Gedmatch calculators on Vahaduo

Quote:

Originally Posted by Lucas

Some "wise men" on Anthrogenica converted to G25 patients from Bari hospital from this study https://www.nature.com/articles/ejhg2014208
There is no single proof about their local ancestry only and G25 shows it clearly. So please don't post this bullshit coords and ask me to add them:)

This is wide spectrum of South and Central Italy simply, not Apulia only.

The average of all samples (except 4 that are probably Peruvian) is virtually identical to the old one, thus confirming that they are all Apulian. As far as I'm concerned they could be 100% local, it's normal in a group to have individuals plotting further south and others further north. Also, there are no Central Italians living in Apulia. On the contrary, thousands of Apulians are living in central Italy.

Italian_Apulia_old

Code:

Distance: 1.8664% / 0.01866449 45.4 TUR_Barcin_N 23.2 Yamnaya_RUS_Samara 17.2 Kura-Araxes_ARM_Kaps 11.0 Levant_PPNB 1.6 WHG 1.0 IRN_Ganj_Dareh_N 0.6 MAR_Taforalt

Italian_Apulia_new

Code:

Distance: 1.7427% / 0.01742725 46.0 TUR_Barcin_N 25.0 Yamnaya_RUS_Samara 14.4 Kura-Araxes_ARM_Kaps 10.8 Levant_PPNB 2.0 IRN_Ganj_Dareh_N 1.4 WHG 0.4 MAR_Taforalt

Quote:

Originally Posted by Kaazi

@Lucas,

Here are new Punjabi Hindu India, Punjabi Christian India and Punjabi Muslim India G25.
https://drive.google.com/file/d/1Xkq...ew?usp=sharing

Additional new Bengali Bangladesh (BEB) from 1000 Genomes are here.
https://drive.google.com/file/d/1TAM...ew?usp=sharing

Quote:

Originally Posted by Komintasavalta

You can run the code below here: https://rdrr.io/snippets/.

Code:

