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Thread: New Simulated AASI G25 Coordinates (+ Updates)

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    Lightbulb New Simulated AASI G25 Coordinates (+ Updates)

    Ladies and Gents,

    I come bearing gifts.

    Several months ago, I created a set of simulated AASI coordinates based on Narasimhan et al.'s qpAdm proportions. These were NW_AASI (Gonur_BA1, SiSBA2, SiSBA3, SGPT and Dzharkutan2 from memory) and S_AASI (Irula, Pulliyar).

    Although these simulations radically improved the fits for practically all South Asians, our 'Censored' pointed out that Narasimhan et al. likely utilised both SiSBA2 and SiSBA3 for their "IVCp" lpop in the qpAdm models for modern groups (I had taken a post from somewhere in the forum at face value, where only SiSBA3 was stated as the source for that lpop, which I should've checked before creating the modern-based simulations).

    As promised several times over the past few weeks, I've corrected the S_AASI simulations based off of the Irula and Pulliyar (see below):

     

    Code:
    S_AASI_Sim (Pulliyar),-0.004810655,-0.212137156,-0.203515802,0.148876368,-0.031558109,0.053539852,-0.011510205,0.024112889,0.125139446,0.089041726,0.000713882,-0.003792554,-0.000836537,0.024717049,-0.049653257,-0.032409686,0.023256422,0.001963602,0.003977382,0.044586008,0.007150366,0.028673754,-0.011179757,0.016897181,-0.011729691
    S_AASI_Sim (Irula),-0.009525226,-0.239836772,-0.208951108,0.15454375,-0.020718969,0.056088654,-0.012872771,0.020823205,0.131311868,0.088651109,0.000283925,-0.001321365,0.001259261,0.018812454,-0.040159185,-0.037173939,0.01966007,-0.002000181,-0.002444666,0.043405215,0.009660745,0.021705468,-0.00888917,0.013704877,-0.009439234


    However... I've also added two new additions to S_AASI:

     

    Code:
    S_AASI_Sim (Hakkipikki),-0.017354205,-0.304894303,-0.268679085,0.181329575,-0.039351991,0.073271504,-0.022843875,0.037359828,0.187881353,0.126707043,-0.010024877,-0.004718921,0.008198494,0.036303194,-0.056184046,-0.072647447,-0.011352189,0.00825265,0.004209097,0.038425578,0.00661663,0.026988706,0.007609686,0.01678573,-0.009232161
    S_AASI_Sim (Mala),0.003619659,-0.232207345,-0.238759358,0.177803307,-0.049846413,0.074427442,-0.013528674,0.028614532,0.145189154,0.099856405,-0.009629229,-0.007501248,0.004294371,0.024294913,-0.044886968,-0.038569947,0.008810692,-0.004591174,-0.004761423,0.029743743,0.014289671,0.018672895,0.00018522,0.016546395,-0.013074696


    Briefly describing my procedure - I excluded all samples with p<0.01 (per the authors' own decision) and selected those within 0.01 > p < 0.10 (Irula were the exception only because I'd utilised them earlier). Realistically, however, there isn't any real limitation to me using qpAdm runs with higher p-values (arbitrarily, p<0.30 might be a reasonable cut-off). As such, I can create simulations as requested in this thread, if the target pop in question is present in both Davidski's G25 spreadsheet and Narasimhan's qpAdm output spreadsheet for modern groups. It would also be preferable if the target pops were tribal isolated groups.

    As an aside, I'd also created a set of modern-based NW_AASI simulations just now (based on Punjabi Jatts and Kashmiri Pandits). However, I've omitted them. Both in terms of model and values, modern NW S Asians seem to produce unusual simulations (f.ex. NW_AASI_Punjabi Jat generated a fit of ~44 with the ancients-based NW_AASI, whereas the S_AASI_Hakkipikki had an excellent ~1.7 fit with the old Irula-Pulliyar-based S_AASI simulation that's currently on Poi's Runner). That irregular output isn't due to human error (same procedure as all the other sims). Instead, I suspect this is confirmation that the three-pop Sintashta-IVCp-AASI qpAdm model in Narasimhan isn't suitable for NW S Asians.

