G25 G25 Central, Eastern and South Eastern Europe Iron Age Calculator

Duarte · Feb 9, 2022

Regio X said:
Morocco EN is almost entirely Iberomaurusian-like, but not the Morocco LN.
Canary itself would have Iberomaurusian.

These models may be "sensible". When I try to isolate the Iberomaurusian component using other old components such EHG, WHG, AHG, CHG, Natufian, Iran Meso, Shum Laka 8000 ybp, Kenya Pastoral Neo etc., the Iberomaurusian % in Portuguese (modern average) becomes 3.4.
Moroccan South gets 33%; Moroccan North, 28.4%. If Portuguese do have about 11% of Moorish on average, as that paper suggests, and if the Moorish were similar to modern Moroccan, then the 3.4% seem coherent.

Hello Regio.
In fact, there are dozens of modeling possibilities, depending on the objective to be achieved. In that sense, I take the same model I used earlier (Jovialis’ G25 ancient and, as target, myself and the modern Iberian G25 samples rich in Iberomaurisians).
This time, following your line of reasoning, I add to the G25 original sources of Jovialis only the samples labeled in ancient G25 as Levant_Natufians, WHG, CHG, IRN_N, TUR_N, KEN_BC, CMR_Shun_Laka.

Mainland and me

(*) PS: Showing all numerical columns, not visible in picture above

Canaries

At least in these guys the Iberomaurisian remains big. Outliers like me, who am a mixed guy, I imagine.

Regio X · Feb 9, 2022

Hello Duarte.
This model seems overfitted. If the goal is isolating the Iberomaurusian, specifically to test its contribution to modern Iberians, I believe using ancient pops relatively far removed to one another would be enough. The model through which I get those 3.4% is based mainly on Epipaleolithic pops, as Iberomaurusians were.
Anyway, if you want to explore your model a bit more, you could try adding the WHG, Anatolian Neo (or Pinarbasi) and even EHG, to test possible excesses.

Duarte · Feb 10, 2022

Regio X said:
Hello Duarte.
This model seems overfitted. If the goal is isolating the Iberomaurusian, specifically to test its contribution to modern Iberians, I believe using ancient pops relatively far removed to one another would be enough. The model through which I get those 3.4% is based mainly on Epipaleolithic pops, as Iberomaurusians were.
Anyway, if you want to explore your model a bit more, you could try adding the WHG, Anatolian Neo (or Pinarbasi) and even EHG, to test possible excesses.

Hi Regio
What do you think this model?

Code:

