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Thread: Global25 automated nMonte for South/Central Asian members

  1. #7771
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    Quote Originally Posted by misanthropy View Post
    That reminds me. On this past group run of interior Indians, I had the second lowest Brahmin (Kush had the lowest) yet the highest South Central Asian (Kalash + Burusho): https://anthrogenica.com/showthread....l=1#post494676

    It sounds like whatever steppe contribution I have may be mediated via more recent Central Asian Muslim migrants rather the subcontinental Brahmin source?

    Could you see which type of steppe group I have more affinity to?

    misanthropy_scaled,0.0387,-0.058901,-0.144814,0.09044,-0.07386,0.048248,0,0.010384,0.043768,0.019135,-0.004547,-0.001948,-0.001784,0.003853,-0.003257,-0.00716,-0.00678,0.001647,0.001885,0.001626,0.002121,0.0059 35,-0.001232,0.007591,-0.005628
    Target: misanthropy_scaled
    Distance: 1.6214% / 0.01621359
    24.2 S_AASI_Sim_Avg
    17.2 Iran_Neolithic:IRN_Ganj_Dareh_N:I1945
    14.8 NW_AASI_Sim_Avg
    12.4 Iran_Neolithic:IRN_Wezmeh_N:WC1
    7.6 Steppe_Pastoralist:RUS_Afanasievo:I5271
    5.4 Eastern_Hunter-Gatherer:RUS_Karelia_HG:I0211
    4.6 Early_Levantine_Farmer:Levant_Natufian:I1072
    3.8 Iran_Neolithic:IRN_Ganj_Dareh_N:I1947
    3.6 Early_European_Farmer:Anatolia_Barcin_N:I0727
    2.2 Ancient_American:USA_Alaska_TrailCreek_9000BP:Trai lCreek
    1.4 Early_European_Farmer:Anatolia_Barcin_N:I0709
    1.4 Africa_Mesolithic:MWI_Hora_9000BP:I2966
    1.2 Northeastern_Asia_Neolithic:RUS_Devils_Gate_Cave_N :NEO240
    0.2 Steppe_Pastoralist:Yamnaya_RUS_Kalmykia:RISE547

    Second model I found:
    Target: misanthropy_scaled
    Distance: 1.4795% / 0.01479474
    23.8 S_AASI_Sim_Avg
    12.8 NW_AASI_Sim_Avg
    11.8 IranianFarmer:IRN_Ganj_Dareh_N:I1945
    11.6 IranianFarmer:IRN_Wezmeh_N:WC1
    7.2 IndoEuropeanSteppePastoralist:Yamnaya_RUS_Kalmykia :RISE547
    7.0 IranianFarmer:IRN_Ganj_Dareh_N:I1947
    6.0 Harappan:IRN_Shahr_I_Sokhta_BA2:I8728
    4.8 WestSiberianHunterGatherer:RUS_Tyumen_HG:I1960
    3.8 LevantineFarmer:Levant_Natufian:I1072
    3.6 AnatolianFarmer:TUR_Barcin_N:I0709
    2.4 AnatolianFarmer:TUR_Barcin_N:I0727
    1.8 EastEuropeanHunterGatherer:RUS_Karelia_HG:I0211
    1.4 NorthSiberian:RUS_Yana_MA:Yana_Young
    1.2 Nilotic:KEN_Kakapel_900BP:KPL003
    0.6 Sinic:CHN_Yellow_River_MN:WGM35
    0.2 SouthAfricanForager:ZAF_2100BP:I9028
    Last edited by maroco; 11-12-2020 at 08:42 AM.

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  3. #7772
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    @ Pegasus

    I would appreciate some help modelling this guy, he's Kashmiri but seems to be heavily IVC shifted in my runs. How would you model him?

    Bronze Age Model:
    sample: Jurble
    distance: 2.4694
    Shahr_I_Sokhta_BA3: 52.5
    Gonur1_BA: 30
    Srubnaya_Alakul_MLBA: 12
    Chokhopani_2700BP: 5.5

    Neolithic Model:
    sample: Jurble
    distance: 2.5303
    Ganj_Dareh_N: 39.5
    Simulated_AASI_NW_by_DMXX: 20.5
    Barcin_N: 15
    Karelia_HG: 8
    LAO_Hoabinhian: 7.5
    Kolyma_Meso: 4.5
    Tyumen_HG: 3
    GEO_CHG: 1.5
    Boshan_N: 0.5

    Coordinates:
    Jurble_scaled,0.063741,-0.026404,-0.115399,0.07752,-0.069859,0.053547,0.00094,0.001615,0.00409,0.00437 4,-0.013803,0.00045,0.000892,-0.001651,0.000407,0.002254,-0.004563,-0.001647,-0.001006,-0.006628,0.00262,0.001978,0.001849,0.000964,0.0016 76
    G25 Neolithic model

    "sample": "kamil154",
    "distance": 2.2284,
    "Ganj_Dareh_N": 41,
    "Barcin_N": 18,
    "Simulated_AASI_NW_by_DMXX": 17,
    "Karelia_HG": 10.5,
    "GEO_CHG": 3.5,
    "Tyumen_HG": 3,
    "LAO_Hoabinhian": 2.5,
    "LapaDoSanto_9600BP": 2.5,
    "Boshan_N": 2

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  5. #7773
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    Quote Originally Posted by kamil154 View Post
    @ Pegasus

    I would appreciate some help modelling this guy, he's Kashmiri but seems to be heavily IVC shifted in my runs. How would you model him?