t=read.csv(header=F,row.names=1,text="Tajik_Ayni:TJ-0080,0.087644,0.014217,-0.036204,0.017765,-0.030467,0.01757,0.00517,0.000923,-0.014112,-0.008201,-0.007632,0.01109,-0.002676,-0.010735,0.009365,0.000398,-0.014342,-0.00114,-0.001131,-0.003126,-0.00025,-0.006554,-0.00419,-0.004579,0.003113 Tajik_Ayni:TJ-0086,0.087644,0.019295,-0.033187,0.015827,-0.042777,0.013666,0.011751,-0.002538,-0.02986,-0.016219,-0.012179,0.002698,-0.006541,-0.012248,0.012079,0.007823,0.000391,0.00076,-0.00176,-0.002501,-0.007986,-0.001855,-0.000616,0.004097,0.00491 Tajik_Ayni:TJ-0091,0.088782,0.019295,-0.032055,0.013243,-0.044316,0.014781,0.00517,0.000231,-0.027611,-0.016401,-0.007145,-0.008243,0.002676,-0.000963,0.014794,0.004773,-0.016559,-0.003674,-0.002765,-0.01063,-0.00025,0.001237,-0.001849,-0.006989,0.005628 Tajik_Ayni:TJ-0495,0.095611,-0.014217,-0.027907,0.018734,-0.044316,0.027889,0.011045,-0.007384,-0.024952,-0.022051,-0.010393,-0.000749,0.00446,-0.015827,0.012351,0.008618,0.00339,-0.008488,-0.001885,-0.012381,-0.009982,-0.00507,0.004314,0.001446,0.003592 Tajik_Ayni:TJ-0796,0.093335,0.004062,-0.037712,0.01615,-0.041238,0.016176,0.011045,0.000462,-0.026793,-0.017495,-0.019487,0.003147,-0.007136,-0.003716,0.013165,0.013126,-0.01004,0.001394,0.005531,-0.004627,-0.003868,-0.006554,0.011216,0.010965,0.005868 Tajik_Ayni:TJ-0798,0.086506,0.016248,-0.031301,0.020995,-0.044008,0.018407,0.011986,-0.000231,-0.020452,-0.029522,-0.001949,0.003897,0.010555,-0.015551,0.013843,0.011403,-0.001695,0.003167,0.005154,-0.008129,-0.005989,-0.00915,0.002958,-0.001205,0.003712 Tajik_Ayni:TJ-0807,0.091058,0.002031,-0.029038,0.022933,-0.030775,0.006972,0.00094,0.002538,-0.019839,-0.021322,-0.005196,0.002398,0.006838,-0.010046,0.013436,0.012596,-0.007171,0.00266,0.001257,-0.005002,-0.003619,0.002597,0.008751,0.008073,0.006706 Tajik_Ayni:TJ-0982,0.095611,0.007109,-0.010559,0.018088,-0.048317,0.011156,0.005875,0.002077,-0.031088,-0.018406,-0.012017,0.005095,-0.000892,-0.003303,0.009229,0.005569,-0.01682,-0.004941,-0.002514,-0.015632,-0.01435,-0.004081,0.003944,-0.000602,0.005628 Tajik_Ayni:TJ-0984,0.095611,0.003047,-0.018102,0.009044,-0.032314,0.014223,0.004935,-0.006461,-0.030883,-0.022962,-0.01153,0.001948,0.002379,-0.009771,0.011808,0.016971,-0.007171,-0.000633,0.002263,-0.012006,-0.004367,-0.002226,-0.001849,0.007471,0.004311 Tajik_Ayni:TJ-0986,0.099026,0.001016,-0.026776,0.02584,-0.042469,0.014502,0.00752,0.000692,-0.026179,-0.025149,-0.003573,0.003147,0.006095,-0.00234,0.000679,0.001989,-0.030249,-0.001647,0.004399,-0.014632,-0.009982,-0.009027,-0.001479,-0.011447,0.006347 Tajik_Ayni:TJ-1032,0.087644,0.015233,-0.029793,0.020026,-0.042777,0.010877,0.00752,-0.002077,-0.036814,-0.021139,-0.004872,-0.002248,-0.001338,-0.002202,0.007736,0.005171,-0.015255,-0.002914,0.002263,-0.004252,-0.010232,-0.004822,0.000739,-0.001084,0.010538 Tajik_Ayni:TJ-1041,0.08992,0.025388,-0.036581,0.020672,-0.045239,0.008088,-0.00141,0.003923,-0.026793,-0.022597,-0.009094,-0.003597,-0.006244,-0.008257,0.017101,0.008618,-0.002217,0.008488,-0.000126,-0.006378,-0.007986,0.000866,-0.002342,0.007591,0.000359 