856
4 haryana-jatt_harappa + rajasthani-brahmin_harappa + tajik_yunusbayev + urkarah_xing @ 4.012163
5 haryana-jatt_harappa + haryana-jatt_harappa + tajik_yunusbayev + tajik_yunusbayev @ 4.102673
6 haryana-jatt_harappa + nepalese-a_xing + stalskoe_xing + tajik_yunusbayev @ 4.142271
7 haryana-jatt_harappa + haryana-jatt_harappa + tajik_yunusbayev + urkarah_xing @ 4.227292
8 nepalese-a_xing + rajasthani-brahmin_harappa + tajik_yunusbayev + urkarah_xing @ 4.305750
9 nepalese-a_xing + punjabi-jatt-sikh_harappa + tajik_yunusbayev + urkarah_xing @ 4.313712
10 haryana-jatt_harappa + rajasthani-brahmin_harappa + stalskoe_xing + tajik_yunusbayev @ 4.354100
11 burusho_hgdp + makrani_hgdp + singapore-indian-d_sgvp + urkarah_xing @ 4.372523
12 bihari-brahmin_harappa + haryana-jatt_harappa + tajik_yunusbayev + urkarah_xing @ 4.373172
13 haryana-jatt_harappa + nepali_harappa + tajik_yunusbayev + urkarah_xing @ 4.389886
14 haryana-jatt_harappa + lezgin_behar + nepalese-a_xing + tajik_yunusbayev @ 4.390042
15 balochi_hgdp + burusho_hgdp + lezgin_behar + singapore-indian-d_sgvp @ 4.428015
16 haryana-jatt_harappa + punjabi-jatt-sikh_harappa + tajik_yunusbayev + urkarah_xing @ 4.463769
17 haryana-jatt_harappa + singapore-indian-c_sgvp + tajik_yunusbayev + urkarah_xing @ 4.513279
18 nepalese-a_xing + nepalese-a_xing + tajik_yunusbayev + urkarah_xing @ 4.523100
19 burusho_hgdp + nepalese-a_xing + tajik_yunusbayev + urkarah_xing @ 4.528226
20 haryana-jatt_harappa + kalash_hgdp + tajik_yunusbayev + tajik_yunusbayev @ 4.531488



Eurogenes EUtest V2 K15
Kit T156535

# Population Percent
1 West_Asian 31.21
2 South_Asian 27.61
3 Eastern_Euro 17.31
4 North_Sea 11.54
5 Baltic 3.06
6 Siberian 2.76
7 Southeast_Asian 2.58
8 Amerindian 2.52
9 Atlantic 1.33
10 East_Med 0.07

# Population (source) Distance
1 Afghan_Pashtun 9.48
2 Kalash 11.1
3 Tadjik 13.87
4 Burusho 14.16
5 Pathan 15.86
6 Afghan_Tadjik 16.92
7 Balochi 16.99
8 Afghan_Uzbeki 17.67
9 Brahui 18.14
10 Punjabi_Jat 18.64
11 Makrani 20.78
12 Sindhi 22.52
13 Turkmen 23.65
14 Tabassaran 24.2
15 Lezgin 26.35
16 Chechen 27.76
17 Kumyk 28.12
18 Nogay 28.42
19 Kabardin 29.48
20 Balkar 30.19

# Primary Population (source) Secondary Population (source) Distance
1 78.9% Kalash + 21.1% Tatar @ 6.17
2 81.9% Kalash + 18.1% Chuvash @ 6.43
3 65% Burusho + 35% Tabassaran @ 6.54
4 82.8% Kalash + 17.2% East_Finnish @ 6.69
5 83.3% Kalash + 16.7% Finnish @ 6.77
6 83.9% Kalash + 16.1% North_Swedish @ 6.86
7 83.9% Kalash + 16.1% Southwest_Finnish @ 7.07
8 83.8% Kalash + 16.2% Mari @ 7.11
9 85.2% Kalash + 14.8% West_Norwegian @ 7.19
10 84.8% Kalash + 15.2% Norwegian @ 7.21
11 83.1% Kalash + 16.9% Kargopol_Russian @ 7.21
12 84.8% Kalash + 15.2% Swedish @ 7.22
13 76.5% Kalash + 23.5% Nogay @ 7.22
14 83.2% Kalash + 16.8% Erzya @ 7.24
15 84.8% Kalash + 15.2% La_Brana-1 @ 7.39
16 58.6% Kalash + 41.4% Tadjik @ 7.41
17 84.8% Kalash + 15.2% Estonian @ 7.45
18 85.3% Kalash + 14.7% North_Dutch @ 7.52
19 85.2% Kalash + 14.8% Danish @ 7.55
20 83.9% Kalash + 16.1% East_German @ 7.57

Using 1 population approximation:
1 Afghan_Pashtun @ 11.033933
2 Kalash @ 12.360916
3 Tadjik @ 15.448825
4 Burusho @ 15.953106
5 Pathan @ 17.923466
6 Afghan_Tadjik @ 18.586372
7 Afghan_Uzbeki @ 19.472904
8 Balochi @ 19.663536
9 Punjabi_Jat @ 20.809826
10 Brahui @ 21.021517
11 Makrani @ 24.085413
12 Sindhi @ 25.400721
13 Turkmen @ 27.130697
14 Tabassaran @ 27.402758
15 Lezgin @ 29.897827
16 Nogay @ 30.761786
17 Chechen @ 31.543739
18 Afghan_Hazara @ 31.676493
19 Kumyk @ 32.098747
20 Kabardin @ 33.508682