MAR_Taforalt:TAF009___BC_12271___Coverage_24.61%,-0.162767,0.07718,-0.024513,-0.079135,0.009848,-0.047969,-0.052877,0.020538,0.13294,0.002005,0.025333,-0.026676,0.057978,-0.052985,0.072882,-0.034076,0.002347,-0.05625,-0.130475,0.04152,-0.026204,-0.120314,0.067909,-0.016508,0.012334
MAR_Taforalt:TAF010___BC_12699___Coverage_72.10%,-0.193499,0.083273,-0.03017,-0.088502,0.034776,-0.055499,-0.076378,0.019384,0.163619,0.008565,0.02111,-0.030573,0.07879,-0.046104,0.077496,-0.046141,-0.00665,-0.069805,-0.144176,0.036518,-0.042924,-0.129217,0.07629,-0.015303,0.018322
MAR_Taforalt:TAF011___BC_12500___Coverage_88.13%,-0.194638,0.085304,-0.021873,-0.088825,0.026774,-0.059961,-0.072148,0.019845,0.161165,0.002551,0.016564,-0.035818,0.080574,-0.051196,0.066367,-0.037523,0.012126,-0.071199,-0.14493,0.035767,-0.041427,-0.12662,0.068279,-0.011447,0.018441
MAR_Taforalt:TAF013___BC_12550___Coverage_84.93%,-0.196914,0.082258,-0.026398,-0.088502,0.032314,-0.057173,-0.074733,0.017768,0.156665,0.002369,0.02111,-0.036717,0.077898,-0.052159,0.072746,-0.038584,0.000913,-0.069552,-0.141285,0.039894,-0.035687,-0.125384,0.075428,-0.011206,0.020477
MAR_Taforalt:TAF014___BC_12550___Coverage_83.86%,-0.201467,0.079211,-0.018479,-0.083011,0.034468,-0.055499,-0.076848,0.014538,0.162596,0.002005,0.020461,-0.029374,0.078344,-0.054223,0.066503,-0.025192,0.017602,-0.063724,-0.151215,0.04127,-0.042176,-0.126126,0.077153,-0.014339,0.012693
Levant_Natufian:I0861___BC_10750___Coverage_9.91%,0.01935,0.135065,-0.039221,-0.135984,0.026774,-0.076137,-0.019036,-0.024691,0.100626,-0.008018,0.02858,-0.019633,0.067343,0.001651,0.022801,0.02612,-0.0103,0.006714,-0.018101,0.041395,-0.004118,-0.003215,-0.014297,-0.011206,0.011975
Levant_Natufian_contam:I1072___BC_10750___Coverage_38.21%,0.021626,0.151314,-0.036204,-0.141475,0.034776,-0.082831,-0.032196,-0.010384,0.128032,0.012028,0.037837,-0.024878,0.085629,0.002615,0.007872,-0.008088,-0.020601,-0.008742,-0.026019,0.040269,0.007112,0.003462,0.007025,0.002289,0.000599
FRA_Nouvelle_Aquitaine_Meso:PER503___BC_7100___Coverage_24.13%,0.122929,0.112724,0.190446,0.186695,0.164646,0.060798,0.030786,0.043383,0.093263,0.014761,-0.023546,-0.018434,0.020961,0.001514,0.059717,0.064969,0.002608,0.017483,-0.001257,0.068783,0.127775,0.008285,-0.057187,-0.182194,0.020836
FRA_Nouvelle_Aquitaine_Meso:PER3023___BC_7100___Coverage_12.97%,0.118376,0.107646,0.194594,0.197031,0.164954,0.044901,0.010575,0.023076,0.092036,0.010752,-0.009581,-0.030723,0.013825,0.001101,0.056731,0.06245,0.00013,-0.006968,-0.007793,0.058653,0.115047,0.019166,-0.043137,-0.184122,0.026465
FRA_Nouvelle_Aquitaine_Meso:PER3123___BC_7100___Coverage_11.13%,0.125205,0.109677,0.181018,0.196708,0.168955,0.059683,0.019506,0.038998,0.096331,0.022415,0.004222,-0.025927,0.005946,0.004679,0.05551,0.064969,-0.009518,0.007095,-0.008296,0.062905,0.120288,0.005935,-0.062363,-0.181953,0.030416
Baltic_LTU_Meso:Spiginas4___BC_6326___Coverage_58.26%,0.134311,0.108662,0.181395,0.186695,0.136949,0.061077,0.010575,0.034383,0.071174,-0.007472,-0.013153,-0.016935,0.029286,0.000138,0.039495,0.060063,0.005215,0.001267,-0.00352,0.048523,0.072248,0.013231,-0.036235,-0.136525,0.012574
Baltic_LVA_HG:I4432___BC_6008___Coverage_63.57%,0.135449,0.100537,0.188937,0.21092,0.110174,0.063587,0.011986,0.023768,0.055221,-0.016219,-0.004709,-0.021281,0.029137,-0.008395,0.039223,0.046141,0.002086,0.007348,-0.005154,0.04252,0.058771,0.008037,-0.029949,-0.119053,0.013771
Baltic_LVA_HG:I4434___BC_5491___Coverage_63.47%,0.122929,0.099522,0.185543,0.208013,0.104327,0.055499,0.013866,0.025153,0.055835,-0.02278,-0.003085,-0.018434,0.032111,-0.006055,0.035152,0.046937,0.005346,0.000253,-0.006285,0.046522,0.060269,0.019043,-0.015283,-0.111582,0.008622
Baltic_LVA_HG:I4438___BC_5298___Coverage_64.52%,0.12862,0.103584,0.175738,0.197354,0.104019,0.052989,0.007285,0.02123,0.044177,-0.029887,-0.000325,-0.019183,0.026759,-0.007432,0.034609,0.052108,-0.000261,0.007981,-0.006285,0.045522,0.059395,0.013973,-0.02884,-0.102424,0.012095
Baltic_LVA_HG:I4439___BC_5696___Coverage_64.59%,0.130897,0.102568,0.182149,0.197354,0.116945,0.055499,0.00799,0.020768,0.061562,-0.019681,-0.016401,-0.014387,0.030921,-0.003303,0.038816,0.05529,0.008605,0.004307,-0.01257,0.040644,0.072622,0.01422,-0.030689,-0.123391,0.003712
Baltic_LVA_HG:I4440___BC_5124___Coverage_62.67%,0.124067,0.109677,0.171213,0.191863,0.103096,0.0502,0.009635,0.021691,0.054403,-0.029704,-0.006171,-0.010341,0.028097,0.005918,0.02823,0.041633,-0.007302,0.009755,-0.004274,0.043271,0.058023,0.013107,-0.025266,-0.10857,0.007065
Baltic_LVA_HG:I4441___BC_4768___Coverage_63.63%,0.135449,0.093429,0.171967,0.188633,0.101557,0.049921,0.0047,0.020307,0.042336,-0.030433,-0.006008,-0.018284,0.026313,-0.00812,0.030673,0.039644,0.008605,-0.0019,-0.011061,0.042145,0.052782,0.022505,-0.024403,-0.105316,0.009939
Baltic_LVA_HG:I4550___BC_6539___Coverage_66.16%,0.130897,0.1046,0.184789,0.200907,0.125562,0.059125,0.009165,0.03046,0.069334,-0.020957,-0.005359,-0.017534,0.023786,-0.002064,0.045738,0.061124,0.005346,0.006334,-0.006159,0.044771,0.072497,0.00643,-0.031551,-0.130862,0.012813
Baltic_LVA_HG:I4551___BC_5720___Coverage_60.35%,0.132035,0.09546,0.178378,0.195739,0.09294,0.057173,0.002115,0.019384,0.050108,-0.03098,-0.003085,-0.014537,0.027651,-0.020781,0.040988,0.044948,0.003651,0.007981,-0.002011,0.043521,0.057523,0.00643,-0.02465,-0.099171,0.003952
Baltic_LVA_HG:I4552___BC_5419___Coverage_64.70%,0.135449,0.098506,0.185543,0.196385,0.10802,0.056894,0.0094,0.020768,0.048063,-0.027153,-0.004709,-0.020682,0.028989,-0.003716,0.03298,0.049854,0.008996,0.006461,0.000377,0.045272,0.063263,0.01422,-0.029826,-0.10869,0.009939
Baltic_LVA_HG:I4553___BC_5420___Coverage_43.85%,0.129758,0.100537,0.181395,0.199615,0.114483,0.051316,0.015981,0.021691,0.05379,-0.02278,-0.008444,-0.02218,0.028692,0,0.042345,0.057146,0.003651,-0.000253,0.001885,0.04102,0.061267,0.01793,-0.026375,-0.113992,0.007903
Baltic_LVA_HG:I4595___BC_5687___Coverage_68.17%,0.126344,0.093429,0.179887,0.187341,0.109559,0.055499,0.002585,0.023076,0.054608,-0.01549,-0.005521,-0.02218,0.027948,0.000963,0.033116,0.05224,0.011604,-0.001774,-0.007416,0.04202,0.063887,0.007048,-0.02354,-0.113631,0.015208
Baltic_LVA_HG:I4596___BC_6020___Coverage_70.35%,0.12862,0.098506,0.18592,0.191863,0.118791,0.058288,0.0094,0.019615,0.058085,-0.028064,0.004222,-0.020082,0.028394,-0.011285,0.031623,0.049456,0.005215,0.00076,-0.003897,0.042896,0.06788,0.008408,-0.033277,-0.116281,0.006347
Baltic_LVA_HG:I4626___BC_5727___Coverage_32.46%,0.121791,0.114755,0.184412,0.200584,0.110482,0.063308,0.002585,0.023537,0.05604,-0.017495,-0.007632,-0.017085,0.020664,0.010046,0.042345,0.036727,-0.008475,0.007728,-0.017221,0.039894,0.068754,0.027327,-0.035495,-0.136766,0.015208
Baltic_LVA_HG:I4628___BC_5083___Coverage_61.08%,0.127482,0.098506,0.177247,0.203491,0.108328,0.051595,0.013161,0.011538,0.048677,-0.032985,-0.002598,-0.020232,0.028543,0.002064,0.029858,0.040175,-0.008736,0.009628,-0.005656,0.04152,0.062265,0.00643,-0.016145,-0.107847,0.016765
Baltic_LVA_HG:I4630___BC_7268___Coverage_65.15%,0.124067,0.08632,0.167819,0.198,0.07386,0.057173,0.00423,0.005307,0.036405,-0.042461,0.004384,-0.009142,0.033597,-0.024634,0.02253,0.041766,0.00013,0.00114,-0.006913,0.036518,0.039805,0.013973,-0.016022,-0.075312,-0.002874
Baltic_LVA_HG:I4632___BC_6366___Coverage_68.26%,0.134311,0.106631,0.183281,0.187664,0.100634,0.059404,0.009635,0.023076,0.050517,-0.031162,-0.009419,-0.024278,0.028692,-0.009221,0.040988,0.053036,0.010691,-0.00038,-0.002137,0.039144,0.062639,0.009769,-0.029456,-0.103991,0.013053
WHG:I1875___BC_7106___Coverage_31.85%,0.130897,0.120848,0.191577,0.194447,0.159107,0.048248,0.015746,0.040152,0.087332,0.007472,-0.016076,-0.015436,0.017839,-0.003303,0.047909,0.047069,0.007302,0.018497,-0.003268,0.057027,0.087471,0.00915,-0.048436,-0.143153,0.01449
WHG:Rochedane___BC_11077___Coverage_19.09%,0.118376,0.111708,0.178001,0.184111,0.150182,0.044623,0.010575,0.034383,0.090809,0.028064,-0.014615,-0.016186,0.013974,-0.002752,0.058767,0.069344,0.002738,0.014189,-0.015335,0.054151,0.101446,0.013231,-0.050778,-0.178579,0.019519
GEO_CHG:KK1___BC_7728___Coverage_99.87%,0.091058,0.102568,-0.083344,-0.00323,-0.08617,0.020638,0.024911,-0.001846,-0.128236,-0.074717,-0.006333,0.023979,-0.054856,0.004404,0.026601,-0.03275,0.02386,-0.013429,-0.022249,0.034767,0.033815,-0.007048,0.006532,-0.025787,-0.002036
DEU_Meso_BDB:BDB001.merged___BC_6650___Coverage_69.84%,0.125205,0.112724,0.194217,0.202199,0.156645,0.051037,0.023266,0.039229,0.090809,0.003462,-0.016564,-0.017085,0.026759,0.006193,0.052252,0.062582,-0.00678,0.013429,0.000251,0.05315,0.099949,0.013725,-0.046095,-0.160746,0.023231
DEU_Meso_TGM:TGM009.A0101___BC_3258___Coverage_58.72%,0.134311,0.141159,0.155751,0.122095,0.127101,0.032909,0.012691,0.015692,0.066266,0.021504,-0.011205,-0.011839,0.010406,-0.002064,0.024973,0.041766,0.011735,0.011275,-0.000754,0.035892,0.077488,0.015209,-0.032661,-0.104955,0.012214