    Finally, I'll be able to create an updated version of my "early AA" simulation once these ones are up on Poi's Runner.

    I've created a separate thread here for several reasons:
    1) The Global25 thread in this section has become much, much too bloated (multiple informative discussions are lost to time in there)
    2) I can provide everyone with updates of any further simulations I create
    3) You can directly advise me on any issues with the simulations that are within my control to correct
    4) You can request AASI simulations per the criteria above (p<0.3, present in Davidski's G25 sheet, present in Narasimhan's qpAdm moderns sheet, ideally a tribal population)

    I'll give Poi a ping shortly, so he's aware of the above, and so that the old S_AASI sims can be replaced (with the addition of the new two).

    Enjoy playing with these simulations.
    Last edited by DMXX; 07-14-2019 at 01:25 AM. Reason: typo

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    Quote Originally Posted by DMXX View Post
    Ladies and Gents,

    I come bearing gifts.

    Several months ago, I created a set of simulated AASI coordinates based on Narasimhan et al.'s qpAdm proportions. These were NW_AASI (Gonur_BA1, SiSBA2, SiSBA3, SGPT and Dzharkutan2 from memory) and S_AASI (Irula, Pulliyar).

    Although these simulations radically improved the fits for practically all South Asians, our 'Censored' pointed out that Narasimhan et al. likely utilised both SiSBA2 and SiSBA3 for their "IVCp" lpop in the qpAdm models for modern groups (I had taken a post from somewhere in the forum at face value, where only SiSBA3 was stated as the source for that lpop, which I should've checked before creating the modern-based simulations).

    As promised several times over the past few weeks, I've corrected the S_AASI simulations based off of the Irula and Pulliyar (see below):

     

    Code:
    S_AASI_Sim (Pulliyar),-0.004810655,-0.212137156,-0.203515802,0.148876368,-0.031558109,0.053539852,-0.011510205,0.024112889,0.125139446,0.089041726,0.000713882,-0.003792554,-0.000836537,0.024717049,-0.049653257,-0.032409686,0.023256422,0.001963602,0.003977382,0.044586008,0.007150366,0.028673754,-0.011179757,0.016897181,-0.011729691
    S_AASI_Sim (Irula),-0.009525226,-0.239836772,-0.208951108,0.15454375,-0.020718969,0.056088654,-0.012872771,0.020823205,0.131311868,0.088651109,0.000283925,-0.001321365,0.001259261,0.018812454,-0.040159185,-0.037173939,0.01966007,-0.002000181,-0.002444666,0.043405215,0.009660745,0.021705468,-0.00888917,0.013704877,-0.009439234


    However... I've also added two new additions to S_AASI:

     

    Code:
    S_AASI_Sim (Hakkipikki),-0.017354205,-0.304894303,-0.268679085,0.181329575,-0.039351991,0.073271504,-0.022843875,0.037359828,0.187881353,0.126707043,-0.010024877,-0.004718921,0.008198494,0.036303194,-0.056184046,-0.072647447,-0.011352189,0.00825265,0.004209097,0.038425578,0.00661663,0.026988706,0.007609686,0.01678573,-0.009232161
    S_AASI_Sim (Mala),0.003619659,-0.232207345,-0.238759358,0.177803307,-0.049846413,0.074427442,-0.013528674,0.028614532,0.145189154,0.099856405,-0.009629229,-0.007501248,0.004294371,0.024294913,-0.044886968,-0.038569947,0.008810692,-0.004591174,-0.004761423,0.029743743,0.014289671,0.018672895,0.00018522,0.016546395,-0.013074696


    Briefly describing my procedure - I excluded all samples with p<0.01 (per the authors' own decision) and selected those within 0.01 > p < 0.10 (Irula were the exception only because I'd utilised them earlier). Realistically, however, there isn't any real limitation to me using qpAdm runs with higher p-values (arbitrarily, p<0.30 might be a reasonable cut-off). As such, I can create simulations as requested in this thread, if the target pop in question is present in both Davidski's G25 spreadsheet and Narasimhan's qpAdm output spreadsheet for modern groups. It would also be preferable if the target pops were tribal isolated groups.