Using 2 populations approximation:
1 50% Kalash +50% Tadjik @ 8.805588

Using 3 populations approximation:
1 50% Kalash +25% Kalash +25% Tatar @ 7.217507

Using 4 populations approximation:
1 Kalash + Kalash + Kalash + Tatar @ 7.217507
2 Burusho + Burusho + Kalash + Tabassaran @ 7.943832
3 Burusho + Kalash + Kalash + Tabassaran @ 8.080607
4 Brahmin_UP + Burusho + Tabassaran + Tabassaran @ 8.092634
5 Burusho + Punjabi_Jat + Tabassaran + Tadjik @ 8.134829
6 Afghan_Pashtun + Kalash + Kalash + Tatar @ 8.174018
7 Chuvash + Kalash + Kalash + Kalash @ 8.211571
8 Afghan_Pashtun + Burusho + Burusho + Tabassaran @ 8.275217
9 Kalash + Punjabi_Jat + Tabassaran + Tadjik @ 8.343127
10 Afghan_Pashtun + Burusho + Punjabi_Jat + Tabassaran @ 8.344979
11 Kalash + Kalash + Kalash + Nogay @ 8.365576
12 Burusho + Gujarati + Tabassaran + Tabassaran @ 8.372521
13 Burusho + Kalash + Kalash + Tatar @ 8.375828
14 Burusho + Kalash + Punjabi_Jat + Tabassaran @ 8.379948
15 Burusho + Kshatriya + Tabassaran + Tabassaran @ 8.432156
16 Burusho + Kalash + Tabassaran + Tadjik @ 8.500617
17 Afghan_Pashtun + Burusho + Kalash + Tabassaran @ 8.501147
18 Bangladeshi + Burusho + Tabassaran + Tabassaran @ 8.520268
19 Burusho + Burusho + Burusho + Tabassaran @ 8.575767
20 Burusho + Burusho + Tabassaran + Tadjik @ 8.578400

Leto
06-05-2018, 01:41 PM
The Chitrali with highest NE-Euro I have found is this one:



HarappaWorld
Kit T156535

# Population Percent
1 Baloch 34.72
2 NE-Euro 18.98
3 Caucasian 17.85
4 S-Indian 15.86
5 NE-Asian 4.04
6 Siberian 2.45
7 American 2.09
8 Mediterranean 2
9 Beringian 1.93
10 San 0.08

# Population (source) Distance
1 pashtun (harappa) 9.48
2 tajik (yunusbayev) 10.7
3 pathan (hgdp) 12.38
4 kalash (hgdp) 12.92
5 haryana-jatt (harappa) 13.28
6 burusho (hgdp) 13.73
7 punjabi-khatri (harappa) 15.4
8 sindhi (harappa) 15.59
9 punjabi-jatt-sikh (harappa) 15.68
10 bhatia (harappa) 16
11 kashmiri (harappa) 16.45
12 punjabi-jatt-muslim (harappa) 18.38
13 kashmiri-pandit (reich) 18.97
14 punjabi (harappa) 20
15 punjabi-brahmin (harappa) 20.18
16 turkmen (yunusbayev) 20.47
17 singapore-indian-c (sgvp) 20.8
18 nepalese-a (xing) 20.85
19 punjabi-arain (xing) 21.03
20 gujarati-muslim (harappa) 21.07

# Primary Population (source) Secondary Population (source) Distance
1 55.9% tajik (yunusbayev) + 44.1% haryana-jatt (harappa) @ 3.54
2 81.4% kalash (hgdp) + 18.6% russian (behar) @ 4.81
3 80.2% kalash (hgdp) + 19.8% mordovian (yunusbayev) @ 4.84
4 80.2% kalash (hgdp) + 19.8% ukranian (yunusbayev) @ 4.85
5 72.3% tajik (yunusbayev) + 27.7% up-brahmin (harappa) @ 4.91
6 67.3% tajik (yunusbayev) + 32.7% punjabi-brahmin (harappa) @ 4.92
7 61.1% tajik (yunusbayev) + 38.9% punjabi-jatt-sikh (harappa) @ 4.95
8 74.2% tajik (yunusbayev) + 25.8% brahmin-uttar-pradesh (metspalu) @ 4.98
9 81.7% kalash (hgdp) + 18.3% belorussian (behar) @ 5.04
10 68.5% haryana-jatt (harappa) + 31.5% stalskoe (xing) @ 5.06
11 60.7% tajik (yunusbayev) + 39.3% punjabi-khatri (harappa) @ 5.07
12 78.3% kalash (hgdp) + 21.7% chuvash (behar) @ 5.08
13 79.3% kalash (hgdp) + 20.7% slovenian (xing) @ 5.12
14 69.3% haryana-jatt (harappa) + 30.7% urkarah (xing) @ 5.13
15 68.4% tajik (yunusbayev) + 31.6% nepalese-a (xing) @ 5.22
16 68.3% tajik (yunusbayev) + 31.7% singapore-indian-c (sgvp) @ 5.25
17 79.1% kalash (hgdp) + 20.9% hungarian (behar) @ 5.25
18 71.1% haryana-jatt (harappa) + 28.9% lezgin (behar) @ 5.38
19 66.3% tajik (yunusbayev) + 33.7% kashmiri-pandit (reich) @ 5.44
20 76.3% tajik (yunusbayev) + 23.7% vaish (reich) @ 5.45