    Bronze Age Model:
    sample: Jurble
    distance: 2.4694
    Shahr_I_Sokhta_BA3: 52.5
    Gonur1_BA: 30
    Srubnaya_Alakul_MLBA: 12
    Chokhopani_2700BP: 5.5

    Neolithic Model:
    sample: Jurble
    distance: 2.5303
    Ganj_Dareh_N: 39.5
    Simulated_AASI_NW_by_DMXX: 20.5
    Barcin_N: 15
    Karelia_HG: 8
    LAO_Hoabinhian: 7.5
    Kolyma_Meso: 4.5
    Tyumen_HG: 3
    GEO_CHG: 1.5
    Boshan_N: 0.5

    Coordinates:
    Jurble_scaled,0.063741,-0.026404,-0.115399,0.07752,-0.069859,0.053547,0.00094,0.001615,0.00409,0.00437 4,-0.013803,0.00045,0.000892,-0.001651,0.000407,0.002254,-0.004563,-0.001647,-0.001006,-0.006628,0.00262,0.001978,0.001849,0.000964,0.0016 76
    Finally-another Kashmiri! I have been waiting lol

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  7. #7774
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    Quote Originally Posted by kamil154 View Post
    @ Pegasus

    I would appreciate some help modelling this guy, he's Kashmiri but seems to be heavily IVC shifted in my runs. How would you model him?

    Bronze Age Model:
    sample: Jurble
    distance: 2.4694
    Shahr_I_Sokhta_BA3: 52.5
    Gonur1_BA: 30
    Srubnaya_Alakul_MLBA: 12
    Chokhopani_2700BP: 5.5

    Neolithic Model:
    sample: Jurble
    distance: 2.5303
    Ganj_Dareh_N: 39.5
    Simulated_AASI_NW_by_DMXX: 20.5
    Barcin_N: 15
    Karelia_HG: 8
    LAO_Hoabinhian: 7.5
    Kolyma_Meso: 4.5
    Tyumen_HG: 3
    GEO_CHG: 1.5
    Boshan_N: 0.5

    Coordinates:
    Jurble_scaled,0.063741,-0.026404,-0.115399,0.07752,-0.069859,0.053547,0.00094,0.001615,0.00409,0.00437 4,-0.013803,0.00045,0.000892,-0.001651,0.000407,0.002254,-0.004563,-0.001647,-0.001006,-0.006628,0.00262,0.001978,0.001849,0.000964,0.0016 76
    He is within range but he has lower Turan/BMAC related ancestry compared to most Kashmiris as well a bit higher AASI.



    "sample": ":Kashmiri",
    "distance": 1.824,
    "Shahr_I_Sokhta_BA2": 61.5,
    "TKM_IA": 32.5,
    "Chokhopani_2700BP": 6

    penalty =0

    "sample": "Kashmiri",
    "distance": 1.7689,
    "Shahr_I_Sokhta_BA2": 60.5,
    "TKM_IA": 34,
    "Chokhopani_2700BP": 5.5



    "sample": "Kashmiri",
    "distance": 1.8325,
    "Shahr_I_Sokhta_BA2": 58.5,
    "Dzharkutan1_BA": 17.5,
    "Srubnaya_MLBA": 17.5,
    "Chokhopani_2700BP": 6.5

    SIS2= 8728/1459

    I have to also do models for others and have been a bit behind .

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  9. #7775
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    Those 3 Bahun samples (Ba15, Ba25, Ba37) in the G25 collection are likely mislabeled Chhetris. Tried to get closer fits with simple random 4 way modeling with modern pops. All of these samples require excess AASI and IranN source over AG Bahun users to get better fits. So, I guess they're most likely not Bahuns with excess Mongoloid but rather Chhetris. As we know the gedmatch calculators also indicated Chhetris having a bit higher S-Indian ratio than Bahuns, so they're likely Bahuns + excess IVC + excess Tibetan.