    As an aside, I'd also created a set of modern-based NW_AASI simulations just now (based on Punjabi Jatts and Kashmiri Pandits). However, I've omitted them. Both in terms of model and values, modern NW S Asians seem to produce unusual simulations (f.ex. NW_AASI_Punjabi Jat generated a fit of ~44 with the ancients-based NW_AASI, whereas the S_AASI_Hakkipikki had an excellent ~1.7 fit with the old Irula-Pulliyar-based S_AASI simulation that's currently on Poi's Runner). That irregular output isn't due to human error (same procedure as all the other sims). Instead, I suspect this is confirmation that the three-pop Sintashta-IVCp-AASI qpAdm model in Narasimhan isn't suitable for NW S Asians.

    Finally, I'll be able to create an updated version of my "early AA" simulation once these ones are up on Poi's Runner.

    I've created a separate thread here for several reasons:
    1) The Global25 thread in this section has become much, much too bloated (multiple informative discussions are lost to time in there)
    2) I can provide everyone with updates of any further simulations I create
    3) You can directly advise me on any issues with the simulations that are within my control to correct
    4) You can request AASI simulations per the criteria above (p<0.3, present in Davidski's G25 sheet, present in Narasimhan's qpAdm moderns sheet, ideally a tribal population)

    I'll give Poi a ping shortly, so he's aware of the above, and so that the old S_AASI sims can be replaced (with the addition of the new two).

    Enjoy playing with these simulations.
    How are the fits with the new AASi sims you've created?

    Should the AASI NW and AASI_south both be used in creating models on nmonte?

  4. The Following User Says Thank You to 26284729292 For This Useful Post:

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    Thanks! Will play around with these, are the co-ords pasted here scaled or unscaled?

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    Quote Originally Posted by 26284729292 View Post
    How are the fits with the new AASi sims you've created?
    See below (cross-validation with Paniya - Default settings):

    Code:
    Sample	Details	Fit	Map	Paniya
    1	Custom:S_AASI_SimHakkipikki		20.9575 	Open Map	100
    2	Custom:S_AASI_SimIrula		8.9173 	Open Map	100
    3	Custom:S_AASI_SimMala		11.3234 	Open Map	100
    4	Custom:S_AASI_SimPulliyar		6.989 	Open Map	100
    In a word, they're heterogeneous. Which one should expect.

    Should the AASI NW and AASI_south both be used in creating models on nmonte?
    I hold a pragmatic view on this, after much tinkering in the past. Whichever yields the best fit. Probably best to include both as a default. If one registers <1% score-wise, probably worth dropping that one.

    Quote Originally Posted by scobar View Post
    Thanks! Will play around with these, are the co-ords pasted here scaled or unscaled?
    You're welcome, and these are scaled.

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    Quote Originally Posted by 26284729292 View Post
    How are the fits with the new AASi sims you've created?

    Should the AASI NW and AASI_south both be used in creating models on nmonte?

    Here's a model I tried (scaled co-ords, nMonte3, 1000 cycles, batch=500, default penalty) -