England_Mesolithic:I6767___BC_8330___Coverage_95.47%,0.126344,0.110693,0.202891,0.197031,0.157876,0.055778,0.010575,0.03346,0.086514,0.016583,-0.017863,-0.01139,0.014866,-0.001651,0.061481,0.065499,0.002477,0.009882,-0.005531,0.06353,0.116295,0.019661,-0.055954,-0.179664,0.019399
Iberia_ElMiron:ElMiron___BC_16825___Coverage_54.49%,0.0774,0.044683,0.105217,0.129201,0.11079,0.031236,0.00188,0.006231,0.088559,0.02442,-0.005359,-0.002847,0.008622,-0.013487,0.037459,0.041633,0.002217,0.006968,-0.015209,0.045772,0.063638,0.007914,-0.036481,-0.129054,0.013053
Iberia_Northwest_Meso:Canes___BC_5139___Coverage_69.93%,0.122929,0.101553,0.164802,0.175067,0.130178,0.053547,0.020211,0.031153,0.079355,0.00164,-0.009094,-0.015286,0.023786,-0.000413,0.049266,0.040307,-0.015125,0.009248,-0.012193,0.049399,0.087471,0.007296,-0.04289,-0.144358,0.015687
Iberia_Northwest_Meso:Chan___BC_7159___Coverage_90.02%,0.092197,0.055854,0.124073,0.153426,0.12587,0.042112,0.00705,0.028153,0.091831,0.02934,-0.006658,-0.007943,0.010704,-0.017065,0.055645,0.048528,0.001565,0.008235,-0.016215,0.061154,0.095581,0.01558,-0.050532,-0.16412,0.021555
Iberia_Southeast_Meso:I10899___BC_22500___Coverage_40.02%,0.097888,0.059916,0.114268,0.14632,0.112944,0.030399,0.005405,0.017307,0.089172,0.024784,-0.00747,-0.011989,0.008771,-0.010872,0.037866,0.045213,0.002217,0.012289,-0.00817,0.052025,0.084725,0.013725,-0.045725,-0.147129,0.019399
ITA_Grotta_Continenza_Meso:RMPR7___BC_8756___Coverage_95.96%,0.126344,0.113739,0.200628,0.200907,0.174186,0.059961,0.015276,0.036922,0.106352,0.02606,-0.019974,-0.013638,0.012042,-0.014313,0.07166,0.069742,-0.002086,0.013302,-0.008422,0.066407,0.119289,0.009521,-0.059405,-0.195811,0.025866
ITA_Grotta_Continenza_Meso:RMPR11___BC_9918___Coverage_64.13%,0.114961,0.109677,0.197988,0.204783,0.168955,0.062472,0.018096,0.040614,0.105739,0.030798,-0.018837,-0.012739,0.015907,-0.009634,0.073832,0.06961,0.007562,0.014696,-0.01433,0.057403,0.113924,0.009645,-0.064459,-0.194485,0.022154
ITA_Grotta_Continenza_Meso:RMPR15___BC_7136___Coverage_95.73%,0.126344,0.112724,0.204022,0.208982,0.175417,0.063029,0.014806,0.046152,0.113715,0.024602,-0.019162,-0.016635,0.020664,-0.002064,0.06691,0.067753,-0.004824,0.008108,-0.007039,0.067532,0.120787,0.014838,-0.058789,-0.201233,0.017962
IRL_Meso:KGH6___BC_4708___Coverage_62.28%,0.129758,0.120848,0.201005,0.200584,0.165262,0.062193,0.018801,0.040844,0.088968,0.010023,-0.011367,-0.014087,0.015907,0.00289,0.056324,0.056748,-0.011343,0.009628,-0.002388,0.0529,0.109806,0.015828,-0.044985,-0.174482,0.02407
IRL_Meso:SRA62___BC_4051___Coverage_99.89%,0.125205,0.113739,0.195726,0.201876,0.167108,0.06526,0.018096,0.034614,0.099603,0.010023,-0.011692,-0.013338,0.021258,0.000688,0.061753,0.059533,-0.005867,0.015583,-0.00993,0.060279,0.111054,0.006925,-0.056201,-0.174362,0.020238
IRN_Belt_Cave_Meso_low_res:I2312_all_d___BC_10000___Coverage_2.64%,0.046667,0.055854,-0.107102,0.029393,-0.100942,0.058288,0.000235,-0.009,-0.064834,-0.059956,0.033614,0.02203,-0.010258,-0.000275,0.057817,0.044285,-0.029597,0.008361,-0.001885,-0.008004,0.013227,-0.016569,-0.023787,-0.025666,0.056761
IRN_HotuIIIb_Meso:I1293___BC_8850___Coverage_3.38%,0.052359,0.064994,-0.124073,0.043282,-0.112636,0.019522,0.003995,-0.007615,-0.071992,-0.053031,0.009906,0.008842,0.001933,-0.017616,0.030673,0.055157,0.004824,-0.010769,0.010559,-0.029389,0.001123,-0.013231,-0.00493,-0.022413,0.025507
LUX_Loschbour:I0001___BC_6075___Coverage_40.06%,0.133173,0.106631,0.20176,0.192186,0.164338,0.055778,0.00611,0.036922,0.096535,0.02278,-0.020786,-0.016186,0.024975,-0.007432,0.065824,0.063643,0.008084,0.006714,-0.013324,0.065281,0.120038,0.019166,-0.059405,-0.175687,0.022992
NOR_Meso:Hum1___BC_7414___Coverage_35.23%,0.125205,0.071087,0.152357,0.196062,0.044316,0.06526,-0.004935,0.003231,0.014112,-0.054853,0.010393,-0.015436,0.020812,-0.028626,0.015065,0.03328,-0.002217,0.006461,-0.015335,0.022136,0.018717,0.019784,-0.005423,-0.056514,0.006227
NOR_Meso:Hum2___BC_7414___Coverage_94.70%,0.126344,0.082258,0.158014,0.185726,0.050779,0.061077,0,0.004384,0.024543,-0.048657,0.009581,-0.017834,0.027948,-0.035231,0.027958,0.041633,-0.001695,0.002914,-0.004399,0.03089,0.026079,0.014715,-0.008997,-0.059044,0.000359
SWE_Meso:ble008___BC_7875___Coverage_4.54%,0.12862,0.083273,0.164425,0.204783,0.066474,0.056615,-0.015276,0.010153,0.032519,-0.050662,0.012342,-0.020831,0.031665,-0.023121,0.036644,0.045478,-0.001043,-0.001394,-0.003017,0.029639,0.037184,0.009027,-0.019103,-0.079047,0.001916
SWE_Meso:SBj___BC_6821___Coverage_29.17%,0.135449,0.093429,0.167442,0.184757,0.080323,0.059125,-0.00329,0.011769,0.037428,-0.053942,-0.001299,-0.02218,0.029881,-0.007432,0.040716,0.030761,-0.010561,0.004941,-0.003017,0.046772,0.049413,0.016569,-0.01368,-0.096038,0.002754
SWE_Meso:SF9___BC_7194___Coverage_70.63%,0.129758,0.092413,0.166687,0.183465,0.089555,0.060798,0.006345,0.014307,0.044995,-0.035172,-0.003085,-0.016785,0.024678,-0.019405,0.031759,0.049058,0.006258,-0.003167,-0.008422,0.041145,0.053031,0.022134,-0.023664,-0.099171,0.006706
SWE_Meso:SF12___BC_6945___Coverage_96.85%,0.134311,0.09546,0.166687,0.193155,0.0834,0.061635,0.006815,0.011076,0.036201,-0.041185,-0.001137,-0.017385,0.031516,-0.020231,0.033387,0.040175,-0.001173,0.002534,-0.007039,0.047523,0.037309,0.012489,-0.025389,-0.092784,0.00455
SWE_Motala_HG:I0012___BC_5648___Coverage_67.21%,0.135449,0.084289,0.173476,0.195739,0.092017,0.056894,-0.00752,0.009692,0.050722,-0.038999,-0.000325,-0.018434,0.032557,-0.016928,0.02823,0.052771,0.004303,0,-0.006913,0.035017,0.062016,0.016693,-0.021445,-0.104714,0.001437
SWE_Motala_HG:I0013___BC_5772___Coverage_27.48%,0.127482,0.088351,0.155751,0.168607,0.089247,0.049921,-0.00329,0.001615,0.040291,-0.030616,0.00747,-0.015736,0.023488,-0.026699,0.034202,0.04402,0.00326,0.002407,-0.009427,0.048023,0.043922,0.010634,-0.019966,-0.097002,0.010897
SWE_Motala_HG:I0014___BC_5736___Coverage_64.22%,0.137726,0.083273,0.167064,0.190571,0.078476,0.056336,-0.004935,0.006,0.036201,-0.038816,0.002273,-0.015436,0.031962,-0.009909,0.034066,0.046672,0.007953,0.006081,-0.005279,0.043771,0.04517,0.011871,-0.026991,-0.098689,0.006107
SWE_Motala_HG:I0015___BC_5760___Coverage_51.34%,0.137726,0.092413,0.160653,0.193155,0.085554,0.058567,0.003995,0.01223,0.025565,-0.041368,-0.002923,-0.019782,0.031219,-0.018304,0.032437,0.051047,0.006128,0.000253,-0.000754,0.040269,0.049163,0.021763,-0.022185,-0.095315,0.008502
SWE_Motala_HG:I0011___BC_5614___Coverage_53.97%,0.124067,0.099522,0.168573,0.188633,0.087093,0.054105,0,0.013153,0.035383,-0.04483,0.001786,-0.024129,0.035976,-0.014863,0.028908,0.051975,0.007171,0.003421,-0.009302,0.03164,0.053531,0.011129,-0.019843,-0.092784,0.008263
TUR_Barcin_N:I0707___BC_6146___Coverage_85.98%,0.122929,0.184826,0.001886,-0.110144,0.054779,-0.048527,0.00141,-0.011769,0.036201,0.08474,0.011205,0.016335,-0.021704,0.002615,-0.038409,-0.014187,0.022817,0.00114,0.012947,-0.002751,-0.011979,0.009645,-0.008627,0.001566,-0.001676
TUR_Barcin_N:I0708___BC_6151___Coverage_83.49%,0.119514,0.173656,-0.003017,-0.101745,0.042469,-0.046854,-0.00094,-0.012692,0.021066,0.074717,0.009419,0.009142,-0.017691,0.000963,-0.041938,-0.007955,0.024121,0.000633,0.015209,-0.013882,-0.022336,0.008903,-0.012448,-0.012652,-0.007305
TUR_Barcin_N:I0709___BC_6135___Coverage_84.11%,0.119514,0.19092,0.008674,-0.108206,0.050163,-0.044065,-0.00282,-0.003923,0.038655,0.088202,0.006983,0.012289,-0.023488,0.001789,-0.042345,-0.023999,0.002347,-0.003674,0.011941,-0.019759,-0.006239,0.012242,-0.000616,-0.00723,-0.002994
TUR_Barcin_N:I0723___BC_5920___Coverage_36.12%,0.118376,0.178733,0.009805,-0.103037,0.057241,-0.05773,0.003525,0.000462,0.041518,0.080548,0.001624,0.004946,-0.027056,-0.005643,-0.043702,-0.006762,0.03729,0.00152,0.017975,-0.009254,-0.015473,0.002968,0.006779,-0.00012,-0.006227
TUR_Barcin_N:I0724___BC_6000___Coverage_4.80%,0.117238,0.168578,0.018856,-0.10013,0.052933,-0.047969,-0.00094,-0.004384,0.031088,0.075446,0.008931,0.01139,-0.017691,-0.003303,-0.045059,0.001989,0.041853,0.012922,0.020363,-0.009755,-0.018717,0.004699,-0.007518,-0.001928,-0.008023
TUR_Barcin_N:I0726___BC_6000___Coverage_19.84%,0.120652,0.180764,0.00264,-0.104653,0.053548,-0.054663,-0.005875,-0.002308,0.035383,0.088749,0.009743,0.015586,-0.027651,0.006881,-0.040716,-0.037655,-0.001825,0.002914,0.0225,-0.015382,-0.013351,0.007666,-0.004683,0.00253,0.006945
TUR_Barcin_N:I0727___BC_6000___Coverage_3.88%,0.114961,0.185842,0.004525,-0.103683,0.036314,-0.053547,-0.00141,-0.008077,0.031088,0.077633,0.005846,0.01109,-0.031813,0.00055,-0.056052,-0.010607,0.022817,0.009122,0.032807,-0.015007,-0.017968,0.005441,-0.016022,-0.007953,0.008023
TUR_Barcin_N:I0736___BC_6350___Coverage_69.43%,0.119514,0.183811,0.006788,-0.091732,0.049855,-0.049921,-0.0047,-0.006,0.04295,0.077815,0.012829,0.013338,-0.020961,-0.011423,-0.04058,0.005701,0.033248,-0.007475,0.007793,-0.007003,-0.016097,0.006306,-0.005916,-0.000964,-0.007544
TUR_Barcin_N:I0744___BC_6320___Coverage_75.46%,0.119514,0.186857,0.009428,-0.107883,0.058472,-0.052989,-0.00987,-0.01223,0.03027,0.082371,0.010393,0.01139,-0.031813,0.003441,-0.048045,-0.011668,0.022426,0.000633,0.005279,-0.007253,-0.012852,-0.000124,-0.004683,0.002289,0.001796