Using 1 population approximation:
1 pashtun_harappa @ 10.312273
2 tajik_yunusbayev @ 11.704757
3 pathan_hgdp @ 13.590567
4 kalash_hgdp @ 14.185414
5 haryana-jatt_harappa @ 14.681555
6 burusho_hgdp @ 15.131252
7 punjabi-khatri_harappa @ 16.945095
8 sindhi_harappa @ 17.139486
9 punjabi-jatt-sikh_harappa @ 17.306044
10 bhatia_harappa @ 17.613039
11 kashmiri_harappa @ 18.140388
12 pushtikar-brahmin_harappa @ 18.902483
13 rajasthani-brahmin_harappa @ 19.567549
14 punjabi-jatt-muslim_harappa @ 20.211288
15 nepali_harappa @ 20.505751
16 kashmiri-pandit_reich @ 20.937525
17 punjabi_harappa @ 22.073219
18 punjabi-brahmin_harappa @ 22.291056
19 turkmen_yunusbayev @ 22.530777
20 singapore-indian-c_sgvp @ 22.968975

Using 2 populations approximation:
1 50% haryana-jatt_harappa +50% tajik_yunusbayev @ 4.102673

Using 3 populations approximation:
1 50% haryana-jatt_harappa +25% tajik_yunusbayev +25% tajik_yunusbayev @ 4.102673

Using 4 populations approximation:
1 haryana-jatt_harappa + nepalese-a_xing + tajik_yunusbayev + urkarah_xing @ 3.441797
2 balochi_hgdp + burusho_hgdp + singapore-indian-d_sgvp + urkarah_xing @ 3.838457
3 brahui_hgdp + burusho_hgdp + singapore-indian-d_sgvp + urkarah_xing @ 4.006856
4 haryana-jatt_harappa + rajasthani-brahmin_harappa + tajik_yunusbayev + urkarah_xing @ 4.012163
5 haryana-jatt_harappa + haryana-jatt_harappa + tajik_yunusbayev + tajik_yunusbayev @ 4.102673
6 haryana-jatt_harappa + nepalese-a_xing + stalskoe_xing + tajik_yunusbayev @ 4.142271
7 haryana-jatt_harappa + haryana-jatt_harappa + tajik_yunusbayev + urkarah_xing @ 4.227292
8 nepalese-a_xing + rajasthani-brahmin_harappa + tajik_yunusbayev + urkarah_xing @ 4.305750
9 nepalese-a_xing + punjabi-jatt-sikh_harappa + tajik_yunusbayev + urkarah_xing @ 4.313712
10 haryana-jatt_harappa + rajasthani-brahmin_harappa + stalskoe_xing + tajik_yunusbayev @ 4.354100
11 burusho_hgdp + makrani_hgdp + singapore-indian-d_sgvp + urkarah_xing @ 4.372523
12 bihari-brahmin_harappa + haryana-jatt_harappa + tajik_yunusbayev + urkarah_xing @ 4.373172
13 haryana-jatt_harappa + nepali_harappa + tajik_yunusbayev + urkarah_xing @ 4.389886
14 haryana-jatt_harappa + lezgin_behar + nepalese-a_xing + tajik_yunusbayev @ 4.390042
15 balochi_hgdp + burusho_hgdp + lezgin_behar + singapore-indian-d_sgvp @ 4.428015
16 haryana-jatt_harappa + punjabi-jatt-sikh_harappa + tajik_yunusbayev + urkarah_xing @ 4.463769
17 haryana-jatt_harappa + singapore-indian-c_sgvp + tajik_yunusbayev + urkarah_xing @ 4.513279
18 nepalese-a_xing + nepalese-a_xing + tajik_yunusbayev + urkarah_xing @ 4.523100
19 burusho_hgdp + nepalese-a_xing + tajik_yunusbayev + urkarah_xing @ 4.528226
20 haryana-jatt_harappa + kalash_hgdp + tajik_yunusbayev + tajik_yunusbayev @ 4.531488



Eurogenes EUtest V2 K15
Kit T156535

# Population Percent
1 West_Asian 31.21
2 South_Asian 27.61
3 Eastern_Euro 17.31
4 North_Sea 11.54
5 Baltic 3.06
6 Siberian 2.76
7 Southeast_Asian 2.58
8 Amerindian 2.52
9 Atlantic 1.33
10 East_Med 0.07