    Target: Likely Chhetri:Ba15
    Distance: 1.6100% / 0.01610026
    32.8 Brahmin_Uttar_Pradesh
    30.0 Brahmin_Khas_Nepal
    25.2 Tamang
    12.0 Brahui

    Target: Likely Chhetri:Ba25
    Distance: 1.9529% / 0.01952893
    44.8 Brahmin_Khas_Nepal
    23.8 Yadava
    22.8 Tibetan_Yajiang
    8.6 Brahui

    Target: Likely Chhetri:Ba37
    Distance: 2.1646% / 0.02164591
    33.4 Brahmin_Khas_Nepal
    32.0 Kol
    25.4 Tibetan_Yajiang
    9.2 Brahui

    An extra Yemenite and Amerindian source for Ba15 sample reduced the fit significantly.
    Target: Likely Chhetri:Ba15
    Distance: 1.4306% / 0.01430575
    37.6 Brahmin_Uttar_Pradesh
    25.6 Brahmin_Khas_Nepal
    24.6 Tamang
    8.2 Brahui
    2.8 Yemenite_Mahra
    1.2 Mixtec

    For Ba25, when Tibetan_Yajiang is replaced by Dongxiang and Papuan, fit is reduced significantly.
    Target: Likely Chhetri:Ba25
    Distance: 1.7258% / 0.01725834
    44.0 Brahmin_Khas_Nepal
    25.0 Dongxiang
    24.6 Yadava
    5.0 Brahui
    1.4 Papuan

    For these samples, I've found Khatri, Sindhi, Brahui, Yadava, Kol, Gujar, Gujarati Brahmin, UP Brahmin, Tibetan Yajiang and Tamang gives better fits among many others.

  10. #7776
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    Looking at some ancients on G25 and testing them on qpAdm, the model is a resounding success and pretty much similar to my G25 model when you factor in standard errors.

    sample: Bustan BA o2:Average
    distance: 1.544
    Shahr_I_Sokhta_BA3: 50
    Alalakh_MLBA_o: 38
    Zevakinskiy_MLBA: 12


    left pops:
    Uzbekistan_BA_Bustan_o2
    SISI8728
    Alalakh_MLBA_outlier
    Kazakhstan_MLBA_Zevakinskiy

    right pops:
    Cameroon_SMA.DG
    Russia_Steppe_Eneolithic
    Australian.DG
    PPNB
    Iran_GanjDareh_N
    DevilsCave_N.SG
    Russia_UstBelaya_Angara
    EHG
    Anatolia_N
    WSHG
    Russia_MA1_HG.SG
    CHG
    Russia_MLBA_Sintashta
    Sweden_HG_Motala

    0 Uzbekistan_BA_Bustan_o2 1
    1 SISI8728 1
    2 Alalakh_MLBA_outlier 1
    3 Kazakhstan_MLBA_Zevakinskiy 1
    4 Cameroon_SMA.DG 1
    5 Russia_Steppe_Eneolithic 3
    6 Australian.DG 2
    7 PPNB 11
    8 Iran_GanjDareh_N 8
    9 DevilsCave_N.SG 4
    10 Russia_UstBelaya_Angara 11
    11 EHG 3
    12 Anatolia_N 30
    13 WSHG 3
    14 Russia_MA1_HG.SG 1
    15 CHG 2
    16 Russia_MLBA_Sintashta 19
    17 Sweden_HG_Motala 6
    jackknife block size: 0.050
    snps: 1150471 indivs: 108
    number of blocks for block jackknife: 714
    ## ncols: 1150471
    coverage: Uzbekistan_BA_Bustan_o2 766753
    coverage: SISI8728 645800
    coverage: Alalakh_MLBA_outlier 733730
    coverage: Kazakhstan_MLBA_Zevakinskiy 711062
    coverage: Cameroon_SMA.DG 1140138
    coverage: Russia_Steppe_Eneolithic 1008226
    coverage: Australian.DG 1120959
    coverage: PPNB 871625
    coverage: Iran_GanjDareh_N 1057358
    coverage: DevilsCave_N.SG 1149702
    coverage: Russia_UstBelaya_Angara 1092594
    coverage: EHG 1027057
    coverage: Anatolia_N 1141220
    coverage: WSHG 858019
    coverage: Russia_MA1_HG.SG 805960
    coverage: CHG 1149558
    coverage: Russia_MLBA_Sintashta 1115156
    coverage: Sweden_HG_Motala 1038843
    Effective number of blocks: 618.643
    numsnps used: 380056
    codimension 1
    f4info:
    f4rank: 2 dof: 11 chisq: 4.460 tail: 0.954472637 dofdiff: 13 chisqdiff: -4.460 taildiff: 1
    B:
    scale 1.000 1.000
    Russia_Steppe_Eneolithic 1.110 -0.547
    Australian.DG -0.566 0.776
    PPNB 0.857 -0.653
    Iran_GanjDareh_N 0.193 -2.163
    DevilsCave_N.SG -0.062 1.055
    Russia_UstBelaya_Angara 0.317 1.317
    EHG 1.606 0.836
    Anatolia_N 1.017 -0.819
    WSHG 1.289 0.774
    Russia_MA1_HG.SG 0.966 0.323
    CHG 0.489 -1.295
    Russia_MLBA_Sintashta 1.299 -0.151
    Sweden_HG_Motala 1.561 0.615
    A:
    scale 614.836 1472.057
    SISI8728 -0.761 0.544
    Alalakh_MLBA_outlier 0.598 -1.407
    Kazakhstan_MLBA_Zevakinskiy 1.436 0.851