    Code:
    ,PC1,PC2,PC3,PC4,PC5,PC6,PC7,PC8,PC9,PC10,PC11,PC12,PC13,PC14,PC15,PC16,PC17,PC18,PC19,PC20,PC21,PC22,PC23,PC24,PC25
    Anatolia_Barcin_N,0.1175998,0.180118,0.0035312,-0.101158,0.0510443,-0.0483875,-0.0043582,-0.0069334,0.0362287,0.0807473,0.0079718,0.0118803,-0.0234545,0.0004691,-0.0419807,-0.0101913,0.0233091,0.0019866,0.0136954,-0.0097489,-0.0142249,0.0057723,-0.0041232,-0.0031658,-0.0043437
    TJK_Sarazm_En,0.084798,0.059916,-0.1057825,0.044251,-0.1227925,0.038208,0.0062275,-0.0101535,-0.0811955,-0.0646025,0.002842,0.009067,-0.008994,-0.014313,0.0313515,0.0177005,-0.0182535,-0.002344,0.001257,-0.0243865,-0.005802,-0.00983,0.0069015,-0.0172915,0.009221
    NPL_Chokhopani_2700BP,0.012521,-0.410274,-0.011691,-0.031331,0.017542,0.011435,0.00658,0.011999,0.010022,0.021139,-0.081194,-0.006444,0.010109,-0.004679,-0.011401,0,0.011213,-0.001267,-0.009302,0.009379,0.004991,0.029306,0.004314,0.003615,0.031734
    RUS_Sintashta_MLBA,0.125433,0.116075,0.0576869,0.0787689,0.0113968,0.0284096,0.0056636,0.0042383,-0.0176231,-0.028034,-0.0025766,0.0013488,-0.0032061,-0.0215196,0.0225975,0.0126579,-0.004885,0.0004476,-0.0002933,-0.0006753,-0.0061142,0.0023618,0.0026497,0.007033,-0.0041074
    RUS_West_Siberia_N,0.1058555,-0.060424,0.0974855,0.199292,-0.082631,0.045738,-0.0419495,-0.0471905,-0.0334395,-0.09212,0.0194865,-0.0106405,0.0273535,-0.071908,0.0259225,0.01664,-0.01356,-0.0065875,-0.000377,0.0032515,-0.0301345,0.0109435,0.024095,0.0074705,-0.010119
    Onge,-0.0225251,-0.2445288,-0.1324289,0.095965,0.0299327,-0.0047557,-0.0076438,0.0075786,0.0548233,0.0244388,0.023495,0.0032182,-0.0040608,0.0084746,-0.0126933,-0.0111446,0.010918,-0.0016203,-0.0059807,0.0288295,-0.0037107,0.0096905,-0.0128242,-0.0011225,0.0043426
    Jarawa,-0.0219821,-0.2430289,-0.1324164,0.0986968,0.0323713,-0.0045841,-0.01012,0.0065044,0.0546974,0.0238044,0.0228054,0.0027349,-0.0041532,0.0103562,-0.0108067,-0.0114441,0.0094529,-0.0019082,-0.0062221,0.0286778,-0.0046401,0.0111366,-0.0123402,0.0022668,0.0049844
    IRN_Shahr_I_Sokhta_BA1,0.073985,0.062455,-0.138215,0.021641,-0.109559,0.0283075,0.0062275,-0.0019615,-0.061562,-0.0346245,-0.001786,-0.00045,-0.005203,-0.0035785,0.019883,0.0332135,-0.0034555,0.003991,-0.000503,-0.0274505,0.0048045,-0.0150855,-0.003821,-0.0218705,0.0194595
    IRN_Shahr_I_Sokhta_BA2,0.05805,0.015233,-0.152734,0.07106,-0.116945,0.054384,0.011516,0.006231,-0.029042,-0.02606,0.000325,0.003897,0.001041,-0.013074,0.020222,0.013657,-0.012126,0.00038,0.000126,-0.02001,0.001123,-0.018795,-0.002342,-0.017111,0.002155
    IRN_Shahr_I_Sokhta_BA3,0.033009,-0.081242,-0.180641,0.120157,-0.097557,0.065539,0.0047,0.009461,0.035996,0.026789,-0.002273,0.003747,-0.005649,0.007982,0.003529,0.003182,0.008736,0.001647,0.000126,-0.002001,0.001373,-0.008161,0.000246,-0.001928,-0.008023
    RUS_Srubnaya_Alakul_MLBA,0.1283672,0.1055022,0.0565263,0.0834058,0.0063259,0.0330021,0.0055096,0.0044358,-0.0177708,-0.0348072,-0.0021293,-0.0015654,-0.0023124,-0.0199401,0.0242338,0.0099441,-0.0082141,0.000549,0,0.0013479,-0.001234,0.0026103,0.0037386,0.004686,0.0004791
    RUS_Srubnaya_MLBA,0.1262297,0.1155672,0.0576241,0.0816867,0.0060934,0.0318772,0.0041595,0.0053536,-0.0194297,-0.0315086,-0.0010716,0.0019184,-0.0039841,-0.016666,0.0225973,0.0074514,-0.0133775,0.0016977,0.0007544,0.0012631,-0.0022709,0.0051686,-0.0006285,0.0047355,-0.0005988
    RUS_Steppe_Maykop,0.108132,0.0187872,0.0362977,0.1403442,-0.0751678,0.045041,-0.0202108,-0.030345,-0.056602,-0.0813685,0.0159548,-0.0038965,0.0097002,-0.0416652,0.0296208,0.0196562,-0.0051502,-0.0040858,-0.0053422,0.006722,-0.0177187,0.0061825,0.0135575,0.0056935,-0.0054188
    S_AASI_Sim_Pulliyar,-0.004810655,-0.212137156,-0.203515802,0.148876368,-0.031558109,0.053539852,-0.011510205,0.024112889,0.125139446,0.089041726,0.000713882,-0.003792554,-0.000836537,0.024717049,-0.049653257,-0.032409686,0.023256422,0.001963602,0.003977382,0.044586008,0.007150366,0.028673754,-0.011179757,0.016897181,-0.011729691
    S_AASI_Sim_Irula,-0.009525226,-0.239836772,-0.208951108,0.15454375,-0.020718969,0.056088654,-0.012872771,0.020823205,0.131311868,0.088651109,0.000283925,-0.001321365,0.001259261,0.018812454,-0.040159185,-0.037173939,0.01966007,-0.002000181,-0.002444666,0.043405215,0.009660745,0.021705468,-0.00888917,0.013704877,-0.009439234
    S_AASI_Sim_Hakkipikki,-0.017354205,-0.304894303,-0.268679085,0.181329575,-0.039351991,0.073271504,-0.022843875,0.037359828,0.187881353,0.126707043,-0.010024877,-0.004718921,0.008198494,0.036303194,-0.056184046,-0.072647447,-0.011352189,0.00825265,0.004209097,0.038425578,0.00661663,0.026988706,0.007609686,0.01678573,-0.009232161
    S_AASI_Sim_Mala,0.003619659,-0.232207345,-0.238759358,0.177803307,-0.049846413,0.074427442,-0.013528674,0.028614532,0.145189154,0.099856405,-0.009629229,-0.007501248,0.004294371,0.024294913,-0.044886968,-0.038569947,0.008810692,-0.004591174,-0.004761423,0.029743743,0.014289671,0.018672895,0.00018522,0.016546395,-0.013074696
    Khatri avg