Tajik_Hisor:TJ-0484,0.088782,0.01828,-0.034318,0.020026,-0.040315,0.015339,0.00188,0.003231,-0.027202,-0.027335,-0.002111,0.004346,-0.00446,-0.009083,0.009636,0.008884,-0.002608,-0.003041,0.002263,-0.015632,-0.008859,0.001484,0.005053,-0.00253,0.001197 Tajik_Hisor:TJ-0486,0.088782,0.014217,-0.026021,0.017442,-0.046162,0.008925,0.001175,0,-0.024338,-0.022962,-0.011692,0.000599,0.001487,-0.010597,0.012893,0.020154,0.012386,0.00114,0.00088,0.003001,-0.00836,-0.000989,-0.005176,-0.00012,0.001916 Tajik_Hisor:TJ-0686,0.092197,-0.022342,-0.01697,0.020995,-0.042777,0.021196,0.009165,0.004615,-0.030474,-0.016583,-0.001137,0.004046,-0.005054,-0.00578,0.012758,0.009414,-0.002477,0.000127,0.001508,-0.011005,-0.006738,0.002226,0.004314,0.005302,-0.002155 Tajik_Hisor:TJ-0688,0.095611,0.01828,-0.020742,0.026486,-0.045239,0.019801,0.006345,-0.006923,-0.022907,-0.026606,-0.004384,-0.001049,0.001784,-0.010046,0.011265,0.018032,-0.001434,0.002027,0.00176,-0.011506,-0.008735,-0.001113,0.006286,0.004579,0.003592 Tajik_Kulob:TJ-0108,0.100164,0.051792,-0.021496,0.029716,-0.044008,0.031515,-0.000705,0.004154,-0.030474,-0.032074,-0.009256,0.001649,-0.000149,-0.011423,0.012758,0.020154,0.015255,-0.005321,-0.00176,-0.011756,-0.007112,-0.013107,0.003451,0.000964,-0.00479 Tajik_Kulob:TJ-0155,0.091058,0.003047,-0.030924,0.013889,-0.05201,0.01004,0.001175,0.003923,-0.03027,-0.026971,-0.010393,-0.005095,-0.006095,-0.004542,0.017372,0.00305,-0.000261,0.008108,0.004022,-0.009379,-0.000374,-0.00272,-0.005423,0,0.004071 Tajik_Kulob:TJ-0500,0.092197,0.014217,-0.049026,0.02907,-0.056318,0.014781,0.00611,-0.002538,-0.035587,-0.021139,-0.000325,-0.004946,-0.003865,-0.012386,0.008958,0.007955,-0.012256,0.000507,0.002765,-0.004377,-0.0141,0.005317,0.003697,0,0.004311 Tajik_Kulob:TJ-0517,0.100164,0.023357,-0.027153,0.028747,-0.041546,0.022032,-0.00141,-0.005769,-0.035383,-0.027518,-0.00682,-0.004646,-0.004311,-0.00867,0.018865,0.018695,-0.001043,0.000253,0.005531,-0.011255,-0.01697,0.000989,-0.000246,0.002771,-0.000239 Tajik_Kulob:TJ-0555,0.099026,0.030466,-0.037712,0.02261,-0.051702,0.01757,0.00611,0.000231,-0.037837,-0.026971,-0.011042,0.004946,0.002081,-0.004404,0.001086,-0.002519,-0.015255,0.00152,0.002514,-0.006753,-0.000125,-0.005812,-0.002095,0.005422,0.011137 Tajik_Kulob:TJ-0573,0.09675,0.017264,-0.038089,0.026163,-0.049548,0.0251,0.000705,-0.009461,-0.028633,-0.021868,-0.002923,-0.004496,0.001487,-0.008533,0.011265,0.013524,0.010952,0.001647,0.003645,-0.001626,-0.005615,0.001607,0.0053,0.010363,-0.008502 Tajik_Kulob:TJ-0574,0.093335,0.023357,-0.034318,0.026486,-0.04924,0.023985,0,0.001615,-0.026997,-0.018588,-0.007795,-0.004346,-0.008176,-0.006331,0.011401,0.02612,0.003129,-0.0019,-0.008296,-0.00988,0.000624,-0.000495,-0.003328,0.000241,0.007065") t2=aggregate(t,list(sub(":.*","",rownames(t))),mean) t3=data.frame(apply(t(t2[,-1]),1,sprintf,fmt="%.6f"),row.names=t2$Group.1) write.table(t3,"",quote=F,col.names=F,sep=",")