    full rank
    f4info:
    f4rank: 3 dof: 0 chisq: 0.000 tail: 1 dofdiff: 11 chisqdiff: 4.460 taildiff: 0.954472637
    B:
    scale 771.094 713.050 397.966
    Russia_Steppe_Eneolithic -1.174 1.220 0.989
    Australian.DG 0.698 -0.928 -0.315
    PPNB -1.018 1.092 0.694
    Iran_GanjDareh_N -0.769 1.696 -0.249
    DevilsCave_N.SG 0.353 -0.728 0.238
    Russia_UstBelaya_Angara 0.102 -0.621 0.665
    EHG -1.092 0.737 1.815
    Anatolia_N -1.246 1.271 0.786
    WSHG -0.949 0.411 1.449
    Russia_MA1_HG.SG -1.184 0.189 0.903
    CHG -0.735 1.357 0.245
    Russia_MLBA_Sintashta -1.240 1.069 1.238
    Sweden_HG_Motala -1.499 0.565 1.568
    A:
    scale 1.732 1.732 1.732
    SISI8728 1.732 0.000 0.000
    Alalakh_MLBA_outlier 0.000 1.732 0.000
    Kazakhstan_MLBA_Zevakinskiy 0.000 0.000 1.732


    best coefficients: 0.538 0.304 0.159
    Jackknife mean: 0.537324048 0.303438160 0.159237792
    std. errors: 0.047 0.058 0.046


    error covariance (* 1,000,000)
    2232 -1762 -470
    -1762 3421 -1659
    -470 -1659 2129


    summ: Uzbekistan_BA_Bustan_o2 3 0.954473 0.537 0.303 0.159


    Narasimhan's models for him are very poor

    Indus_Periphery_Pool Western_Steppe_MLBA ..p= 0.01 0.847 0.153
    Indus_Periphery_Pool Central_Steppe_MLBA .. p=0.021 0.836 0.164




    With Loebanr_0

    sample: Loebanr IA o:Average
    distance: 2.492
    Oy_Dzhaylau_MLBA: 38
    Alalakh_MLBA_o: 34
    Shahr_I_Sokhta_BA2: 28


    On qpAdm another great working model but not as good as the one for Bustan_o2.



    Best coefficients: 0.344 0.313 0.343
    Jackknife mean: 0.342802153 0.314344114 0.342853733
    std. errors: 0.067 0.086 0.035

    error covariance (* 1,000,000)
    4448 -5308 860
    -5308 7428 -2119
    860 -2119 1259


    summ: Pakistan_IA_Loebanr_o_published 3 0.745909 0.343 0.314 0.343 4448




    Modern populations which work well with Alalakh_o:

    sample: Gujar Pakistan:G-83
    distance: 1.9193
    Shahr_I_Sokhta_BA2: 57.5
    Alalakh_MLBA_o: 27.5
    Oy_Dzhaylau_MLBA: 12.5
    Chokhopani_2700BP: 2.5




    sample: Kashmiri Pandit:Average
    distance: 1.9064
    Shahr_I_Sokhta_BA3: 30.5
    Alalakh_MLBA_o: 24
    Shahr_I_Sokhta_BA2: 22
    Oy_Dzhaylau_MLBA: 19
    Chokhopani_2700BP: 4.5

    sample: Punjabi Sikh India PanSikh27270
    distance: 1.5372
    Shahr_I_Sokhta_BA2: 50
    Oy_Dzhaylau_MLBA: 27
    Alalakh_MLBA_o: 23
    Last edited by pegasus; 11-19-2020 at 11:43 PM.

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  12. #7777
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    Quote Originally Posted by pegasus View Post
    Looking at some ancients on G25 and testing them on qpAdm, the model is a resounding success and pretty much similar to my G25 model when you factor in standard errors.

    sample: Bustan BA o2:Average
    distance: 1.544
    Shahr_I_Sokhta_BA3: 50
    Alalakh_MLBA_o: 38
    Zevakinskiy_MLBA: 12


    left pops:
    Uzbekistan_BA_Bustan_o2
    SISI8728
    Alalakh_MLBA_outlier
    Kazakhstan_MLBA_Zevakinskiy

    right pops:
    Cameroon_SMA.DG
    Russia_Steppe_Eneolithic
    Australian.DG
    PPNB
    Iran_GanjDareh_N
    DevilsCave_N.SG
    Russia_UstBelaya_Angara
    EHG
    Anatolia_N
    WSHG
    Russia_MA1_HG.SG
    CHG
    Russia_MLBA_Sintashta
    Sweden_HG_Motala