     
    Model minus sims

    "distance%=2.2728" - Khatri

    IRN_Shahr_I_Sokhta_BA2,49.2
    IRN_Shahr_I_Sokhta_BA3,15.6
    IRN_Shahr_I_Sokhta_BA1,7.6
    Anatolia_Barcin_N,4.4
    RUS_Sintashta_MLBA,4
    RUS_Steppe_Maykop,3.8
    RUS_Srubnaya_MLBA,3
    RUS_Srubnaya_Alakul_MLBA,2.8
    RUS_West_Siberia_N,2.8
    Jarawa,2.6
    NPL_Chokhopani_2700BP,2.2
    Onge,2

    Model w/ sims

    "distance%=1.64" - Khatri

    IRN_Shahr_I_Sokhta_BA2,34.4
    IRN_Shahr_I_Sokhta_BA1,17.2
    IRN_Shahr_I_Sokhta_BA3,9.2
    RUS_Sintashta_MLBA,5.4
    TJK_Sarazm_En,4.6
    RUS_Steppe_Maykop,4.4
    Anatolia_Barcin_N,3.8
    RUS_Srubnaya_MLBA,3.8
    RUS_Srubnaya_Alakul_MLBA,3.4
    S_AASI_Sim_Pulliyar,2.8
    S_AASI_Sim_Hakkipikki,2.6
    S_AASI_Sim_Mala,2.6
    RUS_West_Siberia_N,2.2
    S_AASI_Sim_Irula,1.6
    NPL_Chokhopani_2700BP,1.2
    Jarawa,0.6
    Onge,0.2


