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Thread: Late Gupta era admixture in Western India

  1. #81
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    Quote Originally Posted by Censored View Post
    Just went ahead and ran some users using strictly S/SC Asian populations:

    "distance%=2.0733"

    Bmoney_scaled


    Kanjar,36.2
    Brahmin_Tamil_Nadu,13.6
    Brahui,12.6
    Yadava,12.2
    Iyer,11.2
    Gujarati,6.6
    Makrani,3.8
    Sakilli,3.8

    "distance%=2.3407"

    Patel_scaled

    Gujarati,70.2
    Piramalai,16.8
    Gupta,6.8
    Balochi,6.2

    "distance%=1.6118"

    ssamlal scaled

    Madiga,50.8
    Brahmin_Tamil_Nadu,39
    Tajik,8
    Bhumij,2.2

    "distance%=1.2365"

    varun

    Uttar_Pradesh,37.8
    Brahmin_Uttar_Pradesh,33
    Balochi,16
    Gupta,5
    Makrani,4.2
    Kalash,4

    "distance%=1.4574"

    26 scaled

    Brahmin_Tamil_Nadu,28.6
    Punjabi_Lahore,27.8
    Velamas,20
    Kshatriya,16
    Gujar,5.2
    Sindhi,2
    Brahmin_Manipuri,0.4

    "distance%=1.3944"

    Censored_scaled

    Yadava,24.2
    Chamar,22.2
    Khatri,17
    Brahmin_Tamil_Nadu,12.2
    Sakilli,8
    Tarkalani,6
    Velamas,5.2
    Piramalai,5
    Bhumij,0.2
    Obviously we can always take these with a grain of salt, but I lack more "foreign" components (i.e. Brahui, Tajik, etc.), but generally lack tribal in any fashion in these modern runs. It's always fun to see how these turn out. Bmoney has a really cool run here, completely different than mine, despite our similar gedmatches and all. He has a really strong Iran_N pull which seems to manifest differently to me, despite us scoring pretty similar BMAC in most calcs.

  2. #82
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    Quote Originally Posted by 26284729292 View Post
    Obviously we can always take these with a grain of salt, but I lack more "foreign" components (i.e. Brahui, Tajik, etc.), but generally lack tribal in any fashion in these modern runs. It's always fun to see how these turn out. Bmoney has a really cool run here, completely different than mine, despite our similar gedmatches and all. He has a really strong Iran_N pull which seems to manifest differently to me, despite us scoring pretty similar BMAC in most calcs.
    Yes-it just means you’re mostly pretty typical for your community I guess. You guys don’t have a strong IVC or tribal shift, and heavy NE Euro steppe rather than the “Caucasian” type that would push you towards SC Asians, and of course you’ve been inbreeding for centuries. Varun is an outlier.

  3. The Following User Says Thank You to Censored For This Useful Post:

     tipirneni (11-20-2018)

  4. #83
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    United States of America India
    Huns conquered many older groups such as Alans (Avar), Kangju (Kang-sogdians) etc.. & when they moved into India many of these were part of lakhs of people who settled during the late Gupta age.



    When I check my lactose tolerant genes in MCM6 I found

    rs4988243 -> CT

    Found in Iberia/Tuscany/Middle east/China/Japan/South India-STU&ITU/Gujarat-GIH/Bangladesh-BEB at 10% (1000 genome)

    Qatar -> 40+ % also Saudis share this allele

    DA 125 Kangju U2e2a 1738YBP T-Y13279 was also derived on this allele

    probably due to admixture during this late Gupta time with these West Asia autosome rich Steppe soldiers.



    rs3213871 -> TC

    Found among South Indians/Andhra Kammas
    nMonte3 current
    Velamas Gujarati_D Muslim_UP Tharus Punjabi_1000genomes
    1.859005 3.210341 4.491247 4.998440 6.040323

    G25 Ancients Dist 0.99 Shahr_I_Sokhta_BA3:S8728.E1.L1 65.2 Saidu_Sharif_IA_o:S7722.E1.L1 17.8 Udegram_IA:I1985 7.8 Jordanian:S_Jordanian-1 4.4 Barikot_IA:I6545 2.2 Scotland_N:I26602 Narva_Lithuania: Donkalnis6

    mtDNA mutation 309.1C 315.1C 522.1A 522.2C G8572A G8860A T11368C T16093a T16154C C16519T
    C195T