TUR_Barcin_N:I0745___BC_6293___Coverage_84.87%,0.118376,0.178733,-0.002263,-0.098838,0.049548,-0.046575,-0.010105,-0.002538,0.036814,0.075628,0.010068,0.014237,-0.017542,0.00812,-0.035966,-0.020949,0.005346,0.006334,0.020489,-0.014382,-0.017095,0.008037,0.001356,-0.009278,-0.004191
TUR_Barcin_N:I0746___BC_5978___Coverage_85.47%,0.120652,0.180764,0.011691,-0.093024,0.048317,-0.043507,-0.012691,-0.010615,0.034565,0.078726,0.010393,0.009591,-0.023786,0.006606,-0.048316,-0.027844,0.005607,0.004054,0.012947,-0.017383,-0.013102,0.011005,-0.006532,-0.005543,-0.002036
TUR_Barcin_N:I1096___BC_6350___Coverage_64.66%,0.120652,0.184826,0.008297,-0.101745,0.051702,-0.044344,-0.005405,-0.003692,0.039473,0.0831,0.010718,0.017385,-0.02438,0.006331,-0.043702,-0.0179,0.025946,-0.00076,0.012821,-0.005878,-0.015722,0.00507,-0.005793,0.007832,-0.016406
TUR_Barcin_N:I1097___BC_6332___Coverage_64.39%,0.120652,0.18178,-0.001886,-0.106591,0.054472,-0.048527,-0.00611,-0.007615,0.038246,0.084922,0.008769,0.014687,-0.022894,0.000413,-0.048859,-0.006629,0.021383,0.003421,0.013952,-0.015257,-0.013975,0.005441,-0.011462,-0.009158,-0.002515
TUR_Barcin_N:I1098___BC_6332___Coverage_67.81%,0.114961,0.179749,-0.004148,-0.092701,0.040931,-0.045459,-0.001175,-0.010846,0.030883,0.068703,0.009743,0.007044,-0.019623,0.000688,-0.044381,-0.001326,0.032987,0.003294,0.006788,-0.001501,-0.01148,0.007914,0.007025,-0.002771,-0.00958
TUR_Barcin_N:I1099___BC_6350___Coverage_46.49%,0.111547,0.19092,0.001508,-0.0969,0.055395,-0.04518,0.003525,-0.010615,0.037223,0.077997,0.006171,0.01124,-0.020515,0.00289,-0.039902,-0.016309,0.021644,0.00266,0.013324,-0.007504,-0.003868,0.002844,0.002588,-0.003012,-0.006347
TUR_Barcin_N:I1100___BC_6350___Coverage_25.57%,0.112685,0.17264,-0.001131,-0.084949,0.049855,-0.054384,-0.00705,-0.002308,0.042132,0.088749,-0.003573,0.008692,-0.02557,-0.006881,-0.040173,-0.00769,0.031553,-0.00266,0.007793,-0.01063,-0.023708,-0.00136,0.003574,-0.003253,-0.001557
TUR_Barcin_N:I1101___BC_6350___Coverage_56.53%,0.114961,0.179749,0.006411,-0.100776,0.054779,-0.043786,-0.00094,-0.000462,0.042541,0.078544,0.005684,0.008692,-0.023042,0.007432,-0.034744,-0.010209,0.01682,0.003927,0.018729,-0.006378,-0.020713,0.004575,-0.000616,-0.003133,-0.010179
TUR_Barcin_N:I1102___BC_6350___Coverage_35.46%,0.106994,0.170609,0.00528,-0.097546,0.059703,-0.045459,-0.003995,-0.007846,0.030474,0.08474,0.005196,0.010041,-0.029732,-0.006193,-0.031759,0.001856,0.029597,0.002154,0.013073,-0.008754,-0.009109,0.010634,-0.003821,-0.003856,-0.002634
TUR_Barcin_N:I1103___BC_6350___Coverage_51.86%,0.112685,0.169593,-0.006411,-0.10013,0.044008,-0.046854,-0.00705,-0.005538,0.039269,0.075992,0.011367,0.013638,-0.02215,-0.005505,-0.036644,-0.01127,0.019427,-0.002027,0.010559,-0.008004,-0.016346,0.005564,-0.011216,-0.009278,-0.006945
TUR_Barcin_N:I1580___BC_6255___Coverage_78.21%,0.127482,0.182795,-0.003017,-0.103037,0.052317,-0.04769,-0.008695,-0.012692,0.040496,0.076904,0.007307,0.014987,-0.020961,-0.003716,-0.043159,0.001724,0.035986,-0.001647,0.006788,-0.009254,-0.010357,-0.001731,0.000246,-0.000482,-0.010298
TUR_Barcin_N:I1581___BC_6302___Coverage_71.36%,0.113823,0.175687,0.001131,-0.110467,0.057241,-0.045459,-0.003995,-0.008077,0.040905,0.084558,0.004222,0.013488,-0.02215,-0.000826,-0.04248,0.003978,0.040549,0.004687,0.005405,-0.005628,-0.010731,0.00643,-0.013557,0.003494,-0.000958
TUR_Barcin_N:I1583___BC_6323___Coverage_99.28%,0.119514,0.180764,0.00264,-0.10756,0.048932,-0.051037,-0.010575,-0.008769,0.035792,0.087656,0.012342,0.012139,-0.023786,0.005092,-0.036644,-0.006497,0.020861,0.002534,0.011816,-0.003877,-0.011729,0.004822,0.001232,-0.006748,-0.00491
TUR_Boncuklu_N:ZHAG_BON004___BC_7950___Coverage_67.13%,0.114961,0.176702,0.018856,-0.073321,0.055703,-0.040439,-0.00423,-0.002769,0.040291,0.079637,0.003735,0.019183,-0.029435,0.01101,-0.041938,-0.021612,0.006128,0.007348,0.005154,-0.00963,-0.011979,0.017682,-0.010476,-0.011327,0.001197
TUR_Boncuklu_N:ZHAJ_BON034___BC_7950___Coverage_42.25%,0.117238,0.164516,0.018856,-0.067507,0.058472,-0.036256,-0.00235,-0.008769,0.031701,0.079819,0.013965,0.015886,-0.033895,0.008395,-0.036509,-0.0179,0.018515,0.007348,0.011061,-0.013632,-0.009733,0.008532,-0.010969,-0.01217,-0.001916
TUR_Boncuklu_N:ZHJ_BON024___BC_8240___Coverage_46.00%,0.114961,0.155376,0.016593,-0.068799,0.052317,-0.037929,-0.00282,-0.002769,0.036405,0.082735,0.006496,0.010041,-0.031962,-0.004817,-0.03963,0.002121,0.035595,0.004181,0.01169,-0.007879,-0.009982,0.002968,-0.01405,-0.010122,-0.008742
TUR_Boncuklu_N:ZKO_BON001___BC_7950___Coverage_50.63%,0.112685,0.17264,0.008674,-0.073967,0.059088,-0.039881,0.00235,-0.002538,0.031088,0.072712,0.008769,0.013638,-0.0278,-0.004266,-0.03963,0,0.040941,0.005828,0.004022,-0.005002,-0.008984,0.011747,-0.006902,-0.017352,0.001676
TUR_Boncuklu_N:ZMOJ_BON014___BC_7950___Coverage_45.31%,0.111547,0.170609,0.001508,-0.071383,0.051702,-0.034861,-0.011986,-0.001846,0.030679,0.071801,0.015427,0.014987,-0.0278,-0.004954,-0.03773,0.00769,0.04081,-0.002154,0.014581,-0.010255,-0.007237,0.007296,-0.005669,-0.007712,-0.011975
TUR_Tepecik_Ciftlik_N:Tep002___BC_6537___Coverage_28.20%,0.10927,0.171624,-0.010559,-0.098192,0.035391,-0.040718,-0.00376,-0.002769,0.02986,0.070708,0.014128,0.013488,-0.017988,-0.011698,-0.042616,0.013126,0.022687,-0.000127,0.012318,0.004002,-0.005865,0.002102,-0.005793,-0.004338,-0.013651
TUR_Tepecik_Ciftlik_N:Tep003___BC_6469___Coverage_46.90%,0.111547,0.174671,-0.017725,-0.0969,0.014772,-0.02761,0.00705,-0.011076,0.016157,0.045195,0.016401,0.009292,-0.005352,0.012937,-0.032301,-0.003713,0.011865,-0.001014,0.010307,-0.003001,0.003868,0.008161,-0.010723,-0.005181,-0.002036
TUR_Tepecik_Ciftlik_N:Tep004___BC_6287___Coverage_23.36%,0.103579,0.17264,-0.017725,-0.099484,0.033852,-0.047411,-0.013631,-0.006231,0.032315,0.055035,0.000974,0.010041,-0.005946,0.016652,-0.038409,-0.02612,0.001043,-0.005701,0.013827,-0.008754,0.010357,0.007543,0.000246,-0.003374,-0.005389
TUR_Tepecik_Ciftlik_N:Tep006___BC_6149___Coverage_11.40%,0.110408,0.173656,-0.011314,-0.10756,0.024312,-0.04518,-0.00799,0,0.026588,0.058862,0.002273,-0.000599,-0.011447,0.003028,-0.027551,-0.025192,-0.00013,0.008615,-0.015084,-0.005378,0.002371,0,-0.012448,-0.00241,0.002754
TUR_Pinarbasi_HG:ZBC_IPB001___BC_13461___Coverage_73.74%,0.113823,0.166547,0.029793,-0.082688,0.070782,-0.04016,-0.005875,0.001846,0.04745,0.079637,0.006008,0.009142,-0.021407,-0.009358,-0.042073,-0.003713,0.0442,-0.002787,0.008045,-0.001251,-0.013851,0.003339,-0.003451,-0.009278,-0.005628
UKR_Meso:I1733___BC_8250___Coverage_22.12%,0.122929,0.076165,0.131615,0.195739,0.027697,0.06024,0.003055,-0.001846,0.009613,-0.07089,0.005034,-0.016485,0.025272,-0.027937,0.020222,0.031556,0.00678,-0.005448,-0.011564,0.024637,0.016845,0.001607,-0.008874,-0.036873,0.003113
UKR_Meso:I1763___BC_8131___Coverage_70.73%,0.122929,0.06804,0.140289,0.19154,0.032929,0.05773,-0.00987,0,0.007772,-0.066334,0.018188,-0.017235,0.035679,-0.022708,0.028637,0.029965,-0.005867,-0.000633,-0.003142,0.020885,0.023708,0.017682,0.001725,-0.027112,0.000239
UKR_Meso:I1819___BC_8708___Coverage_69.20%,0.120652,0.07718,0.144437,0.193478,0.036314,0.049364,-0.003995,0.005307,0.007772,-0.060685,0.013965,-0.010191,0.026462,-0.027112,0.024701,0.03633,-0.000522,0.001394,0,0.026388,0.015847,0.009892,0.008134,-0.039885,-0.000239
UKR_Meso:I5876___BC_6882___Coverage_40.60%,0.12862,0.089367,0.145946,0.17862,0.069859,0.047411,0.006345,0.008307,0.020248,-0.05376,-0.000487,-0.017534,0.031516,-0.014175,0.031487,0.036992,0.008084,0.002914,0.000754,0.035767,0.034439,0.012613,-0.012695,-0.053622,0.009101
UKR_Meso:I5885___BC_6149___Coverage_14.17%,0.120652,0.099522,0.149717,0.188633,0.060319,0.049643,0.003995,0.01223,0.038655,-0.041003,0.006333,-0.028175,0.04103,-0.009083,0.013708,0.036064,0.01708,-0.006461,-0.008296,0.038018,0.042425,0.012242,-0.00456,-0.074348,-0.002275
Wales_Meso:I6754___BC_7630___Coverage_30.27%,0.113823,0.116786,0.186675,0.194124,0.162492,0.064424,0.025146,0.031845,0.090604,0.009841,-0.019324,-0.008842,0.003271,-0.001514,0.062431,0.065897,0.000522,0.010515,-0.002011,0.057903,0.105938,0.017188,-0.045725,-0.174241,0.01916
Wales_Meso:SB460A3_lib___BC_7630___Coverage_26.81%,0.118376,0.114755,0.188937,0.196708,0.163415,0.064145,0.023501,0.029537,0.092445,0.010205,-0.020786,-0.003147,0.00669,-0.001651,0.060803,0.063378,-0.002608,0.009755,-0.006788,0.061404,0.105439,0.019537,-0.048929,-0.176531,0.016406
CMR_Shum_Laka_8000BP:I10871___BC_5963___Coverage_99.70%,-0.607815,0.050776,0.015085,0.026486,-0.001846,0.007809,0.128316,-0.100842,0.010226,-0.006014,-0.00065,-0.024878,-0.022448,-0.002752,0.001221,-0.001193,0.011474,0.02065,-0.003897,-0.002126,-0.004617,0.001113,-0.000246,-0.000361,-0.006466
CMR_Shum_Laka_8000BP:I10872___BC_5870___Coverage_47.21%,-0.597571,0.059916,0.014708,0.026163,-0.011079,0.002231,0.120325,-0.098996,0.017385,-0.008018,-0.00065,-0.023679,-0.018285,-0.007707,0.002986,-0.002387,0.013951,0.014062,0.001508,-0.006003,-0.002371,-0.001855,0.003451,-0.001446,0.002275