    Mine

     
    Model minus sims

    "distance%=3.5516" - Scobar_scaled

    IRN_Shahr_I_Sokhta_BA3,59.4
    IRN_Shahr_I_Sokhta_BA2,12.2
    IRN_Shahr_I_Sokhta_BA1,6
    Onge,5.8
    Anatolia_Barcin_N,4.2
    Jarawa,3.8
    TJK_Sarazm_En,2.4
    RUS_Sintashta_MLBA,1.4
    RUS_Srubnaya_Alakul_MLBA,1.4
    RUS_Srubnaya_MLBA,1.4
    NPL_Chokhopani_2700BP,1.2
    RUS_Steppe_Maykop,0.8

    Model w/ sims

    "distance%=2.8742" - Scobar_scaled

    IRN_Shahr_I_Sokhta_BA3,43.8
    IRN_Shahr_I_Sokhta_BA1,12.6
    IRN_Shahr_I_Sokhta_BA2,11.4
    S_AASI_Sim_Irula,5.2
    S_AASI_Sim_Pulliyar,5
    Anatolia_Barcin_N,4
    RUS_Sintashta_MLBA,2.8
    RUS_Srubnaya_MLBA,2.6
    TJK_Sarazm_En,2.6
    RUS_Srubnaya_Alakul_MLBA,2.4
    S_AASI_Sim_Mala,2.4
    Jarawa,2.2
    Onge,2.2
    NPL_Chokhopani_2700BP,0.6
    S_AASI_Sim_Hakkipikki,0.2


    26284729292

     
    With sims

    "distance%=2.4981" - 2xx_scaled

    IRN_Shahr_I_Sokhta_BA3,56.2
    IRN_Shahr_I_Sokhta_BA1,8.4
    IRN_Shahr_I_Sokhta_BA2,7.8
    RUS_Sintashta_MLBA,3
    S_AASI_Sim_Mala,3
    S_AASI_Sim_Pulliyar,2.8
    RUS_Srubnaya_MLBA,2.6
    RUS_Steppe_Maykop,2.4
    Anatolia_Barcin_N,2.2
    RUS_Srubnaya_Alakul_MLBA,2.2
    S_AASI_Sim_Irula,2.2
    TJK_Sarazm_En,2.2
    S_AASI_Sim_Hakkipikki,1.6
    RUS_West_Siberia_N,1.4
    NPL_Chokhopani_2700BP,1
    Onge,0.6
    Jarawa,0.4

    Without sims

    "distance%=3.0729" - 2xx_scaled

    IRN_Shahr_I_Sokhta_BA3,68.6
    IRN_Shahr_I_Sokhta_BA2,8.4
    IRN_Shahr_I_Sokhta_BA1,3.8
    Onge,3.2
    RUS_Srubnaya_MLBA,3
    Jarawa,2.8
    TJK_Sarazm_En,2.4
    RUS_Srubnaya_Alakul_MLBA,2
    Anatolia_Barcin_N,1.4
    RUS_Sintashta_MLBA,1.4
    RUS_Steppe_Maykop,1.4
    RUS_West_Siberia_N,1
    NPL_Chokhopani_2700BP,0.6

  10. The Following 6 Users Say Thank You to scobar For This Useful Post:

     26284729292 (07-14-2019),  bmoney (07-15-2019),  client (07-15-2019),  DMXX (07-14-2019),  Kulin (07-14-2019),  Reza (07-14-2019)

  11. #6
    Bronze Class Member
    Posts
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    Location
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    Siberian Tatars Tajikistan
    Excellent work DMXX, Iím eager to try these out once I get home. Hopefully they will be on the web runner by then. I also support the idea of creating a new thread for this topic.