  5. #84
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    United States of America India


    Kangju sample admixture information

    Based on Dstats Kangju looks more WHG, EHG, IronGates, WEstSiberian_N,MA1 than GanjDareh,Barcin, LBK
    MDLP K23b Oracle Rev 2014 Sep 16

    Kit Z043955

    Admix Results (sorted):

    # Population Percent
    1 European_Early_Farmers 36.11
    2 South_Central_Asian 21.76
    3 European_Hunters_Gatherers 16.2
    4 Ancestral_Altaic 10.15
    5 Arctic 6.98
    6 African_Pygmy 2.65
    7 South_Indian 2.46
    8 Subsaharian 1.99
    9 North_African 1.52
    10 Melano_Polynesian 0.17

    Single Population Sharing:

    # Population (source) Distance
    1 Orcadian ( ) 31.68
    2 Scottish_Argyll_Bute_GBR ( ) 32.6
    3 Icelandic ( ) 33.86
    4 French_South ( ) 34.48
    5 Spanish_Cantabria_IBS ( ) 35.07
    6 Spanish_Pais_Vasco_IBS ( ) 35.1
    7 Spanish_Aragon_IBS ( ) 35.13
    8 Norwegian_West ( ) 35.52
    9 British ( ) 35.83
    10 Welsh ( ) 35.85
    11 CEU ( ) 36.03
    12 Spanish_Castilla_la_Mancha_IBS ( ) 36.15
    13 Spanish_Galicia_IBS ( ) 36.19
    14 Spanish_Canarias_IBS ( ) 36.23
    15 Spanish_Castilla_y_Leon_IBS ( ) 36.23
    16 Spanish_Extremadura_IBS ( ) 36.5
    17 English_Cornwall_GBR ( ) 37.13
    18 Spanish_Valencia_IBS ( ) 37.24
    19 Spanish_Andalucia_IBS ( ) 37.38
    20 Puerto_Rican ( ) 37.4

    Mixed Mode Population Sharing:

    # Primary Population (source) Secondary Population (source) Distance
    1 64% Spanish_Pais_Vasco_IBS ( ) + 36% Kalash ( ) @ 14.37
    2 59.4% Basque_Spanish ( ) + 40.6% Kalash ( ) @ 14.99
    3 59.1% Basque_French ( ) + 40.9% Kalash ( ) @ 15.25
    4 55.6% Basque_French ( ) + 44.4% Burusho ( ) @ 15.67
    5 56.6% Basque_French ( ) + 43.4% Makrani ( ) @ 15.7
    6 58% Basque_French ( ) + 42% Brahui ( ) @ 15.81
    7 58.4% Basque_Spanish ( ) + 41.6% Brahui ( ) @ 15.88
    8 57.5% Basque_French ( ) + 42.5% Balochi ( ) @ 15.94
    9 63.3% Spanish_Pais_Vasco_IBS ( ) + 36.7% Brahui ( ) @ 16.04
    10 57% Basque_Spanish ( ) + 43% Makrani ( ) @ 16.05
    11 56% Basque_Spanish ( ) + 44% Burusho ( ) @ 16.13
    12 57.9% Basque_Spanish ( ) + 42.1% Balochi ( ) @ 16.19
    13 63% Spanish_Pais_Vasco_IBS ( ) + 37% Balochi ( ) @ 16.94
    14 62.2% Spanish_Pais_Vasco_IBS ( ) + 37.8% Makrani ( ) @ 17.12
    15 57.7% Basque_French ( ) + 42.3% Sindhi ( ) @ 17.21
    16 61.4% Spanish_Pais_Vasco_IBS ( ) + 38.6% Burusho ( ) @ 17.47
    17 58.1% Basque_Spanish ( ) + 41.9% Sindhi ( ) @ 17.5
    18 55.8% Basque_French ( ) + 44.2% Tajik_Pomiri_Ishkashim ( ) @ 17.69
    19 63.3% Spanish_Pais_Vasco_IBS ( ) + 36.7% Sindhi ( ) @ 18
    20 57.5% Basque_French ( ) + 42.5% Pathan ( ) @ 18.07