G25 modern average:

G25 Iberian Modern individual with high Iberomaurisians:

Duarte · Feb 10, 2022

@Regio X

In this other model I use the G25 Modern Iberian Averages as target and, as source, I try to use the same ancient samples used by Maciamo in the graph below adding ANF (TUR_N) and Shun_Laka_8000BP (CMR):

Code:

ROU_Iron_Gates_HG:I4081___BC_7411___Coverage_26.67%,0.129758,0.117801,0.165933,0.165054,0.117868,0.062193,0.016686,0.038075,0.053381,-0.011481,-0.003897,-0.023529,0.02557,-0.004404,0.026737,0.055422,0,0.016343,-0.010433,0.038644,0.064761,0.011005,-0.017008,-0.113269,0.009221
ROU_Iron_Gates_HG:I4582___BC_6668___Coverage_80.76%,0.122929,0.122879,0.181018,0.182819,0.120022,0.05522,0.01081,0.029537,0.060335,-0.009294,-0.009743,-0.015886,0.023191,0.005643,0.037459,0.044815,0.01356,0.005448,0.001257,0.048148,0.07075,0.009027,-0.021815,-0.117727,0.006347
ROU_Iron_Gates_HG:I4607___BC_6977___Coverage_27.51%,0.133173,0.108662,0.176492,0.177328,0.12033,0.056057,0.00705,0.022384,0.05788,-0.011299,0.00747,-0.018883,0.022299,-0.010046,0.033523,0.046937,0.01017,0.008361,-0.006159,0.05165,0.068379,0.014591,-0.03377,-0.115077,0.010059
ROU_Iron_Gates_HG:I5411___BC_6650___Coverage_61.08%,0.135449,0.113739,0.176492,0.178943,0.119715,0.05773,0.008695,0.030922,0.054608,-0.013485,-0.009256,-0.020232,0.026908,-0.008533,0.035152,0.047202,0.006128,0.004561,-0.00817,0.04102,0.062639,0.007419,-0.027361,-0.102183,0.01449
ROU_Meso:I2534___BC_5720___Coverage_36.34%,0.134311,0.110693,0.168573,0.168284,0.089863,0.064145,0.01081,0.015922,0.046427,-0.033714,0.002598,-0.019633,0.025272,-0.003991,0.026465,0.023866,-0.00665,0.006334,-0.008673,0.035392,0.052158,0.01014,-0.013434,-0.090133,0.012095
SRB_Iron_Gates_HG:I4870___BC_6790___Coverage_52.92%,0.129758,0.113739,0.180264,0.189602,0.14772,0.058846,0.015276,0.024922,0.079355,-0.00656,-0.011205,-0.012589,0.020218,-0.004542,0.040852,0.057014,0.008736,0.0019,-0.005028,0.049774,0.086472,0.012242,-0.037221,-0.137851,0.013771
SRB_Iron_Gates_HG:I4871___BC_6500___Coverage_44.04%,0.140002,0.109677,0.18856,0.184757,0.132332,0.049085,0.021621,0.032076,0.059312,0.003462,-0.009581,-0.017684,0.020367,0.004817,0.03488,0.044815,-0.00013,0.004181,-0.001131,0.04252,0.072497,0.020279,-0.022678,-0.110257,0.014849
SRB_Iron_Gates_HG:I4872___BC_6500___Coverage_29.14%,0.127482,0.122879,0.187052,0.173452,0.131101,0.05271,0.020446,0.034845,0.061357,-0.013303,-0.013153,-0.005695,0.033003,-0.002615,0.029858,0.054229,0.015255,-0.00038,0.000377,0.059153,0.063388,0.012242,-0.032784,-0.128211,0.011735
SRB_Iron_Gates_HG:I4873___BC_5917___Coverage_69.81%,0.135449,0.11577,0.185543,0.19154,0.137872,0.058009,0.008225,0.03023,0.068925,-0.006196,-0.00747,-0.016935,0.02438,0.001239,0.03773,0.047732,0.013038,0.003927,-0.010182,0.049024,0.072248,0.016199,-0.043999,-0.1305,0.008622
SRB_Iron_Gates_HG:I4874___BC_6549___Coverage_69.61%,0.132035,0.113739,0.187429,0.183465,0.131717,0.059404,0.017391,0.032537,0.072197,-0.01057,-0.011854,-0.017984,0.026462,-0.001651,0.04343,0.051975,0.008475,0.003167,-0.000503,0.053651,0.078861,0.01286,-0.035002,-0.117727,0.018681
SRB_Iron_Gates_HG:I4875___BC_6508___Coverage_70.82%,0.126344,0.118817,0.186298,0.201876,0.134487,0.064145,0.011986,0.029768,0.07322,-0.014032,-0.00682,-0.02218,0.029583,0.001927,0.031623,0.058605,0.009388,-0.001267,-0.007919,0.058153,0.080733,0.013602,-0.035002,-0.131103,0.012095
SRB_Iron_Gates_HG:I4876___BC_6505___Coverage_69.66%,0.130897,0.112724,0.185543,0.179589,0.13818,0.054941,0.022326,0.041537,0.068515,-0.010387,-0.008444,-0.016186,0.027502,-0.002477,0.033387,0.036197,-0.007823,0.005701,-0.00993,0.048398,0.079859,0.007914,-0.037098,-0.132669,0.017244
SRB_Iron_Gates_HG:I4877___BC_6555___Coverage_71.04%,0.127482,0.112724,0.19384,0.183788,0.142488,0.051595,0.017391,0.031845,0.064834,-0.015672,-0.003248,-0.024129,0.031516,0.000413,0.031894,0.052108,0.005476,0.009628,-0.005405,0.046522,0.074369,0.0115,-0.041658,-0.126765,0.012693
SRB_Iron_Gates_HG:I4878___BC_5853___Coverage_69.46%,0.129758,0.111708,0.179887,0.175713,0.132025,0.0502,0.011045,0.031383,0.068106,-0.008383,-0.013478,-0.016785,0.029583,0.004266,0.037052,0.053566,0.014733,-0.001014,-0.011187,0.047523,0.085849,0.004204,-0.034386,-0.127247,0.010179
SRB_Iron_Gates_HG:I4880___BC_5863___Coverage_70.37%,0.134311,0.111708,0.181772,0.174421,0.127101,0.052989,0.018096,0.02723,0.067902,-0.014761,-0.013641,-0.023379,0.021258,-0.001514,0.030266,0.053831,0.013299,0.009122,-0.003268,0.049399,0.075741,0.017311,-0.035002,-0.122668,0.005508
SRB_Iron_Gates_HG:I4881___BC_6413___Coverage_71.59%,0.130897,0.119832,0.18592,0.184111,0.131101,0.063308,0.011281,0.038998,0.073629,-0.018953,-0.011854,-0.020232,0.032705,0.010459,0.035966,0.042296,-0.006389,0.002407,-0.00088,0.048898,0.079734,0.007543,-0.037344,-0.133633,0.011376
SRB_Iron_Gates_HG:I4914___BC_6138___Coverage_70.19%,0.134311,0.114755,0.186298,0.179912,0.133563,0.056615,0.014336,0.030922,0.066675,-0.004191,-0.001299,-0.018583,0.025718,0.003441,0.036916,0.05171,0.010691,0.005068,-0.00993,0.059028,0.073246,0.004204,-0.029949,-0.117004,0.012095
SRB_Iron_Gates_HG:I4915___BC_6165___Coverage_71.03%,0.122929,0.112724,0.177247,0.180558,0.123408,0.05271,0.011516,0.03346,0.063811,-0.010205,-0.011205,-0.010641,0.029881,0.001376,0.031487,0.053964,0.007693,0.010515,-0.008547,0.047148,0.077987,0.014344,-0.031305,-0.113269,0.013891
SRB_Iron_Gates_HG:I4916___BC_6813___Coverage_68.50%,0.136588,0.116786,0.182904,0.169899,0.130794,0.063029,0.013631,0.028614,0.070152,-0.016037,-0.006008,-0.024129,0.027651,-0.004679,0.033794,0.041103,-0.000522,0.004687,-0.005782,0.043521,0.072123,0.01793,-0.028347,-0.119414,0.002754
SRB_Iron_Gates_HG:I4917___BC_6108___Coverage_68.56%,0.136588,0.106631,0.182526,0.187987,0.124639,0.057173,0.012221,0.028383,0.061766,-0.012757,-0.009419,-0.017385,0.026908,-0.002615,0.034066,0.05171,0.004955,0.008488,-0.006536,0.048398,0.07075,0.008779,-0.02465,-0.113992,0.008861
SRB_Iron_Gates_HG:I5233___BC_6051___Coverage_71.57%,0.135449,0.117801,0.183281,0.183142,0.130794,0.063866,0.011986,0.032076,0.063198,-0.017859,-0.007957,-0.016335,0.032259,0.006193,0.038002,0.041501,-0.015125,0.009248,-0.004902,0.049149,0.078986,0.007914,-0.03414,-0.122427,0.011376
SRB_Iron_Gates_HG:I5234___BC_7550___Coverage_61.55%,0.132035,0.122879,0.181395,0.173452,0.12987,0.050479,0.00705,0.033922,0.064834,-0.008747,-0.010555,-0.01094,0.017096,-0.000963,0.03583,0.045346,-0.005737,0.014696,-0.009679,0.044396,0.079734,0.009769,-0.040548,-0.130982,0.013053
SRB_Iron_Gates_HG:I5235___BC_8885___Coverage_71.37%,0.125205,0.113739,0.170836,0.175713,0.123715,0.049364,0.012926,0.035768,0.063198,-0.00656,-0.011367,-0.016485,0.026016,-0.007982,0.027823,0.050649,0.013821,-0.000253,-0.004525,0.049899,0.079734,0.012736,-0.031921,-0.119776,0.015687
SRB_Iron_Gates_HG:I5236___BC_8088___Coverage_71.49%,0.122929,0.123895,0.184035,0.181204,0.133563,0.053547,0.013631,0.028845,0.060539,-0.012028,-0.013153,-0.019483,0.026908,0.002615,0.026194,0.046009,0.001434,0.005574,-0.011941,0.049899,0.075492,0.017682,-0.029579,-0.119896,0.00958
SRB_Iron_Gates_HG:I5237___BC_7550___Coverage_71.67%,0.133173,0.126941,0.1912,0.174744,0.138795,0.050479,0.00799,0.032999,0.066879,-0.007107,-0.008607,-0.015586,0.026016,0.00523,0.034337,0.037788,-0.007823,0.007221,-0.006788,0.040895,0.076615,0.005317,-0.031798,-0.124234,0.006466
SRB_Iron_Gates_HG:I5238___BC_8043___Coverage_71.50%,0.130897,0.113739,0.182149,0.172806,0.117868,0.059404,0.010105,0.035768,0.061766,-0.014761,-0.00682,-0.021431,0.030475,0.004817,0.030673,0.050517,0.010952,0.007348,-0.007668,0.044146,0.060518,0.008037,-0.030935,-0.102183,0.008742
SRB_Iron_Gates_HG:I5239___BC_8383___Coverage_70.29%,0.126344,0.110693,0.184789,0.18508,0.124946,0.053268,0.020916,0.032306,0.056653,-0.016766,-0.008931,-0.012589,0.02661,-0.004817,0.02728,0.055025,0.012778,0.003927,-0.002011,0.043646,0.070126,0.006554,-0.034509,-0.118932,0.010777
SRB_Iron_Gates_HG:I5240___BC_8855___Coverage_70.30%,0.127482,0.126941,0.180641,0.180558,0.132025,0.054663,0.012926,0.036229,0.058903,-0.011299,-0.011692,-0.018434,0.02334,-0.00055,0.031623,0.057544,0.011213,0.007601,-0.004148,0.049024,0.069378,0.007419,-0.027854,-0.127488,0.013412
SRB_Iron_Gates_HG:I5242___BC_8580___Coverage_72.66%,0.130897,0.114755,0.178378,0.17216,0.130794,0.056057,0.017156,0.03023,0.062175,-0.008383,-0.008769,-0.020232,0.029732,-0.003716,0.028501,0.044418,0.013951,0.005194,-0.006536,0.045272,0.071249,0.011994,-0.034016,-0.11845,0.005269
SRB_Iron_Gates_HG:I5244___BC_8835___Coverage_70.28%,0.130897,0.113739,0.167442,0.176359,0.132025,0.055499,0.019271,0.035537,0.070561,-0.00656,-0.002761,-0.014237,0.017839,-0.001376,0.032166,0.050384,0.010691,0.006588,-0.013701,0.0519,0.078112,0.005812,-0.035372,-0.122788,0.005149