    0 Uzbekistan_BA_Bustan_o2 1
    1 SISI8728 1
    2 Alalakh_MLBA_outlier 1
    3 Kazakhstan_MLBA_Zevakinskiy 1
    4 Cameroon_SMA.DG 1
    5 Russia_Steppe_Eneolithic 3
    6 Australian.DG 2
    7 PPNB 11
    8 Iran_GanjDareh_N 8
    9 DevilsCave_N.SG 4
    10 Russia_UstBelaya_Angara 11
    11 EHG 3
    12 Anatolia_N 30
    13 WSHG 3
    14 Russia_MA1_HG.SG 1
    15 CHG 2
    16 Russia_MLBA_Sintashta 19
    17 Sweden_HG_Motala 6
    jackknife block size: 0.050
    snps: 1150471 indivs: 108
    number of blocks for block jackknife: 714
    ## ncols: 1150471
    coverage: Uzbekistan_BA_Bustan_o2 766753
    coverage: SISI8728 645800
    coverage: Alalakh_MLBA_outlier 733730
    coverage: Kazakhstan_MLBA_Zevakinskiy 711062
    coverage: Cameroon_SMA.DG 1140138
    coverage: Russia_Steppe_Eneolithic 1008226
    coverage: Australian.DG 1120959
    coverage: PPNB 871625
    coverage: Iran_GanjDareh_N 1057358
    coverage: DevilsCave_N.SG 1149702
    coverage: Russia_UstBelaya_Angara 1092594
    coverage: EHG 1027057
    coverage: Anatolia_N 1141220
    coverage: WSHG 858019
    coverage: Russia_MA1_HG.SG 805960
    coverage: CHG 1149558
    coverage: Russia_MLBA_Sintashta 1115156
    coverage: Sweden_HG_Motala 1038843
    Effective number of blocks: 618.643
    numsnps used: 380056
    codimension 1
    f4info:
    f4rank: 2 dof: 11 chisq: 4.460 tail: 0.954472637 dofdiff: 13 chisqdiff: -4.460 taildiff: 1
    B:
    scale 1.000 1.000
    Russia_Steppe_Eneolithic 1.110 -0.547
    Australian.DG -0.566 0.776
    PPNB 0.857 -0.653
    Iran_GanjDareh_N 0.193 -2.163
    DevilsCave_N.SG -0.062 1.055
    Russia_UstBelaya_Angara 0.317 1.317
    EHG 1.606 0.836
    Anatolia_N 1.017 -0.819
    WSHG 1.289 0.774
    Russia_MA1_HG.SG 0.966 0.323
    CHG 0.489 -1.295
    Russia_MLBA_Sintashta 1.299 -0.151
    Sweden_HG_Motala 1.561 0.615
    A:
    scale 614.836 1472.057
    SISI8728 -0.761 0.544
    Alalakh_MLBA_outlier 0.598 -1.407
    Kazakhstan_MLBA_Zevakinskiy 1.436 0.851


    full rank
    f4info:
    f4rank: 3 dof: 0 chisq: 0.000 tail: 1 dofdiff: 11 chisqdiff: 4.460 taildiff: 0.954472637
    B:
    scale 771.094 713.050 397.966
    Russia_Steppe_Eneolithic -1.174 1.220 0.989
    Australian.DG 0.698 -0.928 -0.315
    PPNB -1.018 1.092 0.694
    Iran_GanjDareh_N -0.769 1.696 -0.249
    DevilsCave_N.SG 0.353 -0.728 0.238
    Russia_UstBelaya_Angara 0.102 -0.621 0.665
    EHG -1.092 0.737 1.815
    Anatolia_N -1.246 1.271 0.786
    WSHG -0.949 0.411 1.449
    Russia_MA1_HG.SG -1.184 0.189 0.903
    CHG -0.735 1.357 0.245
    Russia_MLBA_Sintashta -1.240 1.069 1.238
    Sweden_HG_Motala -1.499 0.565 1.568
    A:
    scale 1.732 1.732 1.732
    SISI8728 1.732 0.000 0.000
    Alalakh_MLBA_outlier 0.000 1.732 0.000
    Kazakhstan_MLBA_Zevakinskiy 0.000 0.000 1.732


    best coefficients: 0.538 0.304 0.159
    Jackknife mean: 0.537324048 0.303438160 0.159237792
    std. errors: 0.047 0.058 0.046


    error covariance (* 1,000,000)
    2232 -1762 -470
    -1762 3421 -1659
    -470 -1659 2129


    summ: Uzbekistan_BA_Bustan_o2 3 0.954473 0.537 0.303 0.159


    Narasimhan's models for him are very poor

    Indus_Periphery_Pool Western_Steppe_MLBA ..p= 0.01 0.847 0.153
    Indus_Periphery_Pool Central_Steppe_MLBA .. p=0.021 0.836 0.164




    With Loebanr_0

    sample: Loebanr IA o:Average
    distance: 2.492
    Oy_Dzhaylau_MLBA: 38
    Alalakh_MLBA_o: 34
    Shahr_I_Sokhta_BA2: 28


    On qpAdm another great working model but not as good as the one for Bustan_o2.