Wow, Great work. Is this okay or need to modify??

Scaled individuals

Code:

t=read.csv(header=F,row.names=1,text="Punjabi_Christian_India:7854,0.042115,-0.075149,-0.168196,0.115635,-0.072937,0.059961,-0.00094,0.010615,0.044586,0.026424,-0.003248,0.005695,0,0.006881,-0.004886,-0.002652,-0.007562,0.000507,0.00176,-0.005503,0.008485,0.000989,0.004683,-0.009399,0.000239 Punjabi_Christian_India:33021,0.036423,-0.108662,-0.180264,0.128878,-0.068013,0.06526,0.00047,0.009,0.060948,0.040821,-0.008282,-0.000749,0.00223,-0.004679,-0.01045,-0.015911,0.000522,-0.003421,-0.00352,0.002876,0.003868,0.005193,0.000986,0.003615,-0.008263 Punjabi_Hindu_India:8677,0.071709,-0.015233,-0.11917,0.091732,-0.072013,0.054384,0.001175,0.009692,0.012271,0.000547,-0.001949,0.003747,0.00223,-0.010184,0.011943,0.005171,-0.003129,-0.0019,0.007416,-0.007754,0.001123,-0.006059,0.00419,0.004217,-0.005269 Punjabi_Hindu_India:11201,0.050082,-0.059916,-0.162539,0.109821,-0.08063,0.052153,-0.000235,0.00923,0.033951,0.018224,-0.008607,-0.00015,-0.002379,-0.002064,-0.003393,0.009812,0.005346,0.00114,-0.000251,0.003627,0.003494,0.000618,-0.002835,-0.000964,0.001317 Punjabi_Hindu_India:19752,0.071709,-0.002031,-0.113513,0.084949,-0.072629,0.053547,-0.001645,0.006692,0.005727,-0.001822,-0.009256,0.004496,0.000595,-0.00289,0.003936,0.001061,-0.001434,0.006081,0.001885,-0.009254,-0.005366,-0.008903,0.008504,0.002048,-0.005748 Punjabi_Hindu_India:20668,0.079676,0.008124,-0.104462,0.07106,-0.060934,0.043507,0.00141,0.006461,-0.009817,-0.005467,0.001299,0.000749,-0.001041,0.001239,0.011808,0.006364,-0.001956,-0.0019,-0.001508,-0.010755,-0.008111,-0.010016,-0.00037,-0.000964,0.00012 Punjabi_Hindu_India:21049,0.068294,-0.001016,-0.110119,0.086564,-0.074168,0.049085,0,0.003923,-0.00225,-0.004374,-0.00682,-0.00045,0.005352,-0.006331,0.005565,0.019623,0.008475,0.005068,-0.00176,-0.01088,-0.003993,-0.013849,-0.001849,0.00012,-0.009101 Punjabi_Hindu_India:21055,0.067156,-0.004062,-0.111251,0.079458,-0.074475,0.049643,0.005875,0.007846,-0.001023,-0.004738,-0.00406,-0.002098,0.003865,0.000138,0.0019,0.004773,-0.007562,0.000127,0.000503,-0.015007,0.002246,-0.004451,0.00912,0.002289,0.004191 Punjabi_Hindu_India:21080,0.078538,-0.00914,-0.109365,0.086241,-0.067089,0.050758,0.00188,0.002538,-0.000614,0.002734,-0.006658,0.001349,-0.003568,-0.008945,0.012079,0.003182,-0.002868,0.002787,0.001885,-0.013757,-0.00287,0.002349,0.006039,-0.003012,0.000479 Punjabi_Hindu_India:22595,0.076261,-0.008124,-0.109742,0.082688,-0.066474,0.03765,0.003055,0.007154,0.002863,-0.007289,-0.004872,0.002548,-0.000149,-0.01156,0.009229,0.008751,0.006389,-0.00266,-0.006662,-0.012006,-0.002496,0.000124,0.004683,-0.003253,-0.008143 