    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 Z043955

    Admix Results (sorted):

    # Population Percent
    1 West_European 44.43
    2 West_Asian 16.27
    3 Mediterranean 11.41
    4 East_European 9.68
    5 Northeast_Asian 7.07
    6 South_Asian 6.98
    7 Southwest_Asian 3.03
    8 Northwest_African 1.13

    Single Population Sharing:

    # Population (source) Distance
    1 N._European (Xing) 18.11
    2 German (Dodecad) 19.05
    3 Argyll (1000 Genomes) 19.24
    4 Slovenian (Xing) 19.86
    5 CEU (HapMap) 20.06
    6 Orkney (1000 Genomes) 20.59
    7 Orcadian (HGDP) 20.67
    8 Mixed_Germanic (Dodecad) 21.06
    9 Dutch (Dodecad) 23.03
    10 Hungarians (Behar) 23.94
    11 Swedish (Dodecad) 24.25
    12 Kent (1000 Genomes) 24.7
    13 French (HGDP) 25.49
    14 British_Isles (Dodecad) 25.74
    15 British (Dodecad) 25.89
    16 Norwegian (Dodecad) 25.94
    17 Cornwall (1000 Genomes) 26.16
    18 FIN (1000Genomes) 26.21
    19 French (Dodecad) 26.32
    20 Irish (Dodecad) 27.15

    Mixed Mode Population Sharing:

    # Primary Population (source) Secondary Population (source) Distance
    1 66% Swedish (Dodecad) + 34% Makrani (HGDP) @ 8.22
    2 66.3% Swedish (Dodecad) + 33.7% Brahui (HGDP) @ 8.54
    3 66.1% Swedish (Dodecad) + 33.9% Balochi (HGDP) @ 8.54
    4 64.4% Norwegian (Dodecad) + 35.6% Makrani (HGDP) @ 8.6
    5 55% Swedish (Dodecad) + 45% Stalskoe (Xing) @ 8.7
    6 66.9% Swedish (Dodecad) + 33.1% Iranian (Dodecad) @ 8.86
    7 64.4% Norwegian (Dodecad) + 35.6% Balochi (HGDP) @ 8.94
    8 53.2% Norwegian (Dodecad) + 46.8% Stalskoe (Xing) @ 8.95
    9 64.7% Norwegian (Dodecad) + 35.3% Brahui (HGDP) @ 8.97
    10 67% Swedish (Dodecad) + 33% Iranians (Behar) @ 9.08
    11 65% Swedish (Dodecad) + 35% Kurd (Dodecad) @ 9.24
    12 65.3% Norwegian (Dodecad) + 34.7% Iranian (Dodecad) @ 9.28
    13 65.3% Norwegian (Dodecad) + 34.7% Iranians (Behar) @ 9.59
    14 76.2% N._European (Xing) + 23.8% Kalash (HGDP) @ 9.68
    15 66% Swedish (Dodecad) + 34% Kurd (Xing) @ 9.71
    16 63.3% Norwegian (Dodecad) + 36.7% Kurd (Dodecad) @ 9.73
    17 68.4% Mixed_Germanic (Dodecad) + 31.6% Uzbeks (Behar) @ 10.05
    18 68.9% Swedish (Dodecad) + 31.1% Kalash (HGDP) @ 10.15
    19 74.9% Argyll (1000 Genomes) + 25.1% Kalash (HGDP) @ 10.17
    20 64.3% Norwegian (Dodecad) + 35.7% Kurd (Xing) @ 10.19



    Admix Results (sorted):

    # Population Percent
    1 West_European 44.43
    2 West_Asian 16.27
    3 Mediterranean 11.41
    4 East_European 9.68
    5 Northeast_Asian 7.07
    6 South_Asian 6.98
    7 Southwest_Asian 3.03
    8 Northwest_African 1.13


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

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

    Least-squares method.