SRB_Iron_Gates_HG:I5401___BC_6888___Coverage_40.13%,0.129758,0.120848,0.17159,0.169253,0.121561,0.060519,0.00282,0.031153,0.067084,-0.005649,-0.013803,-0.018733,0.024975,-0.003165,0.035016,0.052903,0.000391,0.007475,-0.013575,0.040269,0.075991,0.016569,-0.039439,-0.120137,0.021435
SRB_Iron_Gates_HG:I5402___BC_6206___Coverage_70.19%,0.129758,0.114755,0.187806,0.177974,0.126485,0.055499,0.013396,0.032999,0.058698,-0.011116,-0.010718,-0.019782,0.022894,0.002202,0.027008,0.041235,-0.011213,0.006081,-0.004022,0.048398,0.078362,0.006059,-0.0334,-0.117486,0.008502
SRB_Iron_Gates_HG:I5407___BC_6050___Coverage_73.84%,0.130897,0.120848,0.191577,0.182819,0.139103,0.050758,0.020211,0.032768,0.066061,-0.008201,-0.012342,-0.015736,0.022894,0.001789,0.04058,0.052373,0.003129,-0.001267,-0.008799,0.051275,0.07387,0.005441,-0.032784,-0.127006,0.013651
SRB_Iron_Gates_HG:I5409___BC_7550___Coverage_50.64%,0.129758,0.126941,0.172344,0.1657,0.129563,0.055778,0.019271,0.037845,0.061357,-0.002005,-0.005846,-0.014537,0.02557,-0.001376,0.031216,0.037655,-0.001825,0.011275,-0.004651,0.044897,0.071499,0.01051,-0.034509,-0.12568,0.012693
SRB_Iron_Gates_HG:I5771___BC_6375___Coverage_19.85%,0.133173,0.126941,0.175738,0.171191,0.136025,0.044901,0.016921,0.037152,0.066675,-0.009294,-0.010068,-0.024278,0.017988,-0.002615,0.031487,0.054362,0.013821,0.013429,-0.00817,0.048273,0.077488,0.015333,-0.040672,-0.117245,0.010897
SRB_Iron_Gates_HG:I5772___BC_6500___Coverage_38.11%,0.124067,0.118817,0.173098,0.174421,0.12587,0.056894,0.011986,0.031614,0.049086,-0.005832,-0.001949,-0.01169,0.016501,-0.008257,0.031623,0.030628,-0.006389,0.010135,-0.016969,0.044521,0.06214,0.017311,-0.034879,-0.111944,0.008742
SRB_Iron_Gates_HG_o:I5232___BC_5951___Coverage_70.76%,0.127482,0.149283,0.095034,0.027778,0.09294,-0.003347,0.002585,0.011769,0.054608,0.040821,-0.001624,-0.002997,-0.002379,0.003991,-0.005972,0.013259,0.008345,-0.0019,-0.00264,0.02026,0.024457,0.006801,-0.015036,-0.0629,0.005748
RUS_Argun_River_Meso:cta016___BC_6314___Coverage_97.71%,0.01935,-0.445817,0.087115,-0.040052,-0.076014,-0.055499,0.017156,0.022384,0.01268,0.017677,-0.015265,0.000749,-0.003568,0.009221,-0.002443,-0.007823,0.003651,0.004181,0.01081,0.021635,-0.012852,-0.021887,-0.02428,-0.008073,-0.001437
RUS_Dzhylinda_Meso:Dzhylinda1___BC_6469___Coverage_65.51%,0.037562,-0.364575,0.09692,0.020349,-0.096326,-0.032072,-0.035017,-0.03023,0.001432,-0.010934,0.016076,-0.004496,0.005054,-0.018029,-0.008958,-0.001458,-0.000261,0.000253,0.008673,0.013381,-0.008485,-0.013602,-0.007272,0.00482,-0.002275
RUS_Kolyma_Meso:Kolyma_River___BC_7825___Coverage_99.93%,0.043253,-0.337156,0.087492,0.045543,-0.07663,-0.02259,-0.047707,-0.050767,-0.006545,-0.024055,0.005846,-0.006145,0.017988,-0.026424,-0.021851,-0.004243,0.001173,0.012162,0.018101,0.008879,0.004118,-0.023247,0.013311,0.009158,0.009221
RUS_Veretye_Meso:PES001___BC_10761___Coverage_97.50%,0.124067,0.04773,0.145191,0.204783,0.008617,0.054384,-0.022796,-0.017307,-0.005727,-0.071254,0.014777,-0.011839,0.038652,-0.048168,0.02348,0.025325,-0.01004,0.003547,-0.00264,0.022011,-0.002371,0.01694,0.005053,-0.033017,-0.008263
RUS_Vologda_Veretye_Meso:KAR001___BC_6371___Coverage_15.30%,0.121791,0.033512,0.115022,0.167638,-0.000615,0.06024,-0.021151,-0.010384,-0.024747,-0.07581,0.018512,-0.019033,0.02438,-0.048443,0.015744,0.011668,-0.001565,0.00114,-0.023757,0.023511,0.002496,0.01793,0.01861,-0.021087,-0.009101
MAR_Taforalt:TAF009___BC_12271___Coverage_24.61%,-0.162767,0.07718,-0.024513,-0.079135,0.009848,-0.047969,-0.052877,0.020538,0.13294,0.002005,0.025333,-0.026676,0.057978,-0.052985,0.072882,-0.034076,0.002347,-0.05625,-0.130475,0.04152,-0.026204,-0.120314,0.067909,-0.016508,0.012334
MAR_Taforalt:TAF010___BC_12699___Coverage_72.10%,-0.193499,0.083273,-0.03017,-0.088502,0.034776,-0.055499,-0.076378,0.019384,0.163619,0.008565,0.02111,-0.030573,0.07879,-0.046104,0.077496,-0.046141,-0.00665,-0.069805,-0.144176,0.036518,-0.042924,-0.129217,0.07629,-0.015303,0.018322
MAR_Taforalt:TAF011___BC_12500___Coverage_88.13%,-0.194638,0.085304,-0.021873,-0.088825,0.026774,-0.059961,-0.072148,0.019845,0.161165,0.002551,0.016564,-0.035818,0.080574,-0.051196,0.066367,-0.037523,0.012126,-0.071199,-0.14493,0.035767,-0.041427,-0.12662,0.068279,-0.011447,0.018441
MAR_Taforalt:TAF013___BC_12550___Coverage_84.93%,-0.196914,0.082258,-0.026398,-0.088502,0.032314,-0.057173,-0.074733,0.017768,0.156665,0.002369,0.02111,-0.036717,0.077898,-0.052159,0.072746,-0.038584,0.000913,-0.069552,-0.141285,0.039894,-0.035687,-0.125384,0.075428,-0.011206,0.020477
MAR_Taforalt:TAF014___BC_12550___Coverage_83.86%,-0.201467,0.079211,-0.018479,-0.083011,0.034468,-0.055499,-0.076848,0.014538,0.162596,0.002005,0.020461,-0.029374,0.078344,-0.054223,0.066503,-0.025192,0.017602,-0.063724,-0.151215,0.04127,-0.042176,-0.126126,0.077153,-0.014339,0.012693
Levant_Natufian:I0861___BC_10750___Coverage_9.91%,0.01935,0.135065,-0.039221,-0.135984,0.026774,-0.076137,-0.019036,-0.024691,0.100626,-0.008018,0.02858,-0.019633,0.067343,0.001651,0.022801,0.02612,-0.0103,0.006714,-0.018101,0.041395,-0.004118,-0.003215,-0.014297,-0.011206,0.011975
Levant_Natufian_contam:I1072___BC_10750___Coverage_38.21%,0.021626,0.151314,-0.036204,-0.141475,0.034776,-0.082831,-0.032196,-0.010384,0.128032,0.012028,0.037837,-0.024878,0.085629,0.002615,0.007872,-0.008088,-0.020601,-0.008742,-0.026019,0.040269,0.007112,0.003462,0.007025,0.002289,0.000599
FRA_Nouvelle_Aquitaine_Meso:PER503___BC_7100___Coverage_24.13%,0.122929,0.112724,0.190446,0.186695,0.164646,0.060798,0.030786,0.043383,0.093263,0.014761,-0.023546,-0.018434,0.020961,0.001514,0.059717,0.064969,0.002608,0.017483,-0.001257,0.068783,0.127775,0.008285,-0.057187,-0.182194,0.020836
FRA_Nouvelle_Aquitaine_Meso:PER3023___BC_7100___Coverage_12.97%,0.118376,0.107646,0.194594,0.197031,0.164954,0.044901,0.010575,0.023076,0.092036,0.010752,-0.009581,-0.030723,0.013825,0.001101,0.056731,0.06245,0.00013,-0.006968,-0.007793,0.058653,0.115047,0.019166,-0.043137,-0.184122,0.026465
FRA_Nouvelle_Aquitaine_Meso:PER3123___BC_7100___Coverage_11.13%,0.125205,0.109677,0.181018,0.196708,0.168955,0.059683,0.019506,0.038998,0.096331,0.022415,0.004222,-0.025927,0.005946,0.004679,0.05551,0.064969,-0.009518,0.007095,-0.008296,0.062905,0.120288,0.005935,-0.062363,-0.181953,0.030416
Baltic_LTU_Meso:Spiginas4___BC_6326___Coverage_58.26%,0.134311,0.108662,0.181395,0.186695,0.136949,0.061077,0.010575,0.034383,0.071174,-0.007472,-0.013153,-0.016935,0.029286,0.000138,0.039495,0.060063,0.005215,0.001267,-0.00352,0.048523,0.072248,0.013231,-0.036235,-0.136525,0.012574
Baltic_LVA_HG:I4432___BC_6008___Coverage_63.57%,0.135449,0.100537,0.188937,0.21092,0.110174,0.063587,0.011986,0.023768,0.055221,-0.016219,-0.004709,-0.021281,0.029137,-0.008395,0.039223,0.046141,0.002086,0.007348,-0.005154,0.04252,0.058771,0.008037,-0.029949,-0.119053,0.013771
Baltic_LVA_HG:I4434___BC_5491___Coverage_63.47%,0.122929,0.099522,0.185543,0.208013,0.104327,0.055499,0.013866,0.025153,0.055835,-0.02278,-0.003085,-0.018434,0.032111,-0.006055,0.035152,0.046937,0.005346,0.000253,-0.006285,0.046522,0.060269,0.019043,-0.015283,-0.111582,0.008622
Baltic_LVA_HG:I4438___BC_5298___Coverage_64.52%,0.12862,0.103584,0.175738,0.197354,0.104019,0.052989,0.007285,0.02123,0.044177,-0.029887,-0.000325,-0.019183,0.026759,-0.007432,0.034609,0.052108,-0.000261,0.007981,-0.006285,0.045522,0.059395,0.013973,-0.02884,-0.102424,0.012095
Baltic_LVA_HG:I4439___BC_5696___Coverage_64.59%,0.130897,0.102568,0.182149,0.197354,0.116945,0.055499,0.00799,0.020768,0.061562,-0.019681,-0.016401,-0.014387,0.030921,-0.003303,0.038816,0.05529,0.008605,0.004307,-0.01257,0.040644,0.072622,0.01422,-0.030689,-0.123391,0.003712
Baltic_LVA_HG:I4440___BC_5124___Coverage_62.67%,0.124067,0.109677,0.171213,0.191863,0.103096,0.0502,0.009635,0.021691,0.054403,-0.029704,-0.006171,-0.010341,0.028097,0.005918,0.02823,0.041633,-0.007302,0.009755,-0.004274,0.043271,0.058023,0.013107,-0.025266,-0.10857,0.007065
Baltic_LVA_HG:I4441___BC_4768___Coverage_63.63%,0.135449,0.093429,0.171967,0.188633,0.101557,0.049921,0.0047,0.020307,0.042336,-0.030433,-0.006008,-0.018284,0.026313,-0.00812,0.030673,0.039644,0.008605,-0.0019,-0.011061,0.042145,0.052782,0.022505,-0.024403,-0.105316,0.009939
Baltic_LVA_HG:I4550___BC_6539___Coverage_66.16%,0.130897,0.1046,0.184789,0.200907,0.125562,0.059125,0.009165,0.03046,0.069334,-0.020957,-0.005359,-0.017534,0.023786,-0.002064,0.045738,0.061124,0.005346,0.006334,-0.006159,0.044771,0.072497,0.00643,-0.031551,-0.130862,0.012813