Punjabi_Hindu_India:22626,0.067156,-0.015233,-0.108988,0.080104,-0.065858,0.046296,0.001645,0.006461,0.007772,-0.01221,-0.007957,-0.002248,0.002825,-0.009634,0.009908,0.008221,-0.008475,-0.001014,0.000251,-0.005378,0.001872,0.002844,0.007395,0.001446,-0.001197 Punjabi_Hindu_India:22664,0.072847,-0.004062,-0.104462,0.072675,-0.069244,0.052431,-0.001175,0.004384,-0.008999,-0.004374,-0.012179,-0.001349,0.005352,-0.014863,0.010586,0.006497,-0.012647,0.001647,-0.000126,-0.008504,-0.007237,-0.006306,0.002465,-0.002771,-0.000718 Punjabi_Hindu_India:22730,0.067156,-0.006093,-0.113513,0.07429,-0.073552,0.052153,-0.00047,0.006923,0.009613,-0.001276,-0.007632,0.00015,-0.000743,-0.004266,0.009772,0.001591,-0.01682,0.003421,-0.002891,-0.010005,0.007237,0.002597,0.004807,-0.002892,0.008981 Punjabi_Hindu_India:22761,0.0774,-0.011171,-0.11653,0.089471,-0.065243,0.052989,-0.002585,0.006923,-0.004909,-0.004374,-0.008931,0.001948,0.001041,-0.009634,0.009772,0.005701,0.000261,-0.007348,-0.007039,-0.012881,-0.003369,0.003215,0.005176,0.000723,-0.007903 Punjabi_Hindu_India:23665,0.072847,-0.012186,-0.112005,0.072675,-0.069859,0.046575,0.004465,0.007846,0.002863,-0.000547,-0.008931,0.000899,-0.004608,-0.008808,0.004072,0.020419,0.008996,0.00266,-0.00088,-0.009129,-0.001497,-0.012736,0.000123,0.003735,0.002515 Punjabi_Hindu_India:23815,0.063741,-0.032497,-0.121056,0.091732,-0.066166,0.0502,-0.00047,-0.000692,0.015135,0.01057,-0.00406,0.001798,-0.001189,0.004679,0.00285,-0.010607,-0.012778,0.001267,-0.005279,-0.007504,-0.003119,0.004204,0.008504,0.002771,0.000838 Punjabi_Hindu_India:23816,0.076261,-0.017264,-0.116907,0.086887,-0.067705,0.047133,0.009165,0.006461,0.005522,0.003462,-0.015265,-0.000899,0.002973,-0.000826,0.008279,0.012198,-0.007823,-0.004434,0.005782,-0.005503,-0.000873,-0.00507,-0.004067,-0.001928,-0.001676 Punjabi_Hindu_India:23896,0.066017,-0.014217,-0.105217,0.08721,-0.07109,0.040439,0.00376,0.005769,-0.001023,-0.008201,0.000487,-0.003897,0.000743,-0.013212,0.007736,0.015646,0.012778,-0.010642,-0.003268,-0.005753,0.00025,-0.004328,-0.001602,0.001325,0.000958 Punjabi_Hindu_India:24211,0.069432,-0.011171,-0.103708,0.081719,-0.070167,0.046017,0.003995,0.007846,0.001227,-0.005649,-0.010393,-0.000899,-0.001338,-0.003028,0.001221,-0.003713,-0.00339,0.003041,0.008296,-0.007253,-0.000873,0.00136,0.000123,0.000843,-0.000359 Punjabi_Hindu_India:25529,0.069432,-0.014217,-0.098428,0.082365,-0.069859,0.051874,0.003525,-0.001615,0.005318,-0.005832,0.001624,0,-0.000743,-0.012799,0.012215,0.016309,0.006258,-0.003421,-0.003394,5e-04,-0.010482,-0.005317,0.007765,0.001928,-0.001317 Punjabi_Hindu_India:26216,0.068294,-0.012186,-0.117285,0.086564,-0.067397,0.047969,0.003995,0.010384,0.000205,-0.006378,-0.009256,0.001948,-0.000743,-0.009496,0.010993,0.018828,0.007953,-0.001014,0.00176,-0.000125,0.000374,-0.007296,0.003204,0.006386,-0.007784 