    Using 1 population approximation:
    1 N._European_Xing @ 19.587975
    2 German_Dodecad @ 20.626404
    3 Argyll_1000 Genomes @ 20.870298
    4 Slovenian_Xing @ 21.443300
    5 CEU_HapMap @ 21.743351
    6 Orkney_1000 Genomes @ 22.394287
    7 Orcadian_HGDP @ 22.468826
    8 Mixed_Germanic_Dodecad @ 22.877644
    9 Dutch_Dodecad @ 25.155624
    10 Hungarians_Behar @ 26.069534
    11 Swedish_Dodecad @ 26.744907
    12 Kent_1000 Genomes @ 27.057976
    13 French_HGDP @ 27.757040
    14 British_Isles_Dodecad @ 28.254417
    15 British_Dodecad @ 28.426506
    16 Norwegian_Dodecad @ 28.707932
    17 Cornwall_1000 Genomes @ 28.718632
    18 French_Dodecad @ 28.727285
    19 FIN_1000Genomes @ 29.225655
    20 Irish_Dodecad @ 29.886522

    Using 2 populations approximation:
    1 50% Swedish_Dodecad +50% Stalskoe_Xing @ 9.433094


    Using 3 populations approximation:
    1 50% British_Dodecad +25% Chuvashs_16_Behar +25% Kalash_HGDP @ 6.946078


    Using 4 populations approximation:
    ++++++++++++++++++++++++++++++++++++++++++++++++++ ++++++++++++++++++++++++++++++++++++++++++++++++++ +++++
    1 Chuvashs_16_Behar + Irish_Dodecad + Irish_Dodecad + Makrani_HGDP @ 6.192174
    2 Brahui_HGDP + Chuvashs_16_Behar + Irish_Dodecad + Irish_Dodecad @ 6.259570
    3 Chuvashs_16_Behar + Irish_Dodecad + Irish_Dodecad + Kalash_HGDP @ 6.329032
    4 Chuvashs_16_Behar + Cornwall_1000 Genomes + Irish_Dodecad + Kalash_HGDP @ 6.438259
    5 Balochi_HGDP + Chuvashs_16_Behar + Irish_Dodecad + Irish_Dodecad @ 6.475193
    6 British_Dodecad + Chuvashs_16_Behar + Irish_Dodecad + Kalash_HGDP @ 6.579153
    7 Chuvashs_16_Behar + Cornwall_1000 Genomes + Irish_Dodecad + Makrani_HGDP @ 6.605404
    8 Brahui_HGDP + Chuvashs_16_Behar + Cornwall_1000 Genomes + Irish_Dodecad @ 6.621923
    9 Chuvashs_16_Behar + Cornwall_1000 Genomes + Cornwall_1000 Genomes + Kalash_HGDP @ 6.661192
    10 British_Isles_Dodecad + Chuvashs_16_Behar + Irish_Dodecad + Kalash_HGDP @ 6.685716
    11 British_Dodecad + Chuvashs_16_Behar + Irish_Dodecad + Makrani_HGDP @ 6.798785
    12 British_Dodecad + Chuvashs_16_Behar + Cornwall_1000 Genomes + Kalash_HGDP @ 6.801534
    13 Brahui_HGDP + British_Dodecad + Chuvashs_16_Behar + Irish_Dodecad @ 6.819864
    14 Balochi_HGDP + Chuvashs_16_Behar + Cornwall_1000 Genomes + Irish_Dodecad @ 6.822198
    15 British_Isles_Dodecad + Chuvashs_16_Behar + Irish_Dodecad + Makrani_HGDP @ 6.846113
    16 Brahui_HGDP + British_Isles_Dodecad + Chuvashs_16_Behar + Irish_Dodecad @ 6.871347
    17 British_Isles_Dodecad + Chuvashs_16_Behar + Cornwall_1000 Genomes + Kalash_HGDP @ 6.887172
    18 Chuvashs_16_Behar + Irish_Dodecad + Kalash_HGDP + Kent_1000 Genomes @ 6.889717
    19 British_Dodecad + British_Dodecad + Chuvashs_16_Behar + Kalash_HGDP @ 6.946078
    20 Balochi_HGDP + British_Dodecad + Chuvashs_16_Behar + Irish_Dodecad @ 7.026371
    nMonte3 current
    Velamas Gujarati_D Muslim_UP Tharus Punjabi_1000genomes
    1.859005 3.210341 4.491247 4.998440 6.040323