    Best coefficients: 0.344 0.313 0.343
    Jackknife mean: 0.342802153 0.314344114 0.342853733
    std. errors: 0.067 0.086 0.035

    error covariance (* 1,000,000)
    4448 -5308 860
    -5308 7428 -2119
    860 -2119 1259


    summ: Pakistan_IA_Loebanr_o_published 3 0.745909 0.343 0.314 0.343 4448




    Modern populations which work well with Alalakh_o:

    sample: Gujar Pakistan:G-83
    distance: 1.9193
    Shahr_I_Sokhta_BA2: 57.5
    Alalakh_MLBA_o: 27.5
    Oy_Dzhaylau_MLBA: 12.5
    Chokhopani_2700BP: 2.5




    sample: Kashmiri Pandit:Average
    distance: 1.9064
    Shahr_I_Sokhta_BA3: 30.5
    Alalakh_MLBA_o: 24
    Shahr_I_Sokhta_BA2: 22
    Oy_Dzhaylau_MLBA: 19
    Chokhopani_2700BP: 4.5

    sample: Punjabi Sikh India PanSikh27270
    distance: 1.5372
    Shahr_I_Sokhta_BA2: 50
    Oy_Dzhaylau_MLBA: 27
    Alalakh_MLBA_o: 23
    Can we see your results? Thank you

  13. #7778
    Gold Class Member
    Posts
    4,348
    Location
    Shangri La

    Afghanistan Jammu and Kashmir United States of America Canada
    Quote Originally Posted by pegasus View Post
    Looking at some ancients on G25 and testing them on qpAdm, the model is a resounding success and pretty much similar to my G25 model when you factor in standard errors.

    sample: Bustan BA o2:Average
    distance: 1.544
    Shahr_I_Sokhta_BA3: 50
    Alalakh_MLBA_o: 38
    Zevakinskiy_MLBA: 12


    left pops:
    Uzbekistan_BA_Bustan_o2
    SISI8728
    Alalakh_MLBA_outlier
    Kazakhstan_MLBA_Zevakinskiy

    right pops:
    Cameroon_SMA.DG
    Russia_Steppe_Eneolithic
    Australian.DG
    PPNB
    Iran_GanjDareh_N
    DevilsCave_N.SG
    Russia_UstBelaya_Angara
    EHG
    Anatolia_N
    WSHG
    Russia_MA1_HG.SG
    CHG
    Russia_MLBA_Sintashta
    Sweden_HG_Motala

    0 Uzbekistan_BA_Bustan_o2 1
    1 SISI8728 1
    2 Alalakh_MLBA_outlier 1
    3 Kazakhstan_MLBA_Zevakinskiy 1
    4 Cameroon_SMA.DG 1
    5 Russia_Steppe_Eneolithic 3
    6 Australian.DG 2
    7 PPNB 11
    8 Iran_GanjDareh_N 8
    9 DevilsCave_N.SG 4
    10 Russia_UstBelaya_Angara 11
    11 EHG 3
    12 Anatolia_N 30
    13 WSHG 3
    14 Russia_MA1_HG.SG 1
    15 CHG 2
    16 Russia_MLBA_Sintashta 19
    17 Sweden_HG_Motala 6
    jackknife block size: 0.050
    snps: 1150471 indivs: 108
    number of blocks for block jackknife: 714
    ## ncols: 1150471
    coverage: Uzbekistan_BA_Bustan_o2 766753
    coverage: SISI8728 645800
    coverage: Alalakh_MLBA_outlier 733730
    coverage: Kazakhstan_MLBA_Zevakinskiy 711062
    coverage: Cameroon_SMA.DG 1140138
    coverage: Russia_Steppe_Eneolithic 1008226
    coverage: Australian.DG 1120959
    coverage: PPNB 871625
    coverage: Iran_GanjDareh_N 1057358
    coverage: DevilsCave_N.SG 1149702
    coverage: Russia_UstBelaya_Angara 1092594
    coverage: EHG 1027057
    coverage: Anatolia_N 1141220
    coverage: WSHG 858019
    coverage: Russia_MA1_HG.SG 805960
    coverage: CHG 1149558
    coverage: Russia_MLBA_Sintashta 1115156
    coverage: Sweden_HG_Motala 1038843
    Effective number of blocks: 618.643
    numsnps used: 380056
    codimension 1
    f4info:
    f4rank: 2 dof: 11 chisq: 4.460 tail: 0.954472637 dofdiff: 13 chisqdiff: -4.460 taildiff: 1
    B:
    scale 1.000 1.000
    Russia_Steppe_Eneolithic 1.110 -0.547
    Australian.DG -0.566 0.776
    PPNB 0.857 -0.653
    Iran_GanjDareh_N 0.193 -2.163
    DevilsCave_N.SG -0.062 1.055
    Russia_UstBelaya_Angara 0.317 1.317
    EHG 1.606 0.836
    Anatolia_N 1.017 -0.819
    WSHG 1.289 0.774
    Russia_MA1_HG.SG 0.966 0.323
    CHG 0.489 -1.295
    Russia_MLBA_Sintashta 1.299 -0.151
    Sweden_HG_Motala 1.561 0.615
    A:
    scale 614.836 1472.057
    SISI8728 -0.761 0.544
    Alalakh_MLBA_outlier 0.598 -1.407
    Kazakhstan_MLBA_Zevakinskiy 1.436 0.851