Punjabi_Hindu_India:26448,0.073985,-0.016248,-0.114645,0.084949,-0.064012,0.05773,0.00188,0.006923,0.003886,-0.001276,-0.002598,-0.00045,-0.004608,-0.00867,0.010043,0.003845,-0.003912,-0.000127,0.001885,-0.007379,0.000998,-0.005441,0.001479,0.000602,-0.001197 Punjabi_Hindu_India:26564,0.066017,-0.008124,-0.105971,0.084949,-0.064935,0.050479,-0.00423,0.001154,-0.006954,-0.004374,-0.017213,-0.00015,-0.002973,-0.001101,0.008415,-0.006629,-0.007041,0.000507,0.000628,-0.009004,-0.005989,-0.010387,0.002465,-0.003615,0.001796 Punjabi_Hindu_India:26899,0.076261,-0.01828,-0.101445,0.091409,-0.069859,0.053268,-0.00282,0.006231,0.011044,-0.000547,-0.006333,0.004946,-0.000297,-0.003716,0.019544,0.001724,-0.003129,-0.005701,-0.000503,0.00075,0.004243,0.008408,0.000986,-0.004579,0.006466 Punjabi_Hindu_India:26918,0.072847,-0.014217,-0.107857,0.087856,-0.070475,0.047133,0.004465,0.009923,0.003477,-0.005103,-0.006496,-0.000749,0.002527,-0.006744,0.003664,0.005038,-0.002347,0.007348,0.002891,-0.010005,-0.000624,-0.006554,0.005176,0.000843,-0.004311 Punjabi_Hindu_India:26966,0.0774,-0.011171,-0.105217,0.077843,-0.063704,0.054105,0.00047,0.002077,0.002863,-0.003827,-0.008119,-0.001948,0.00223,-0.012524,0.007736,0.01485,0.009648,0.000507,-0.010433,-0.003627,0.00262,-0.004081,0.00419,0.003735,-0.001197 Punjabi_Hindu_India:26992,0.07057,-0.012186,-0.09692,0.079458,-0.073552,0.042949,-0.00141,0.001615,0.006954,-0.00656,0.000812,0.003597,-0.002527,-0.013762,0.005157,0.009546,0.007041,0.002407,-0.00176,-0.004877,-0.007112,-0.001607,0.003697,0.011929,0.000479 Punjabi_Hindu_India:27269,0.076261,-0.00914,-0.106725,0.081073,-0.072937,0.046017,0.002115,0.002538,0.00225,-0.003098,-0.005684,-0.001649,-0.002676,-0.006468,0.00475,0.006497,-0.00326,0.000127,0.000754,-0.006753,-0.005989,0.005441,0.002835,-0.001205,0.002754 Punjabi_Hindu_India:27578,0.078538,0.012186,-0.101445,0.075582,-0.070475,0.036535,0.003995,-0.002538,-0.006545,-0.01385,-0.007632,-0.004196,0.000446,-0.009083,0.008686,0.017634,-0.01017,-0.001394,-0.002765,-0.008504,-0.001747,-0.005317,0.005793,-0.003735,0.008981 Punjabi_Muslim_India:22413,0.063741,-0.016248,-0.12181,0.063308,-0.061242,0.04016,-0.003525,0.003692,0.022089,0.020046,-0.004547,0.004046,-0.003568,0.001651,-0.001493,0.00305,0.004433,0.002914,-0.002891,0.004127,-0.000374,-0.000371,0.001972,-0.000964,0.004311 Punjabi_Muslim_India:23026,0.066017,-0.011171,-0.113513,0.074936,-0.065858,0.049643,0,0.005538,-0.005113,0.001276,-0.007957,0.005095,-0.00446,-0.005643,0.011265,0.00769,0.002999,0.003041,0.005154,-0.011506,0.000125,-0.007914,0.005793,-0.001566,-0.00479") t2=aggregate(t,list(sub(":.*","",rownames(t))),mean) t3=data.frame(apply(t(t2[,-1]),1,sprintf,fmt="%.6f"),row.names=t2$Group.1) write.table(t3,"",quote=F,col.names=F,sep=",")