Baltic_LVA_HG:I4551___BC_5720___Coverage_60.35%,0.132035,0.09546,0.178378,0.195739,0.09294,0.057173,0.002115,0.019384,0.050108,-0.03098,-0.003085,-0.014537,0.027651,-0.020781,0.040988,0.044948,0.003651,0.007981,-0.002011,0.043521,0.057523,0.00643,-0.02465,-0.099171,0.003952
Baltic_LVA_HG:I4552___BC_5419___Coverage_64.70%,0.135449,0.098506,0.185543,0.196385,0.10802,0.056894,0.0094,0.020768,0.048063,-0.027153,-0.004709,-0.020682,0.028989,-0.003716,0.03298,0.049854,0.008996,0.006461,0.000377,0.045272,0.063263,0.01422,-0.029826,-0.10869,0.009939
Baltic_LVA_HG:I4553___BC_5420___Coverage_43.85%,0.129758,0.100537,0.181395,0.199615,0.114483,0.051316,0.015981,0.021691,0.05379,-0.02278,-0.008444,-0.02218,0.028692,0,0.042345,0.057146,0.003651,-0.000253,0.001885,0.04102,0.061267,0.01793,-0.026375,-0.113992,0.007903
Baltic_LVA_HG:I4595___BC_5687___Coverage_68.17%,0.126344,0.093429,0.179887,0.187341,0.109559,0.055499,0.002585,0.023076,0.054608,-0.01549,-0.005521,-0.02218,0.027948,0.000963,0.033116,0.05224,0.011604,-0.001774,-0.007416,0.04202,0.063887,0.007048,-0.02354,-0.113631,0.015208
Baltic_LVA_HG:I4596___BC_6020___Coverage_70.35%,0.12862,0.098506,0.18592,0.191863,0.118791,0.058288,0.0094,0.019615,0.058085,-0.028064,0.004222,-0.020082,0.028394,-0.011285,0.031623,0.049456,0.005215,0.00076,-0.003897,0.042896,0.06788,0.008408,-0.033277,-0.116281,0.006347
Baltic_LVA_HG:I4626___BC_5727___Coverage_32.46%,0.121791,0.114755,0.184412,0.200584,0.110482,0.063308,0.002585,0.023537,0.05604,-0.017495,-0.007632,-0.017085,0.020664,0.010046,0.042345,0.036727,-0.008475,0.007728,-0.017221,0.039894,0.068754,0.027327,-0.035495,-0.136766,0.015208
Baltic_LVA_HG:I4628___BC_5083___Coverage_61.08%,0.127482,0.098506,0.177247,0.203491,0.108328,0.051595,0.013161,0.011538,0.048677,-0.032985,-0.002598,-0.020232,0.028543,0.002064,0.029858,0.040175,-0.008736,0.009628,-0.005656,0.04152,0.062265,0.00643,-0.016145,-0.107847,0.016765
Baltic_LVA_HG:I4630___BC_7268___Coverage_65.15%,0.124067,0.08632,0.167819,0.198,0.07386,0.057173,0.00423,0.005307,0.036405,-0.042461,0.004384,-0.009142,0.033597,-0.024634,0.02253,0.041766,0.00013,0.00114,-0.006913,0.036518,0.039805,0.013973,-0.016022,-0.075312,-0.002874
Baltic_LVA_HG:I4632___BC_6366___Coverage_68.26%,0.134311,0.106631,0.183281,0.187664,0.100634,0.059404,0.009635,0.023076,0.050517,-0.031162,-0.009419,-0.024278,0.028692,-0.009221,0.040988,0.053036,0.010691,-0.00038,-0.002137,0.039144,0.062639,0.009769,-0.029456,-0.103991,0.013053
WHG:I1875___BC_7106___Coverage_31.85%,0.130897,0.120848,0.191577,0.194447,0.159107,0.048248,0.015746,0.040152,0.087332,0.007472,-0.016076,-0.015436,0.017839,-0.003303,0.047909,0.047069,0.007302,0.018497,-0.003268,0.057027,0.087471,0.00915,-0.048436,-0.143153,0.01449
WHG:Rochedane___BC_11077___Coverage_19.09%,0.118376,0.111708,0.178001,0.184111,0.150182,0.044623,0.010575,0.034383,0.090809,0.028064,-0.014615,-0.016186,0.013974,-0.002752,0.058767,0.069344,0.002738,0.014189,-0.015335,0.054151,0.101446,0.013231,-0.050778,-0.178579,0.019519
GEO_CHG:KK1___BC_7728___Coverage_99.87%,0.091058,0.102568,-0.083344,-0.00323,-0.08617,0.020638,0.024911,-0.001846,-0.128236,-0.074717,-0.006333,0.023979,-0.054856,0.004404,0.026601,-0.03275,0.02386,-0.013429,-0.022249,0.034767,0.033815,-0.007048,0.006532,-0.025787,-0.002036
DEU_Meso_BDB:BDB001.merged___BC_6650___Coverage_69.84%,0.125205,0.112724,0.194217,0.202199,0.156645,0.051037,0.023266,0.039229,0.090809,0.003462,-0.016564,-0.017085,0.026759,0.006193,0.052252,0.062582,-0.00678,0.013429,0.000251,0.05315,0.099949,0.013725,-0.046095,-0.160746,0.023231
DEU_Meso_TGM:TGM009.A0101___BC_3258___Coverage_58.72%,0.134311,0.141159,0.155751,0.122095,0.127101,0.032909,0.012691,0.015692,0.066266,0.021504,-0.011205,-0.011839,0.010406,-0.002064,0.024973,0.041766,0.011735,0.011275,-0.000754,0.035892,0.077488,0.015209,-0.032661,-0.104955,0.012214
England_Mesolithic:I6767___BC_8330___Coverage_95.47%,0.126344,0.110693,0.202891,0.197031,0.157876,0.055778,0.010575,0.03346,0.086514,0.016583,-0.017863,-0.01139,0.014866,-0.001651,0.061481,0.065499,0.002477,0.009882,-0.005531,0.06353,0.116295,0.019661,-0.055954,-0.179664,0.019399
Iberia_ElMiron:ElMiron___BC_16825___Coverage_54.49%,0.0774,0.044683,0.105217,0.129201,0.11079,0.031236,0.00188,0.006231,0.088559,0.02442,-0.005359,-0.002847,0.008622,-0.013487,0.037459,0.041633,0.002217,0.006968,-0.015209,0.045772,0.063638,0.007914,-0.036481,-0.129054,0.013053
Iberia_Northwest_Meso:Canes___BC_5139___Coverage_69.93%,0.122929,0.101553,0.164802,0.175067,0.130178,0.053547,0.020211,0.031153,0.079355,0.00164,-0.009094,-0.015286,0.023786,-0.000413,0.049266,0.040307,-0.015125,0.009248,-0.012193,0.049399,0.087471,0.007296,-0.04289,-0.144358,0.015687
Iberia_Northwest_Meso:Chan___BC_7159___Coverage_90.02%,0.092197,0.055854,0.124073,0.153426,0.12587,0.042112,0.00705,0.028153,0.091831,0.02934,-0.006658,-0.007943,0.010704,-0.017065,0.055645,0.048528,0.001565,0.008235,-0.016215,0.061154,0.095581,0.01558,-0.050532,-0.16412,0.021555
Iberia_Southeast_Meso:I10899___BC_22500___Coverage_40.02%,0.097888,0.059916,0.114268,0.14632,0.112944,0.030399,0.005405,0.017307,0.089172,0.024784,-0.00747,-0.011989,0.008771,-0.010872,0.037866,0.045213,0.002217,0.012289,-0.00817,0.052025,0.084725,0.013725,-0.045725,-0.147129,0.019399
ITA_Grotta_Continenza_Meso:RMPR7___BC_8756___Coverage_95.96%,0.126344,0.113739,0.200628,0.200907,0.174186,0.059961,0.015276,0.036922,0.106352,0.02606,-0.019974,-0.013638,0.012042,-0.014313,0.07166,0.069742,-0.002086,0.013302,-0.008422,0.066407,0.119289,0.009521,-0.059405,-0.195811,0.025866
ITA_Grotta_Continenza_Meso:RMPR11___BC_9918___Coverage_64.13%,0.114961,0.109677,0.197988,0.204783,0.168955,0.062472,0.018096,0.040614,0.105739,0.030798,-0.018837,-0.012739,0.015907,-0.009634,0.073832,0.06961,0.007562,0.014696,-0.01433,0.057403,0.113924,0.009645,-0.064459,-0.194485,0.022154
ITA_Grotta_Continenza_Meso:RMPR15___BC_7136___Coverage_95.73%,0.126344,0.112724,0.204022,0.208982,0.175417,0.063029,0.014806,0.046152,0.113715,0.024602,-0.019162,-0.016635,0.020664,-0.002064,0.06691,0.067753,-0.004824,0.008108,-0.007039,0.067532,0.120787,0.014838,-0.058789,-0.201233,0.017962
IRL_Meso:KGH6___BC_4708___Coverage_62.28%,0.129758,0.120848,0.201005,0.200584,0.165262,0.062193,0.018801,0.040844,0.088968,0.010023,-0.011367,-0.014087,0.015907,0.00289,0.056324,0.056748,-0.011343,0.009628,-0.002388,0.0529,0.109806,0.015828,-0.044985,-0.174482,0.02407
IRL_Meso:SRA62___BC_4051___Coverage_99.89%,0.125205,0.113739,0.195726,0.201876,0.167108,0.06526,0.018096,0.034614,0.099603,0.010023,-0.011692,-0.013338,0.021258,0.000688,0.061753,0.059533,-0.005867,0.015583,-0.00993,0.060279,0.111054,0.006925,-0.056201,-0.174362,0.020238
IRN_Belt_Cave_Meso_low_res:I2312_all_d___BC_10000___Coverage_2.64%,0.046667,0.055854,-0.107102,0.029393,-0.100942,0.058288,0.000235,-0.009,-0.064834,-0.059956,0.033614,0.02203,-0.010258,-0.000275,0.057817,0.044285,-0.029597,0.008361,-0.001885,-0.008004,0.013227,-0.016569,-0.023787,-0.025666,0.056761
IRN_HotuIIIb_Meso:I1293___BC_8850___Coverage_3.38%,0.052359,0.064994,-0.124073,0.043282,-0.112636,0.019522,0.003995,-0.007615,-0.071992,-0.053031,0.009906,0.008842,0.001933,-0.017616,0.030673,0.055157,0.004824,-0.010769,0.010559,-0.029389,0.001123,-0.013231,-0.00493,-0.022413,0.025507
LUX_Loschbour:I0001___BC_6075___Coverage_40.06%,0.133173,0.106631,0.20176,0.192186,0.164338,0.055778,0.00611,0.036922,0.096535,0.02278,-0.020786,-0.016186,0.024975,-0.007432,0.065824,0.063643,0.008084,0.006714,-0.013324,0.065281,0.120038,0.019166,-0.059405,-0.175687,0.022992
NOR_Meso:Hum1___BC_7414___Coverage_35.23%,0.125205,0.071087,0.152357,0.196062,0.044316,0.06526,-0.004935,0.003231,0.014112,-0.054853,0.010393,-0.015436,0.020812,-0.028626,0.015065,0.03328,-0.002217,0.006461,-0.015335,0.022136,0.018717,0.019784,-0.005423,-0.056514,0.006227
NOR_Meso:Hum2___BC_7414___Coverage_94.70%,0.126344,0.082258,0.158014,0.185726,0.050779,0.061077,0,0.004384,0.024543,-0.048657,0.009581,-0.017834,0.027948,-0.035231,0.027958,0.041633,-0.001695,0.002914,-0.004399,0.03089,0.026079,0.014715,-0.008997,-0.059044,0.000359
SWE_Meso:ble008___BC_7875___Coverage_4.54%,0.12862,0.083273,0.164425,0.204783,0.066474,0.056615,-0.015276,0.010153,0.032519,-0.050662,0.012342,-0.020831,0.031665,-0.023121,0.036644,0.045478,-0.001043,-0.001394,-0.003017,0.029639,0.037184,0.009027,-0.019103,-0.079047,0.001916
SWE_Meso:SBj___BC_6821___Coverage_29.17%,0.135449,0.093429,0.167442,0.184757,0.080323,0.059125,-0.00329,0.011769,0.037428,-0.053942,-0.001299,-0.02218,0.029881,-0.007432,0.040716,0.030761,-0.010561,0.004941,-0.003017,0.046772,0.049413,0.016569,-0.01368,-0.096038,0.002754
SWE_Meso:SF9___BC_7194___Coverage_70.63%,0.129758,0.092413,0.166687,0.183465,0.089555,0.060798,0.006345,0.014307,0.044995,-0.035172,-0.003085,-0.016785,0.024678,-0.019405,0.031759,0.049058,0.006258,-0.003167,-0.008422,0.041145,0.053031,0.022134,-0.023664,-0.099171,0.006706