# Population (source) Distance
1 Afghan_Pashtun 9.48
2 Kalash 11.1
3 Tadjik 13.87
4 Burusho 14.16
5 Pathan 15.86
6 Afghan_Tadjik 16.92
7 Balochi 16.99
8 Afghan_Uzbeki 17.67
9 Brahui 18.14
10 Punjabi_Jat 18.64
11 Makrani 20.78
12 Sindhi 22.52
13 Turkmen 23.65
14 Tabassaran 24.2
15 Lezgin 26.35
16 Chechen 27.76
17 Kumyk 28.12
18 Nogay 28.42
19 Kabardin 29.48
20 Balkar 30.19

# Primary Population (source) Secondary Population (source) Distance
1 78.9% Kalash + 21.1% Tatar @ 6.17
2 81.9% Kalash + 18.1% Chuvash @ 6.43
3 65% Burusho + 35% Tabassaran @ 6.54
4 82.8% Kalash + 17.2% East_Finnish @ 6.69
5 83.3% Kalash + 16.7% Finnish @ 6.77
6 83.9% Kalash + 16.1% North_Swedish @ 6.86
7 83.9% Kalash + 16.1% Southwest_Finnish @ 7.07
8 83.8% Kalash + 16.2% Mari @ 7.11
9 85.2% Kalash + 14.8% West_Norwegian @ 7.19
10 84.8% Kalash + 15.2% Norwegian @ 7.21
11 83.1% Kalash + 16.9% Kargopol_Russian @ 7.21
12 84.8% Kalash + 15.2% Swedish @ 7.22
13 76.5% Kalash + 23.5% Nogay @ 7.22
14 83.2% Kalash + 16.8% Erzya @ 7.24
15 84.8% Kalash + 15.2% La_Brana-1 @ 7.39
16 58.6% Kalash + 41.4% Tadjik @ 7.41
17 84.8% Kalash + 15.2% Estonian @ 7.45
18 85.3% Kalash + 14.7% North_Dutch @ 7.52
19 85.2% Kalash + 14.8% Danish @ 7.55
20 83.9% Kalash + 16.1% East_German @ 7.57

Using 1 population approximation:
1 Afghan_Pashtun @ 11.033933
2 Kalash @ 12.360916
3 Tadjik @ 15.448825
4 Burusho @ 15.953106
5 Pathan @ 17.923466
6 Afghan_Tadjik @ 18.586372
7 Afghan_Uzbeki @ 19.472904
8 Balochi @ 19.663536
9 Punjabi_Jat @ 20.809826
10 Brahui @ 21.021517
11 Makrani @ 24.085413
12 Sindhi @ 25.400721
13 Turkmen @ 27.130697
14 Tabassaran @ 27.402758
15 Lezgin @ 29.897827
16 Nogay @ 30.761786
17 Chechen @ 31.543739
18 Afghan_Hazara @ 31.676493
19 Kumyk @ 32.098747
20 Kabardin @ 33.508682

Using 2 populations approximation:
1 50% Kalash +50% Tadjik @ 8.805588

Using 3 populations approximation:
1 50% Kalash +25% Kalash +25% Tatar @ 7.217507

Using 4 populations approximation:
1 Kalash + Kalash + Kalash + Tatar @ 7.217507
2 Burusho + Burusho + Kalash + Tabassaran @ 7.943832
3 Burusho + Kalash + Kalash + Tabassaran @ 8.080607
4 Brahmin_UP + Burusho + Tabassaran + Tabassaran @ 8.092634
5 Burusho + Punjabi_Jat + Tabassaran + Tadjik @ 8.134829
6 Afghan_Pashtun + Kalash + Kalash + Tatar @ 8.174018
7 Chuvash + Kalash + Kalash + Kalash @ 8.211571
8 Afghan_Pashtun + Burusho + Burusho + Tabassaran @ 8.275217
9 Kalash + Punjabi_Jat + Tabassaran + Tadjik @ 8.343127
10 Afghan_Pashtun + Burusho + Punjabi_Jat + Tabassaran @ 8.344979
11 Kalash + Kalash + Kalash + Nogay @ 8.365576
12 Burusho + Gujarati + Tabassaran + Tabassaran @ 8.372521
13 Burusho + Kalash + Kalash + Tatar @ 8.375828
14 Burusho + Kalash + Punjabi_Jat + Tabassaran @ 8.379948
15 Burusho + Kshatriya + Tabassaran + Tabassaran @ 8.432156
16 Burusho + Kalash + Tabassaran + Tadjik @ 8.500617
17 Afghan_Pashtun + Burusho + Kalash + Tabassaran @ 8.501147
18 Bangladeshi + Burusho + Tabassaran + Tabassaran @ 8.520268
19 Burusho + Burusho + Burusho + Tabassaran @ 8.575767
20 Burusho + Burusho + Tabassaran + Tadjik @ 8.578400
Dodecad K12 is one of the best for South and Central Asians.

lameduck
06-05-2018, 02:17 PM
Which ethnicities . Please post complete result or link

kho chitralis

SexyLionMan
08-12-2018, 12:48 PM
It’s no surprise Jats have very high Steppe DNA and maintained their purity. Plus, Jats have less South Asian ancestry than the average Indian and are outlanders or outcastes meaning the same thing. LOL X

Leto
12-06-2018, 08:09 PM
Eurogenes EUtest V2 K15 Oracle results:
Kit M611023

Admix Results (sorted):