    full rank
    f4info:
    f4rank: 3 dof: 0 chisq: 0.000 tail: 1 dofdiff: 11 chisqdiff: 4.460 taildiff: 0.954472637
    B:
    scale 771.094 713.050 397.966
    Russia_Steppe_Eneolithic -1.174 1.220 0.989
    Australian.DG 0.698 -0.928 -0.315
    PPNB -1.018 1.092 0.694
    Iran_GanjDareh_N -0.769 1.696 -0.249
    DevilsCave_N.SG 0.353 -0.728 0.238
    Russia_UstBelaya_Angara 0.102 -0.621 0.665
    EHG -1.092 0.737 1.815
    Anatolia_N -1.246 1.271 0.786
    WSHG -0.949 0.411 1.449
    Russia_MA1_HG.SG -1.184 0.189 0.903
    CHG -0.735 1.357 0.245
    Russia_MLBA_Sintashta -1.240 1.069 1.238
    Sweden_HG_Motala -1.499 0.565 1.568
    A:
    scale 1.732 1.732 1.732
    SISI8728 1.732 0.000 0.000
    Alalakh_MLBA_outlier 0.000 1.732 0.000
    Kazakhstan_MLBA_Zevakinskiy 0.000 0.000 1.732


    best coefficients: 0.538 0.304 0.159
    Jackknife mean: 0.537324048 0.303438160 0.159237792
    std. errors: 0.047 0.058 0.046


    error covariance (* 1,000,000)
    2232 -1762 -470
    -1762 3421 -1659
    -470 -1659 2129


    summ: Uzbekistan_BA_Bustan_o2 3 0.954473 0.537 0.303 0.159


    Narasimhan's models for him are very poor

    Indus_Periphery_Pool Western_Steppe_MLBA ..p= 0.01 0.847 0.153
    Indus_Periphery_Pool Central_Steppe_MLBA .. p=0.021 0.836 0.164




    With Loebanr_0

    sample: Loebanr IA o:Average
    distance: 2.492
    Oy_Dzhaylau_MLBA: 38
    Alalakh_MLBA_o: 34
    Shahr_I_Sokhta_BA2: 28


    On qpAdm another great working model but not as good as the one for Bustan_o2.



    Best coefficients: 0.344 0.313 0.343
    Jackknife mean: 0.342802153 0.314344114 0.342853733
    std. errors: 0.067 0.086 0.035

    error covariance (* 1,000,000)
    4448 -5308 860
    -5308 7428 -2119
    860 -2119 1259


    summ: Pakistan_IA_Loebanr_o_published 3 0.745909 0.343 0.314 0.343




    Modern populations which work well with Alalakh_o:

    sample: Gujar Pakistan:G-83
    distance: 1.9193
    Shahr_I_Sokhta_BA2: 57.5
    Alalakh_MLBA_o: 27.5
    Oy_Dzhaylau_MLBA: 12.5
    Chokhopani_2700BP: 2.5




    sample: Kashmiri Pandit:Average
    distance: 1.9064
    Shahr_I_Sokhta_BA3: 30.5
    Alalakh_MLBA_o: 24
    Shahr_I_Sokhta_BA2: 22
    Oy_Dzhaylau_MLBA: 19
    Chokhopani_2700BP: 4.5

    sample: Punjabi Sikh India PanSikh27270
    distance: 1.5372
    Shahr_I_Sokhta_BA2: 50
    Oy_Dzhaylau_MLBA: 27
    Alalakh_MLBA_o: 23
    This is all in line with Lubotsky's paper.