Average scaled

Code:

Punjabi_Christian_India,0.039269,-0.091906,-0.174230,0.122256,-0.070475,0.062610,-0.000235,0.009808,0.052767,0.033622,-0.005765,0.002473,0.001115,0.001101,-0.007668,-0.009282,-0.003520,-0.001457,-0.000880,-0.001313,0.006176,0.003091,0.002834,-0.002892,-0.004012 Punjabi_Hindu_India,0.071329,-0.011810,-0.111055,0.083753,-0.069426,0.048630,0.001549,0.005265,0.003363,-0.002801,-0.006544,0.000261,0.000022,-0.006835,0.007721,0.007494,-0.001318,-0.000127,-0.000540,-0.007286,-0.001751,-0.003206,0.003259,0.000593,-0.000594 Punjabi_Muslim_India,0.064879,-0.013709,-0.117662,0.069122,-0.063550,0.044901,-0.001762,0.004615,0.008488,0.010661,-0.006252,0.004570,-0.004014,-0.001996,0.004886,0.005370,0.003716,0.002978,0.001131,-0.003690,-0.000124,-0.004142,0.003883,-0.001265,-0.000240

Average unscaled

Code:

Punjabi_Christian_India,0.003450,-0.009050,-0.046200,0.037850,-0.022900,0.022450,-0.000100,0.004250,0.025800,0.018450,-0.003550,0.001650,0.000750,0.000800,-0.005650,-0.007000,-0.002700,-0.001150,-0.000700,-0.001050,0.004950,0.002500,0.002300,-0.002400,-0.003350 Punjabi_Hindu_India,0.006267,-0.001163,-0.029448,0.025930,-0.022559,0.017437,0.000659,0.002281,0.001644,-0.001537,-0.004030,0.000174,0.000015,-0.004967,0.005689,0.005652,-0.001011,-0.000100,-0.000430,-0.005826,-0.001404,-0.002593,0.002644,0.000493,-0.000496 Punjabi_Muslim_India,0.005700,-0.001350,-0.031200,0.021400,-0.020650,0.016100,-0.000750,0.002000,0.004150,0.005850,-0.003850,0.003050,-0.002700,-0.001450,0.003600,0.004050,0.002850,0.002350,0.000900,-0.002950,-0.000100,-0.003350,0.003150,-0.001050,-0.000200

Quote:

Originally Posted by Kaazi

Wow, Great work. Is this okay or need to modify??

Looks right. Another way is to run this shell command:

Code:

sed 's/:[^,]*//' g25individuals.csv|awk -F, '{n[$1]++;for(i=2;i<=NF;i++){a[$1,i]+=$i}}END{for(i in n){o=i;for(j=2;j<=NF;j++)o=o FS sprintf("%.6f",a[i,j]/n[i]);print o}}'

The Punjabi Hindu average is almost a quarter Andronovo (Aktogai)

Target: Punjabi_Hindu_India
Distance: 1.9099% / 0.01909899
71.4 IRN_Shahr_I_Sokhta_BA2
23.6 KAZ_Aktogai_MLBA
3.2 MNG_Ulaanzuukh_Slab_Grave
1.2 TUR_Kaman-Kalehoyuk_MLBA
0.6 Levant_Megiddo_MLBA

I wonder if that's also the case for Bobby Jindal, an Indian-American and a former governor of Louisiana (2008-2016), born in the U.S. to Punjabi Hindu parents.
https://bloximages.newyork1.vip.town...bab0.image.jpg

Quote:

Originally Posted by Komintasavalta

Looks right. Another way is to run this shell command:

Code:

sed 's/:[^,]*//' g25individuals.csv|awk -F, '{n[$1]++;for(i=2;i<=NF;i++){a[$1,i]+=$i}}END{for(i in n){o=i;for(j=2;j<=NF;j++)o=o FS sprintf("%.6f",a[i,j]/n[i]);print o}}'

Can you share the similar R code for a single group of samples to run on that easy site?? Sometime, we only need to average one group.

https://rdrr.io/snippets/.

Quote:

Originally Posted by Kaazi

Can you share the similar R code for a single group of samples to run on that easy site?? Sometime, we only need to average one group.

https://rdrr.io/snippets/.

That's easier:

Code:

t=read.csv(header=F,row.names=1,text="Moksha:MOE-014,0.133173,0.075149,0.068636,0.063954,0.021235,0.017012,0.00799,0.011999,-0.001227,-0.02442,-0.000325,-0.006744,0.019475,0.012937,-0.015472,-0.001193,0.008345,-0.008868,-0.00352,-0.012631,-0.009483,-0.002473,-0.002958,-0.003494,0.004431 Erzya:MOE-001,0.125205,0.080227,0.077687,0.060724,0.028313,0.021753,0.011751,0.014307,-0.005318,-0.028611,0.00406,-0.007793,0.023042,0.01734,-0.015336,0.001591,0.004042,0.00114,0.000628,-0.005753,-0.004243,-0.011871,-0.001849,-0.01205,0.003952") paste(sprintf("%.6f",colMeans(t)),collapse=",")

You can also download R here and then paste the code to the R console application: https://cran.r-project.org.

https://i.ibb.co/d6GBmcn/a.png

Or in a shell:

Code:

awk -F, '{for(i=2;i<=NF;i++)a[i]+=$i}END{for(i in a)printf"%.6f"(i==NF?"\n":FS),a[i]/NR}' g25individuals.csv

Quote:

Originally Posted by Leto

The Punjabi Hindu average is almost a quarter Andronovo (Aktogai)

Target: Punjabi_Hindu_India
Distance: 1.9099% / 0.01909899
71.4 IRN_Shahr_I_Sokhta_BA2
23.6 KAZ_Aktogai_MLBA
3.2 MNG_Ulaanzuukh_Slab_Grave
1.2 TUR_Kaman-Kalehoyuk_MLBA
0.6 Levant_Megiddo_MLBA

I wonder if that's also the case for Bobby Jindal, an Indian-American and a former governor of Louisiana (2008-2016), born in the U.S. to Punjabi Hindu parents.
https://bloximages.newyork1.vip.town...bab0.image.jpg

Guys on AG told that Bobby Jindal belongs to Baniya caste which looks like this one Hindu sample 11201.

Code:

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

Target: Punjabi_Hindu_India:11201
Distance: 2.5776% / 0.02577635
85.6 IRN_Shahr_I_Sokhta_BA3
8.8 RUS_Srubnaya_Alakul_MLBA
4.2 UZB_Dzharkutan1_BA
1.4 NPL_Chokhopani_2700BP

Target: Punjabi_Hindu_India
Distance: 1.3561% / 0.01356054
53.4 IRN_Shahr_I_Sokhta_BA3
23.0 RUS_Srubnaya_Alakul_MLBA
21.4 UZB_Dzharkutan1_BA
2.2 NPL_Chokhopani_2700BP

The Hindu average is the most representative of two Punjabi Hindu castes: Brahmins and Tarkhans. So, they are more Steppe than other Punjabis (non Jatt) and can score upto 29% Steppe like this sample.

Target: Punjabi_Hindu_India:26899
Distance: 2.6991% / 0.02699138
56.4 IRN_Shahr_I_Sokhta_BA3
28.8 RUS_Srubnaya_Alakul_MLBA
12.2 UZB_Dzharkutan1_BA
2.6 NPL_Chokhopani_2700BP

Can anyone here obtain G25 coordinates for some of the sample from Yunusbayev?
https://evolbio.ut.ee/caucasus/
I'm interested in the Tajiks (n=15), would like to compare them to those from Jeong.

Quote:

Originally Posted by Leto

Can anyone here obtain G25 coordinates for some of the sample from Yunusbayev?
https://evolbio.ut.ee/caucasus/
I'm interested in the Tajiks (n=15), would like to compare them to those from Jeong.

I did a SmartPCA run where I compared the samples from that paper against samples from the Human Origins dataset.

When the same sample was included in both sets, I omitted the sample from HO. The Nogai samples in that paper are the same as the samples labeled Nogai_Karachay_Cherkessia in HO, so I omitted all the samples from HO.

The Tajik samples from that paper look a bit more western than the Tajik samples in HO. Out of the samples labeled Tajik in HO, 23 are from Jeong 2019 and 8 are from Lazaridis 2014.

The Turkmen samples from that paper are a lot more western than the Turkmen samples in HO. No Turkmen sample was included in both sets.

https://i.ibb.co/7NqncFz/1.png

Quote:

Originally Posted by Komintasavalta

I did a SmartPCA run where I compared the samples from that paper against samples from the Human Origins dataset.

When the same sample was included in both sets, I omitted the sample from HO. The Nogai samples in that paper are the same as the samples labeled Nogai_Karachay_Cherkessia in HO, so I omitted all the samples from HO.

The Tajik samples from that paper look a bit more western than the Tajik samples in HO. Out of the samples labeled Tajik in HO, 23 are from Jeong 2019 and 8 are from Lazaridis 2014.

The Turkmen samples from that paper are a lot more western than the Turkmen samples in HO. No Turkmen sample was included in both sets.

[img]https://i.ibb.co/7NqncFz/1.png

Interesting. Unfortunately, there seems to be no info on the exact origin of those samples (unlike the Jeong study).