# Population Percent
1 South_Asian 38.43
2 West_Asian 23.6
3 North_Sea 13.64
4 Eastern_Euro 12.1
5 Baltic 5.75
6 Atlantic 2.5
7 Amerindian 1.53
8 East_Med 1.39
9 Oceanian 0.89
10 Sub-Saharan 0.17

Single Population Sharing:

# Population (source) Distance
1 Punjabi_Jat 8.59
2 Pathan 10.23
3 Kalash 11.69
4 Burusho 13.66
5 Sindhi 14.45
6 Afghan_Pashtun 15.65
7 Balochi 18.76
8 Brahui 19.46
9 Brahmin_UP 20.78
10 Tadjik 21.96
11 Makrani 22.09
12 Gujarati 22.62
13 Afghan_Uzbeki 23.87
14 Kshatriya 23.98
15 Afghan_Tadjik 23.99
16 Bangladeshi 27.2
17 Turkmen 30.37
18 Dharkar 31.77
19 Kanjar 32.88
20 Tabassaran 34.56

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 86.2% Punjabi_Jat + 13.8% Swedish @ 3.76
2 86% Punjabi_Jat + 14% North_Swedish @ 3.8
3 86.7% Punjabi_Jat + 13.3% West_Norwegian @ 3.84
4 86.3% Punjabi_Jat + 13.7% Norwegian @ 3.87
5 86% Punjabi_Jat + 14% Finnish @ 4.18
6 86.7% Punjabi_Jat + 13.3% North_Dutch @ 4.26
7 86.3% Punjabi_Jat + 13.7% Southwest_Finnish @ 4.35
8 86.7% Punjabi_Jat + 13.3% Danish @ 4.38
9 86.1% Punjabi_Jat + 13.9% West_German @ 4.41
10 87.1% Punjabi_Jat + 12.9% Orcadian @ 4.43
11 86.4% Punjabi_Jat + 13.6% North_German @ 4.46
12 86.8% Punjabi_Jat + 13.2% Estonian @ 4.52
13 87.3% Punjabi_Jat + 12.7% West_Scottish @ 4.58
14 86% Punjabi_Jat + 14% East_German @ 4.59
15 86.3% Punjabi_Jat + 13.7% East_Finnish @ 4.61
16 87.3% Punjabi_Jat + 12.7% Irish @ 4.63
17 85.6% Punjabi_Jat + 14.4% Hungarian @ 4.64
18 85.9% Punjabi_Jat + 14.1% Ukrainian_Lviv @ 4.66
19 86.1% Punjabi_Jat + 13.9% Ukrainian @ 4.7
20 87.2% Punjabi_Jat + 12.8% Southeast_English @ 4.71


Eurogenes K13 Oracle results:
K13 Oracle ref data revised 21 Nov 2013

Kit M611023

Admix Results (sorted):

# Population Percent
1 South_Asian 36.42
2 West_Asian 32.33
3 North_Atlantic 13.74
4 Baltic 13.41
5 Amerindian 1.85
6 Oceanian 1.3
7 East_Med 0.38
8 Siberian 0.29
9 Sub-Saharan 0.28

Single Population Sharing:

# Population (source) Distance
1 Punjabi_Jat 8.84
2 Pathan 11.61
3 Kalash 12.16
4 Burusho 13.91
5 Afghan_Pashtun 14.93
6 Sindhi 16.26
7 Brahmin_UP 19.72
8 Tadjik 20.83
9 Gujarati 22.3
10 Kshatriya 23.35
11 Afghan_Tadjik 23.67
12 Balochi 23.68
13 Makrani 24.8
14 Brahui 24.91
15 Bangladeshi 27.56
16 Dharkar 31.37
17 Tabassaran 31.69
18 Turkmen 31.77
19 Kanjar 32.16
20 Lezgin 34

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 86.1% Punjabi_Jat + 13.9% Swedish @ 2.47
2 86.3% Punjabi_Jat + 13.7% Norwegian @ 2.5
3 85.6% Punjabi_Jat + 14.4% North_German @ 2.66
4 86.2% Punjabi_Jat + 13.8% North_Dutch @ 2.66
5 86% Punjabi_Jat + 14% Danish @ 2.7
6 86.3% Punjabi_Jat + 13.7% North_Swedish @ 2.73
7 86.3% Punjabi_Jat + 13.7% Irish @ 2.77
8 86.5% Punjabi_Jat + 13.5% West_Scottish @ 2.85
9 86.4% Punjabi_Jat + 13.6% Orcadian @ 2.86
10 86.5% Punjabi_Jat + 13.5% Southeast_English @ 3.08
11 86.7% Punjabi_Jat + 13.3% Southwest_English @ 3.15
12 85.7% Punjabi_Jat + 14.3% West_German @ 3.4
13 86.9% Punjabi_Jat + 13.1% Southwest_Finnish @ 3.42
14 86% Punjabi_Jat + 14% South_Dutch @ 3.49
15 85.7% Punjabi_Jat + 14.3% East_German @ 3.49
16 87.3% Punjabi_Jat + 12.7% La_Brana-1 @ 3.51
17 85.6% Punjabi_Jat + 14.4% Austrian @ 3.53
18 85.4% Punjabi_Jat + 14.6% Hungarian @ 3.79
19 87.2% Punjabi_Jat + 12.8% Finnish @ 3.84
20 86.2% Punjabi_Jat + 13.8% South_Polish @ 3.96


I think he's fully native:

What if he is 1/8 British? After all the British were there for over 200 years. He's extremely Nordic for an Indian (Afghans are not Indians). Though he may not be mixed.