  12. The Following 3 Users Say Thank You to Censored For This Useful Post:

     DMXX (07-14-2019),  FrostAssassin0701 (07-14-2019),  poi (07-14-2019)

  13. #7
    Moderator
    Posts
    771
    Sex
    Location
    Sarai-Batu
    Ethnicity
    Bengali
    Nationality
    Canadian
    mtDNA (M)
    A11-a*
    Y-DNA (P)
    J2b2a

    Canada Bangladesh Jammu and Kashmir India Pakistan Sri Lanka
    Using Scobar's model

    "sample": "Test1:Kulin_scaled",
    "fit": 2.2284,
    "S_AASI_Sim_Hakkipikki": 13.33,
    "IRN_Shahr_I_Sokhta_BA1": 11.67,
    "IRN_Shahr_I_Sokhta_BA3": 11.67,
    "IRN_Shahr_I_Sokhta_BA2": 10.83,
    "S_AASI_Sim_Mala": 8.33,
    "Jarawa": 5.83,
    "NPL_Chokhopani_2700BP": 5.83,
    "RUS_Sintashta_MLBA": 5,
    "S_AASI_Sim_Pulliyar": 5,
    "TJK_Sarazm_En": 5,
    "RUS_West_Siberia_N": 4.17,
    "Onge": 3.33,
    "RUS_Srubnaya_MLBA": 3.33,
    "RUS_Steppe_Maykop": 2.5,
    "Anatolia_Barcin_N": 1.67,
    "RUS_Srubnaya_Alakul_MLBA": 1.67,
    "S_AASI_Sim_Irula": 0.83,
    "closestDistances": [
    "IRN_Shahr_I_Sokhta_BA3:undefined: 9.019311",
    "IRN_Shahr_I_Sokhta_BA2:undefined: 17.440668",
    "Jarawa:undefined: 18.663759",
    "Onge:undefined: 18.698754",
    "S_AASI_Sim_Pulliyar:undefined: 20.759908",
    "S_AASI_Sim_Irula:undefined: 22.729493",
    "IRN_Shahr_I_Sokhta_BA1:undefined: 23.735395",
    "S_AASI_Sim_Mala:undefined: 24.892355",
    "TJK_Sarazm_En:undefined: 25.260561",
    "RUS_Steppe_Maykop:undefined: 27.562554",
    "RUS_Srubnaya_Alakul_MLBA:undefined: 31.186332",
    "RUS_Srubnaya_MLBA:undefined: 31.834192",
    "RUS_West_Siberia_N:undefined: 31.949629",
    "RUS_Sintashta_MLBA:undefined: 31.950675",
    "S_AASI_Sim_Hakkipikki:undefined: 34.394002",
    "NPL_Chokhopani_2700BP:undefined: 36.992224",
    "Anatolia_Barcin_N:undefined: 41.207358"

  14. The Following 5 Users Say Thank You to Kulin For This Useful Post:

     bmoney (07-15-2019),  client (07-15-2019),  DMXX (07-14-2019),  Reza (07-14-2019),  Sapporo (07-14-2019)

  15. #8
    Registered Users
    Posts
    918
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    Brahmin (mixed)
    Nationality
    Indian
    mtDNA (M)
    M-30
    Y-DNA (P)
    R-1A (Z-93)