    G25 Ancients Dist 0.99 Shahr_I_Sokhta_BA3:S8728.E1.L1 65.2 Saidu_Sharif_IA_o:S7722.E1.L1 17.8 Udegram_IA:I1985 7.8 Jordanian:S_Jordanian-1 4.4 Barikot_IA:I6545 2.2 Scotland_N:I26602 Narva_Lithuania: Donkalnis6

    mtDNA mutation 309.1C 315.1C 522.1A 522.2C G8572A G8860A T11368C T16093a T16154C C16519T
    C195T

  6. The Following User Says Thank You to tipirneni For This Useful Post:

     bmoney (12-17-2018)

  7. #85
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    Post Some related admixure

    MATCH BETWEEN SURESH TIPIRNENI & PAK GUJAR SAMPLES on Genesis GED
    Out of 3 kits FTDNA, MyHeritage & Ancestry DNA there is only a minor difference between them
    GED DEsc Total Max No of
    ZA8180497 (*PK_GUJAR::G-60) 408.1 cM (11.395 Pct) 10.2 cM 194
    UJ1114322 (*PK_GUJAR::G-72) 408.8 cM (11.414 Pct) 8.8 cM 194
    RF6904387 (*PK_GUJAR::G-81) 379.5 cM (10.596 Pct) 6.6 cM 191
    WY3185562 (*PK_GUJAR::G-82) 380.2 cM (10.615 Pct) 5.3 cM 188
    WA8871320 (*PK_GUJAR::G-83) 362.5 cM (10.121 Pct) 6.8 cM 173
    YH3386715 (*PK_GUJAR::G-84) 402.6 cM (11.240 Pct) 8.1 cM 197
    AP5209679 (*PK_GUJAR::G-89) 376.0 cM (10.497 Pct) 6.8 cM 189
    HN7606120 (*PK_GUJAR::G-95) 383.8 cM (10.716 Pct) 5.4 cM 191
    NZ2721526 (*PK_GUJAR::G-97) 321.6 cM (8.978 Pct) 8.0 cM 155
    DQ3353422 (*PK_GUJAR::G-113) 412.9 cM (11.529 Pct) 7.0 cM 197
    XM4818987 (*PK_GUJAR::G-117) 387.0 cM (10.804 Pct) 7.5 cM 186
    TL8063285 (*PK_GUJAR::G-140) 380.8 cM (10.632 Pct) 5.6 cM 186
    ZM1080505 (*PK_GUJAR::G-157) 377.8 cM (10.549 Pct) 5.2 cM 183
    RF3163214 (*PK_GUJAR::G-168) 402.7 cM (11.244 Pct) 6.3 cM 190
    YK3610676 (*PK_GUJAR::G-182) 428.6 cM (11.967 Pct) 6.4 cM 207
    QX9647569 (*PK_GUJAR::G-185) 375.1 cM (10.473 Pct) 7.2 cM 179
    ZF7468281 (*PK_GUJAR::GM-35) 427.6 cM (11.939 Pct) 7.0 cM 210

    Out of the unrelated groups on Genesis, these Gujar samples are high match after which there are Kshatriya samples, Uyghur samples, Burusho, Iranian, Bengali samples. The Gypsy samples & Iraqi samples are also unrelated ones that produce high matches.

    Gujar Uploaded by Khana
    https://anthrogenica.com/showthread.php?14155-Global25-automated-nMonte-for-South-Central-Asian-members&p=397486&viewfull=1#post397486
    nMonte3 current
    Velamas Gujarati_D Muslim_UP Tharus Punjabi_1000genomes
    1.859005 3.210341 4.491247 4.998440 6.040323

    G25 Ancients Dist 0.99 Shahr_I_Sokhta_BA3:S8728.E1.L1 65.2 Saidu_Sharif_IA_o:S7722.E1.L1 17.8 Udegram_IA:I1985 7.8 Jordanian:S_Jordanian-1 4.4 Barikot_IA:I6545 2.2 Scotland_N:I26602 Narva_Lithuania: Donkalnis6

    mtDNA mutation 309.1C 315.1C 522.1A 522.2C G8572A G8860A T11368C T16093a T16154C C16519T
    C195T

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     agent_lime (01-07-2019)

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