Ajeje Brazorf
12-06-2018, 09:15 PM
What if he is 1/8 British? After all the British were there for over 200 years. He's extremely Nordic for an Indian (Afghans are not Indians). Though he may not be mixed.

If he was partly British he would score some EEF but he doesn't. Also he's not Nordic shifted in the geographical and ethnic sense but rather Central Asian shifted imo


<tbody>
#

Primary Population (source)
Secondary Population (source)
Distance


1

57.1%
Tiwari ( )
+
42.9%
Tajik_Yagnobi ( )
@
2.2


2

51.1%
Kshatriya ( )
+
48.9%
Tajik_Yagnobi ( )
@
2.36


3

70.5%
Jatt_Haryana ( )
+
29.5%
Tajik_Pomiri_Rushan ( )
@
2.42


4

73.5%
Tajik_Pomiri_Shugnan ( )
+
26.5%
Kamsali ( )
@
2.49


5

72%
Tajik_Pomiri_Shugnan ( )
+
28%
Scheduled_Caste_Tamil_Nadu ( )
@
2.51


6

71%
Tajik_Pomiri_Shugnan ( )
+
29%
Lodhi ( )
@
2.58


7

74.5%
Tajik_Pomiri_Shugnan ( )
+
25.5%
Sakilli ( )
@
2.58


8

71.9%
Tajik_Pomiri_Shugnan ( )
+
28.1%
Dusadh ( )
@
2.59


9

73.2%
Tajik_Pomiri_Shugnan ( )
+
26.8%
Kol ( )
@
2.59


10

68.8%
Jatt_Haryana ( )
+
31.2%
Tajik_Pomiri_Shugnan ( )
@
2.61


11

73.3%
Tajik_Pomiri_Shugnan ( )
+
26.7%
Vishwabrahmin ( )
@
2.61


12

66.4%
Tajik_Pomiri_Shugnan ( )
+
33.6%
Srivastava ( )
@
2.66


13

67.1%
Tajik_Pomiri_Shugnan ( )
+
32.9%
Muslim_India ( )
@
2.68


14

72.7%
Tajik_Pomiri_Shugnan ( )
+
27.3%
Vysya ( )
@
2.69


15

54.1%
Hindi ( )
+
45.9%
Tajik_Yagnobi ( )
@
2.73


16

71.8%
Tajik_Pomiri_Shugnan ( )
+
28.2%
Scheduled_Caste_UP ( )
@
2.73


17

77.4%
Jatt_Haryana ( )
+
22.6%
Tajik_Yagnobi ( )
@
2.74


18

64.4%
Tajik_Pomiri_Rushan ( )
+
35.6%
Srivastava ( )
@
2.77


19

71%
Tajik_Pomiri_Shugnan ( )
+
29%
Bhili ( )
@
2.78


20

58.6%
Tajik_Pomiri_Rushan ( )
+
41.4%
Brahmins_UP ( )
@
2.78

</tbody>

tipirneni
12-06-2018, 09:39 PM
If he was partly British he would score some EEF but he doesn't. Also he's not Nordic shifted in the geographical and ethnic sense but rather Central Asian shifted imo