    Quote Originally Posted by Kulin View Post
    Using Scobar's model

    "sample": "Test1:Kulin_scaled",
    "fit": 2.2284,
    "S_AASI_Sim_Hakkipikki": 13.33,
    "IRN_Shahr_I_Sokhta_BA1": 11.67,
    "IRN_Shahr_I_Sokhta_BA3": 11.67,
    "IRN_Shahr_I_Sokhta_BA2": 10.83,
    "S_AASI_Sim_Mala": 8.33,
    "Jarawa": 5.83,
    "NPL_Chokhopani_2700BP": 5.83,
    "RUS_Sintashta_MLBA": 5,
    "S_AASI_Sim_Pulliyar": 5,
    "TJK_Sarazm_En": 5,
    "RUS_West_Siberia_N": 4.17,
    "Onge": 3.33,
    "RUS_Srubnaya_MLBA": 3.33,
    "RUS_Steppe_Maykop": 2.5,
    "Anatolia_Barcin_N": 1.67,
    "RUS_Srubnaya_Alakul_MLBA": 1.67,
    "S_AASI_Sim_Irula": 0.83,
    "closestDistances": [
    "IRN_Shahr_I_Sokhta_BA3:undefined: 9.019311",
    "IRN_Shahr_I_Sokhta_BA2:undefined: 17.440668",
    "Jarawa:undefined: 18.663759",
    "Onge:undefined: 18.698754",
    "S_AASI_Sim_Pulliyar:undefined: 20.759908",
    "S_AASI_Sim_Irula:undefined: 22.729493",
    "IRN_Shahr_I_Sokhta_BA1:undefined: 23.735395",
    "S_AASI_Sim_Mala:undefined: 24.892355",
    "TJK_Sarazm_En:undefined: 25.260561",
    "RUS_Steppe_Maykop:undefined: 27.562554",
    "RUS_Srubnaya_Alakul_MLBA:undefined: 31.186332",
    "RUS_Srubnaya_MLBA:undefined: 31.834192",
    "RUS_West_Siberia_N:undefined: 31.949629",
    "RUS_Sintashta_MLBA:undefined: 31.950675",
    "S_AASI_Sim_Hakkipikki:undefined: 34.394002",
    "NPL_Chokhopani_2700BP:undefined: 36.992224",
    "Anatolia_Barcin_N:undefined: 41.207358"
    Can you run my V3? I'll PM you coords.

  16. The Following User Says Thank You to 26284729292 For This Useful Post:

     Kulin (07-14-2019)

  17. #9
    Administrator
    Posts
    3,686
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    mtDNA (M)
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    Y-DNA (P)
    R2a*-M124 (L295-)

    England
    Here's the moderns-based NW_AASI simulations, in case you guys were interested (please note my caution about them above):

    Code:
    NW_AASI_Sim (Punjabi_Jat),0.094567092,-0.01210031,-0.103329923,0.049574001,-0.059647466,0.051445724,-0.018535549,0.004702444,0.000167165,-0.01354295,-0.019100802,-0.020440779,0.000163871,0.002306857,-0.007801069,0.020404698,-0.008912441,0.003030766,0.01923494,-0.036334361,-0.009910173,-0.013342789,0.001910154,0.006290832,0.021856536
    NW_AASI_Sim (Kashmiri_Pandit),0.111962634,-0.125030211,-0.059634609,-0.009824166,-0.062937043,0.016282401,0.023509874,0.010023709,-0.048014129,-0.003337695,-0.049857444,-0.028270902,0.027452093,0.05153618,-0.04525803,0.014228418,0.027475604,0.001844817,0.02520256,-0.016049014,-0.04660462,-0.000136231,-0.001075507,0.033386909,0.024903592
    I've also added the averages for both NW_AASI modern and S_AASI below:

    Code:
    NW_AASI_Sim_modern_Av,0.103264863,-0.068565261,-0.081482266,0.019874918,-0.061292255,0.033864063,0.002487163,0.007363077,-0.023923482,-0.008440323,-0.034479123,-0.024355841,0.013807982,0.026921519,-0.02652955,0.017316558,0.009281582,0.002437792,0.02221875,-0.026191688,-0.028257397,-0.00673951,0.000417324,0.019838871,0.023380064
    S_AASI_Sim Av,-0.007017607,-0.247268894,-0.229976338,0.16563825,-0.035368871,0.064331863,-0.015188881,0.027727614,0.147380455,0.101064071,-0.004664075,-0.004333522,0.003228897,0.026031903,-0.047720864,-0.045200255,0.010093749,0.000906224,0.000245098,0.039040136,0.009429353,0.024010206,-0.003068505,0.015983546,-0.010868946
    While you guys are waiting for Poi to add these to his Runner, I'd recommend just sticking with the S_AASI average simulation for the time being. See whether that provides better fits than those individual samples.
    Last edited by DMXX; 07-14-2019 at 03:47 AM. Reason: average added

  18. The Following 3 Users Say Thank You to DMXX For This Useful Post:

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  19. #10
    What is the difference between NAASI and SAASI exactly?

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