    It seems therefore worthwhile to seriously consider another scenario.13 It seems attractive to assume that the southward movement of Indo-Aryans was simultaneous with the decline of the BMAC and was even triggered by it, since the profound changes in the economy of the BMAC would have forced the Indo-Aryan pastoralists to look for new markets. In the situation of an economic and political crisis, it is only to be expected that in their movement, the Indo-Aryans were joined by a sizable group of the BMAC people, who would bring their culture and the agricultural lifestyle with them.

    This scenario may account for the prolonged contacts of the Indo-Aryans and the BMAC people in the Swat valley and the Punjab and, consequently, for a large number of loanwords when the Indo-Aryans started to get settled and to learn agriculture. At the same time, it perfectly explains the fact that “intrusive BMAC material is subsequently found further to the south in Iran, Afghanistan and Pakistan.”14 As we know from major people movements of the past, they often were multiethnic, and a joint movement of Indo-Aryans and the BMAC people would not be surprising at all.

    It would be nice to hear from the geneticists whether this scenario is in line with the genetic evidence. In view of the many samples from the necropolis in Gonur, we will undoubtedly hear more about this issue in the future. Up till now, the linguistic scenarios have time and again found support in the analyses of ancient DNA. Will this also here be the case?
    Last edited by pegasus; 11-20-2020 at 01:25 AM.

  14. The Following 3 Users Say Thank You to pegasus For This Useful Post:

     agent_lime (11-20-2020),  discreetmaverick (11-20-2020),  Jatt1 (11-20-2020)

  15. #7779
    Registered Users
    Posts
    257
    Sex
    Location
    brooklyn
    Ethnicity
    kashmiri butt/pahari
    Nationality
    american/pakistani
    Y-DNA (P)
    J-CTS5368
    mtDNA (M)
    U2b

    here are my brothers coordinates can someone help me get a goodfit

    butt_scaled,0.068294,-0.022342,-0.112005,0.081396,-0.083708,0.042391,0.00376,0.011076,0.009204,-0.00893,-0.007632,-0.000749,-0.001933,-0.007844,0.007465,0.006497,-0.006128,0.00152,0.002765,-0.02051,0.000624,-0.014096,-0.001356,0.004699,-0.002036

    butt,0.006,-0.0022,-0.0297,0.0252,-0.0272,0.0152,0.0016,0.0048,0.0045,-0.0049,-0.0047,-0.0005,-0.0013,-0.0057,0.0055,0.0049,-0.0047,0.0012,0.0022,-0.0164,0.0005,-0.0114,-0.0011,0.0039,-0.0017

    Target: Butt_scaled
    Distance: 3.0284% / 0.03028450
    52.4 IRN_Shahr_I_Sokhta_BA2
    19.2 TJK_Sarazm_En
    16.8 RUS_Sintashta_MLBA
    4.0 IRN_Ganj_Dareh_N
    3.0 Levant_PPNB
    3.0 Nganassan
    1.4 Han
    0.2 Anatolia_Tepecik_Ciftlik_N

    mine for comparision;
    istance: 2.5497% / 0.02549668
    56.4 IRN_Shahr_I_Sokhta_BA2
    18.0 RUS_Sintashta_MLBA
    13.0 IRN_Ganj_Dareh_N
    4.0 KAZ_Botai
    3.0 TJK_Sarazm_En
    2.6 Han
    2.6 Levant_PPNB
    0.4 Anatolia_Barcin_N

  16. #7780
    Gold Class Member
    Posts
    4,348
    Location
    Shangri La

    Afghanistan Jammu and Kashmir United States of America Canada
    Quote Originally Posted by Ahmed Ali View Post
    Hahaha I agree re my grandad, the recurrent Med has me stumped. I recently returned from Pakistan and made a point of asking every other relative for their version of the family history. They all repeatedly said we're Rajputs with an 18th or 19th century Iranian ancestor, but not so sure the admixture supports that ...

    In relation to Mom/Khala, I had a chat with my Naani and she said the only known heritage is Potohari/AJK (Awan/Rajput)
    I looked at both your mom and Khala, they both need a more ANF enriched BMAC source , I had to use Sappali Tepe2 which often works well with Afghan Pashtuns, which infers a bit more Iran Chl ancestry. So there was definitely some further admixture beyond the traditional combinations used for populations here. I have looked at Potohari and Mirpuri results galore thanks to Amber and they are not like your mom's family.

    sample: Ahmedmom
    distance: 1.4976
    Shahr_I_Sokhta_BA2: 57
    Oy_Dzhaylau_MLBA: 21.5
    Sappali_Tepe2_BA: 18
    Chokhopani_2700BP: 3.5

    sample: AhmedKhaala
    distance: 1.8908
    Shahr_I_Sokhta_BA2: 55.5
    Oy_Dzhaylau_MLBA: 18.5
    Sappali_Tepe2_BA: 22.5
    Chokhopani_2700BP: 3.5

  17. The Following 3 Users Say Thank You to pegasus For This Useful Post:

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