<tbody>
#

Primary Population (source)
Secondary Population (source)
Distance


1

57.1%
Tiwari ( )
+
42.9%
Tajik_Yagnobi ( )
@
2.2


2

51.1%
Kshatriya ( )
+
48.9%
Tajik_Yagnobi ( )
@
2.36


3

70.5%
Jatt_Haryana ( )
+
29.5%
Tajik_Pomiri_Rushan ( )
@
2.42


4

73.5%
Tajik_Pomiri_Shugnan ( )
+
26.5%
Kamsali ( )
@
2.49


5

72%
Tajik_Pomiri_Shugnan ( )
+
28%
Scheduled_Caste_Tamil_Nadu ( )
@
2.51


6

71%
Tajik_Pomiri_Shugnan ( )
+
29%
Lodhi ( )
@
2.58


7

74.5%
Tajik_Pomiri_Shugnan ( )
+
25.5%
Sakilli ( )
@
2.58


8

71.9%
Tajik_Pomiri_Shugnan ( )
+
28.1%
Dusadh ( )
@
2.59


9

73.2%
Tajik_Pomiri_Shugnan ( )
+
26.8%
Kol ( )
@
2.59


10

68.8%
Jatt_Haryana ( )
+
31.2%
Tajik_Pomiri_Shugnan ( )
@
2.61


11

73.3%
Tajik_Pomiri_Shugnan ( )
+
26.7%
Vishwabrahmin ( )
@
2.61


12

66.4%
Tajik_Pomiri_Shugnan ( )
+
33.6%
Srivastava ( )
@
2.66


13

67.1%
Tajik_Pomiri_Shugnan ( )
+
32.9%
Muslim_India ( )
@
2.68


14

72.7%
Tajik_Pomiri_Shugnan ( )
+
27.3%
Vysya ( )
@
2.69


15

54.1%
Hindi ( )
+
45.9%
Tajik_Yagnobi ( )
@
2.73


16

71.8%
Tajik_Pomiri_Shugnan ( )
+
28.2%
Scheduled_Caste_UP ( )
@
2.73


17

77.4%
Jatt_Haryana ( )
+
22.6%
Tajik_Yagnobi ( )
@
2.74


18

64.4%
Tajik_Pomiri_Rushan ( )
+
35.6%
Srivastava ( )
@
2.77


19

71%
Tajik_Pomiri_Shugnan ( )
+
29%
Bhili ( )
@
2.78


20

58.6%
Tajik_Pomiri_Rushan ( )
+
41.4%
Brahmins_UP ( )
@
2.78

</tbody>
There has been a lot of connection with ancient South Asian kingdoms with Central Asian ones such as Yue-chi/Tochar Huns etc... It might be the old Sakyan rulers during Iron Age might have some conquests & connections into these Central Asian tribes & during fall of Yue-chi/Kushan rule in India some of these tribes mixed with local Fighters/Peasants & Military vocations. You will see high central asian content in those castes. Jats have saying that they mixed with these Yue-chi tribes during their rule in Madura in late Buddhist era. there are vast number of artifacts from this era in Northern India. These tribes took over old Greaco-Bactrian kingdoms in Afghan & moved into North India & later to other parts.

https://upload.wikimedia.org/wikipedia/commons/thumb/e/ee/Buddha_in_Abhaya_Mudra_-_Circa_2nd_Century_CE_-_ACCN_00-A-4_-_Government_Museum_-_Mathura_2013-02-23_5692.JPG/220px-Buddha_in_Abhaya_Mudra_-_Circa_2nd_Century_CE_-_ACCN_00-A-4_-_Government_Museum_-_Mathura_2013-02-23_5692.JPG

http://upload.wikimedia.org/wikipedia/commons/thumb/3/37/Hunnu_Empire.jpg/440px-Hunnu_Empire.jpg

tipirneni
12-06-2018, 09:44 PM
There has been a lot of connection with ancient South Asian kingdoms with Central Asian ones such as Yue-chi/Tochar Huns etc... It might be the old Sakyan rulers during Iron Age might have some conquests & connections into these Central Asian tribes & during fall of Yue-chi/Kushan rule in India some of these tribes mixed with local Fighters/Peasants & Military vocations. You will see high central asian content in those castes. Jats have saying that they mixed with these Yue-chi tribes during their rule in Madura in late Buddhist era. there are vast number of artifacts from this era in Northern India. These tribes took over old Greaco-Bactrian kingdoms in Afghan & moved into North India & later to other parts.

https://upload.wikimedia.org/wikipedia/commons/thumb/e/ee/Buddha_in_Abhaya_Mudra_-_Circa_2nd_Century_CE_-_ACCN_00-A-4_-_Government_Museum_-_Mathura_2013-02-23_5692.JPG/220px-Buddha_in_Abhaya_Mudra_-_Circa_2nd_Century_CE_-_ACCN_00-A-4_-_Government_Museum_-_Mathura_2013-02-23_5692.JPG

http://upload.wikimedia.org/wikipedia/commons/thumb/3/37/Hunnu_Empire.jpg/440px-Hunnu_Empire.jpg

Main line of India Solar dynasty. There is also Lunar, Yadu & Nag dynasties. They extend to very remote time. They tend to keep memories alive from another era.
http://ancientvoice.wdfiles.com/local--files/article%3Aikshwaku-kings-in-mahabharata/Mbh_Ikswaku_Lineage.png

Leto
12-06-2018, 09:46 PM
If he was partly British he would score some EEF but he doesn't. Also he's not Nordic shifted in the geographical and ethnic sense but rather Central Asian shifted imo

By Nordic I meant Northeastern Europe. If he isn't mixed, that's a hell of a lot of Aryan blood for a living South Asian. I love them Aryans! :thumb001::cool:

tipirneni
12-06-2018, 10:38 PM
By Nordic I meant Northeastern Europe. If he isn't mixed, that's a hell of a lot of Aryan blood for a living South Asian. I love them Aryans! :thumb001::cool:

It might be due to high caste Endogamy. Jats have a well established endogamy & connection to their ancient kingdom near Madura. Whereas Brahmins & Kshatriya who are spread all over India usually have local admixture based on where they rule. The Tiwari brahmin you are seeing the list might be ancient Saraswati civilization that is parallel to the IVC people & mixed in chalcolithic period to establish Gangetic Vedic Aryan civilization, which later formed the basis for the Iron age kingdoms all over India.

SexyLionMan
12-07-2018, 01:31 PM
What if he is 1/8 British? After all the British were there for over 200 years. He's extremely Nordic for an Indian (Afghans are not Indians). Though he may not be mixed.

I doubt that he’s mixed because our caste don’t do that often in modern times and yes he’s very Nordic in terms of DNA for an Indian.

Leto
12-07-2018, 02:45 PM
It's probably one of the least South Asian Indians

S-Indian 24.87
South_Indian 25.42
South_Asian 26.26


On this calculator I get around 50%

MDLP K23b Oracle results:

Admix Results (sorted):

# Population Percent
1 South_Central_Asian 31.3
2 South_Indian 25.42
3 Caucasian 14.12
4 European_Hunters_Gatherers 13.92
5 Ancestral_Altaic 8.79
6 Near_East 1.33
7 European_Early_Farmers 1.33
8 Arctic 1.13
9 Paleo_Siberian 1.07
10 Australoid 0.93
11 Melano_Polynesian 0.43
12 Archaic_Human 0.18
13 Archaic_African 0.04
14 Khoisan 0.01

Single Population Sharing:

# Population (source) Distance
1 Pakistani_Pushtun ( ) 8.76
2 Pathan ( ) 9.31
3 Jatt_Haryana ( ) 9.39
4 Jatt_Pahari ( ) 10.68
5 Burusho ( ) 12.87
6 Punjabi_Gujjar ( ) 14.73
7 Pashtun_Afghani ( ) 15
8 Tajik_Pomiri_Ishkashim ( ) 15.92
9 Afghan_Pushtun ( ) 16.41
10 Jatt_Muslim ( ) 16.73
11 Mumbai_Jew ( ) 17.1
12 Cochin_Jew ( ) 17.3
13 Pakistani ( ) 18.36
14 Sindhi ( ) 19.3
15 GujaratiA_GIH ( ) 19.62
16 Tajik_Pomiri_Shugnan ( ) 20.05
17 Uzbek_Afghan ( ) 20.68
18 Tajik_Afghan ( ) 21.18
19 Tajik_Pomiri_Rushan ( ) 21.86
20 Tiwari ( ) 23.27

Mixed Mode Population Sharing:

# Primary Population (source) Secondary Population (source) Distance
1 57.1% Tiwari ( ) + 42.9% Tajik_Yagnobi ( ) @ 2.2
2 51.1% Kshatriya ( ) + 48.9% Tajik_Yagnobi ( ) @ 2.36
3 70.5% Jatt_Haryana ( ) + 29.5% Tajik_Pomiri_Rushan ( ) @ 2.42
4 73.5% Tajik_Pomiri_Shugnan ( ) + 26.5% Kamsali ( ) @ 2.49
5 72% Tajik_Pomiri_Shugnan ( ) + 28% Scheduled_Caste_Tamil_Nadu ( ) @ 2.51
6 71% Tajik_Pomiri_Shugnan ( ) + 29% Lodhi ( ) @ 2.58
7 74.5% Tajik_Pomiri_Shugnan ( ) + 25.5% Sakilli ( ) @ 2.58
8 71.9% Tajik_Pomiri_Shugnan ( ) + 28.1% Dusadh ( ) @ 2.59
9 73.2% Tajik_Pomiri_Shugnan ( ) + 26.8% Kol ( ) @ 2.59
10 68.8% Jatt_Haryana ( ) + 31.2% Tajik_Pomiri_Shugnan ( ) @ 2.61
11 73.3% Tajik_Pomiri_Shugnan ( ) + 26.7% Vishwabrahmin ( ) @ 2.61
12 66.4% Tajik_Pomiri_Shugnan ( ) + 33.6% Srivastava ( ) @ 2.66
13 67.1% Tajik_Pomiri_Shugnan ( ) + 32.9% Muslim_India ( ) @ 2.68
14 72.7% Tajik_Pomiri_Shugnan ( ) + 27.3% Vysya ( ) @ 2.69
15 54.1% Hindi ( ) + 45.9% Tajik_Yagnobi ( ) @ 2.73
16 71.8% Tajik_Pomiri_Shugnan ( ) + 28.2% Scheduled_Caste_UP ( ) @ 2.73
17 77.4% Jatt_Haryana ( ) + 22.6% Tajik_Yagnobi ( ) @ 2.74
18 64.4% Tajik_Pomiri_Rushan ( ) + 35.6% Srivastava ( ) @ 2.77
19 71% Tajik_Pomiri_Shugnan ( ) + 29% Bhili ( ) @ 2.78
20 58.6% Tajik_Pomiri_Rushan ( ) + 41.4% Brahmins_UP ( ) @ 2.78

Mingle
12-07-2018, 03:19 PM
I've seen a few Chitrali Pakistani kits, they had like 15-20% North European too.

There's barely any genetic difference between Northern Pashtuns (KPK, N2KL) and Chitralis.


Dodecad K12 is one of the best for South and Central Asians.

It does seem to be one of the better calcs. Its main flaw is it doesn't have much reference samples, but the Admix Results look good. How is it for Europeans?

Leto
12-07-2018, 03:29 PM
It does seem to be one of the better calcs. Its main flaw is it doesn't have much reference samples, but the Admix Results look good. How is it for Europeans?
Yes, absolutely. Dodecad oracles are usually inaccurate but the components are cool. I use it for Europeans cause it has no annoying 'Amerindian' noise and at least partially separates the Caucasoid element of South Asian. It is bad for new world mixes that have Amerindian ancestry.

Can you please post your MDLP K23b in the threads I made some time ago?
https://www.theapricity.com/forum/showthread.php?268202-Post-your-EHG-Caucasus-amp-EEF-scores-from-MDLP-K23b/page5