SWE_Meso:SF12___BC_6945___Coverage_96.85%,0.134311,0.09546,0.166687,0.193155,0.0834,0.061635,0.006815,0.011076,0.036201,-0.041185,-0.001137,-0.017385,0.031516,-0.020231,0.033387,0.040175,-0.001173,0.002534,-0.007039,0.047523,0.037309,0.012489,-0.025389,-0.092784,0.00455
SWE_Motala_HG:I0012___BC_5648___Coverage_67.21%,0.135449,0.084289,0.173476,0.195739,0.092017,0.056894,-0.00752,0.009692,0.050722,-0.038999,-0.000325,-0.018434,0.032557,-0.016928,0.02823,0.052771,0.004303,0,-0.006913,0.035017,0.062016,0.016693,-0.021445,-0.104714,0.001437
SWE_Motala_HG:I0013___BC_5772___Coverage_27.48%,0.127482,0.088351,0.155751,0.168607,0.089247,0.049921,-0.00329,0.001615,0.040291,-0.030616,0.00747,-0.015736,0.023488,-0.026699,0.034202,0.04402,0.00326,0.002407,-0.009427,0.048023,0.043922,0.010634,-0.019966,-0.097002,0.010897
SWE_Motala_HG:I0014___BC_5736___Coverage_64.22%,0.137726,0.083273,0.167064,0.190571,0.078476,0.056336,-0.004935,0.006,0.036201,-0.038816,0.002273,-0.015436,0.031962,-0.009909,0.034066,0.046672,0.007953,0.006081,-0.005279,0.043771,0.04517,0.011871,-0.026991,-0.098689,0.006107
SWE_Motala_HG:I0015___BC_5760___Coverage_51.34%,0.137726,0.092413,0.160653,0.193155,0.085554,0.058567,0.003995,0.01223,0.025565,-0.041368,-0.002923,-0.019782,0.031219,-0.018304,0.032437,0.051047,0.006128,0.000253,-0.000754,0.040269,0.049163,0.021763,-0.022185,-0.095315,0.008502
SWE_Motala_HG:I0011___BC_5614___Coverage_53.97%,0.124067,0.099522,0.168573,0.188633,0.087093,0.054105,0,0.013153,0.035383,-0.04483,0.001786,-0.024129,0.035976,-0.014863,0.028908,0.051975,0.007171,0.003421,-0.009302,0.03164,0.053531,0.011129,-0.019843,-0.092784,0.008263
TUR_Barcin_N:I0707___BC_6146___Coverage_85.98%,0.122929,0.184826,0.001886,-0.110144,0.054779,-0.048527,0.00141,-0.011769,0.036201,0.08474,0.011205,0.016335,-0.021704,0.002615,-0.038409,-0.014187,0.022817,0.00114,0.012947,-0.002751,-0.011979,0.009645,-0.008627,0.001566,-0.001676
TUR_Barcin_N:I0708___BC_6151___Coverage_83.49%,0.119514,0.173656,-0.003017,-0.101745,0.042469,-0.046854,-0.00094,-0.012692,0.021066,0.074717,0.009419,0.009142,-0.017691,0.000963,-0.041938,-0.007955,0.024121,0.000633,0.015209,-0.013882,-0.022336,0.008903,-0.012448,-0.012652,-0.007305
TUR_Barcin_N:I0709___BC_6135___Coverage_84.11%,0.119514,0.19092,0.008674,-0.108206,0.050163,-0.044065,-0.00282,-0.003923,0.038655,0.088202,0.006983,0.012289,-0.023488,0.001789,-0.042345,-0.023999,0.002347,-0.003674,0.011941,-0.019759,-0.006239,0.012242,-0.000616,-0.00723,-0.002994
TUR_Barcin_N:I0723___BC_5920___Coverage_36.12%,0.118376,0.178733,0.009805,-0.103037,0.057241,-0.05773,0.003525,0.000462,0.041518,0.080548,0.001624,0.004946,-0.027056,-0.005643,-0.043702,-0.006762,0.03729,0.00152,0.017975,-0.009254,-0.015473,0.002968,0.006779,-0.00012,-0.006227
TUR_Barcin_N:I0724___BC_6000___Coverage_4.80%,0.117238,0.168578,0.018856,-0.10013,0.052933,-0.047969,-0.00094,-0.004384,0.031088,0.075446,0.008931,0.01139,-0.017691,-0.003303,-0.045059,0.001989,0.041853,0.012922,0.020363,-0.009755,-0.018717,0.004699,-0.007518,-0.001928,-0.008023
TUR_Barcin_N:I0726___BC_6000___Coverage_19.84%,0.120652,0.180764,0.00264,-0.104653,0.053548,-0.054663,-0.005875,-0.002308,0.035383,0.088749,0.009743,0.015586,-0.027651,0.006881,-0.040716,-0.037655,-0.001825,0.002914,0.0225,-0.015382,-0.013351,0.007666,-0.004683,0.00253,0.006945
TUR_Barcin_N:I0727___BC_6000___Coverage_3.88%,0.114961,0.185842,0.004525,-0.103683,0.036314,-0.053547,-0.00141,-0.008077,0.031088,0.077633,0.005846,0.01109,-0.031813,0.00055,-0.056052,-0.010607,0.022817,0.009122,0.032807,-0.015007,-0.017968,0.005441,-0.016022,-0.007953,0.008023
TUR_Barcin_N:I0736___BC_6350___Coverage_69.43%,0.119514,0.183811,0.006788,-0.091732,0.049855,-0.049921,-0.0047,-0.006,0.04295,0.077815,0.012829,0.013338,-0.020961,-0.011423,-0.04058,0.005701,0.033248,-0.007475,0.007793,-0.007003,-0.016097,0.006306,-0.005916,-0.000964,-0.007544
TUR_Barcin_N:I0744___BC_6320___Coverage_75.46%,0.119514,0.186857,0.009428,-0.107883,0.058472,-0.052989,-0.00987,-0.01223,0.03027,0.082371,0.010393,0.01139,-0.031813,0.003441,-0.048045,-0.011668,0.022426,0.000633,0.005279,-0.007253,-0.012852,-0.000124,-0.004683,0.002289,0.001796
TUR_Barcin_N:I0745___BC_6293___Coverage_84.87%,0.118376,0.178733,-0.002263,-0.098838,0.049548,-0.046575,-0.010105,-0.002538,0.036814,0.075628,0.010068,0.014237,-0.017542,0.00812,-0.035966,-0.020949,0.005346,0.006334,0.020489,-0.014382,-0.017095,0.008037,0.001356,-0.009278,-0.004191
TUR_Barcin_N:I0746___BC_5978___Coverage_85.47%,0.120652,0.180764,0.011691,-0.093024,0.048317,-0.043507,-0.012691,-0.010615,0.034565,0.078726,0.010393,0.009591,-0.023786,0.006606,-0.048316,-0.027844,0.005607,0.004054,0.012947,-0.017383,-0.013102,0.011005,-0.006532,-0.005543,-0.002036
TUR_Barcin_N:I1096___BC_6350___Coverage_64.66%,0.120652,0.184826,0.008297,-0.101745,0.051702,-0.044344,-0.005405,-0.003692,0.039473,0.0831,0.010718,0.017385,-0.02438,0.006331,-0.043702,-0.0179,0.025946,-0.00076,0.012821,-0.005878,-0.015722,0.00507,-0.005793,0.007832,-0.016406
TUR_Barcin_N:I1097___BC_6332___Coverage_64.39%,0.120652,0.18178,-0.001886,-0.106591,0.054472,-0.048527,-0.00611,-0.007615,0.038246,0.084922,0.008769,0.014687,-0.022894,0.000413,-0.048859,-0.006629,0.021383,0.003421,0.013952,-0.015257,-0.013975,0.005441,-0.011462,-0.009158,-0.002515
TUR_Barcin_N:I1098___BC_6332___Coverage_67.81%,0.114961,0.179749,-0.004148,-0.092701,0.040931,-0.045459,-0.001175,-0.010846,0.030883,0.068703,0.009743,0.007044,-0.019623,0.000688,-0.044381,-0.001326,0.032987,0.003294,0.006788,-0.001501,-0.01148,0.007914,0.007025,-0.002771,-0.00958
TUR_Barcin_N:I1099___BC_6350___Coverage_46.49%,0.111547,0.19092,0.001508,-0.0969,0.055395,-0.04518,0.003525,-0.010615,0.037223,0.077997,0.006171,0.01124,-0.020515,0.00289,-0.039902,-0.016309,0.021644,0.00266,0.013324,-0.007504,-0.003868,0.002844,0.002588,-0.003012,-0.006347
TUR_Barcin_N:I1100___BC_6350___Coverage_25.57%,0.112685,0.17264,-0.001131,-0.084949,0.049855,-0.054384,-0.00705,-0.002308,0.042132,0.088749,-0.003573,0.008692,-0.02557,-0.006881,-0.040173,-0.00769,0.031553,-0.00266,0.007793,-0.01063,-0.023708,-0.00136,0.003574,-0.003253,-0.001557
TUR_Barcin_N:I1101___BC_6350___Coverage_56.53%,0.114961,0.179749,0.006411,-0.100776,0.054779,-0.043786,-0.00094,-0.000462,0.042541,0.078544,0.005684,0.008692,-0.023042,0.007432,-0.034744,-0.010209,0.01682,0.003927,0.018729,-0.006378,-0.020713,0.004575,-0.000616,-0.003133,-0.010179
TUR_Barcin_N:I1102___BC_6350___Coverage_35.46%,0.106994,0.170609,0.00528,-0.097546,0.059703,-0.045459,-0.003995,-0.007846,0.030474,0.08474,0.005196,0.010041,-0.029732,-0.006193,-0.031759,0.001856,0.029597,0.002154,0.013073,-0.008754,-0.009109,0.010634,-0.003821,-0.003856,-0.002634
TUR_Barcin_N:I1103___BC_6350___Coverage_51.86%,0.112685,0.169593,-0.006411,-0.10013,0.044008,-0.046854,-0.00705,-0.005538,0.039269,0.075992,0.011367,0.013638,-0.02215,-0.005505,-0.036644,-0.01127,0.019427,-0.002027,0.010559,-0.008004,-0.016346,0.005564,-0.011216,-0.009278,-0.006945
TUR_Barcin_N:I1580___BC_6255___Coverage_78.21%,0.127482,0.182795,-0.003017,-0.103037,0.052317,-0.04769,-0.008695,-0.012692,0.040496,0.076904,0.007307,0.014987,-0.020961,-0.003716,-0.043159,0.001724,0.035986,-0.001647,0.006788,-0.009254,-0.010357,-0.001731,0.000246,-0.000482,-0.010298
TUR_Barcin_N:I1581___BC_6302___Coverage_71.36%,0.113823,0.175687,0.001131,-0.110467,0.057241,-0.045459,-0.003995,-0.008077,0.040905,0.084558,0.004222,0.013488,-0.02215,-0.000826,-0.04248,0.003978,0.040549,0.004687,0.005405,-0.005628,-0.010731,0.00643,-0.013557,0.003494,-0.000958
TUR_Barcin_N:I1583___BC_6323___Coverage_99.28%,0.119514,0.180764,0.00264,-0.10756,0.048932,-0.051037,-0.010575,-0.008769,0.035792,0.087656,0.012342,0.012139,-0.023786,0.005092,-0.036644,-0.006497,0.020861,0.002534,0.011816,-0.003877,-0.011729,0.004822,0.001232,-0.006748,-0.00491
TUR_Boncuklu_N:ZHAG_BON004___BC_7950___Coverage_67.13%,0.114961,0.176702,0.018856,-0.073321,0.055703,-0.040439,-0.00423,-0.002769,0.040291,0.079637,0.003735,0.019183,-0.029435,0.01101,-0.041938,-0.021612,0.006128,0.007348,0.005154,-0.00963,-0.011979,0.017682,-0.010476,-0.011327,0.001197
TUR_Boncuklu_N:ZHAJ_BON034___BC_7950___Coverage_42.25%,0.117238,0.164516,0.018856,-0.067507,0.058472,-0.036256,-0.00235,-0.008769,0.031701,0.079819,0.013965,0.015886,-0.033895,0.008395,-0.036509,-0.0179,0.018515,0.007348,0.011061,-0.013632,-0.009733,0.008532,-0.010969,-0.01217,-0.001916
TUR_Boncuklu_N:ZHJ_BON024___BC_8240___Coverage_46.00%,0.114961,0.155376,0.016593,-0.068799,0.052317,-0.037929,-0.00282,-0.002769,0.036405,0.082735,0.006496,0.010041,-0.031962,-0.004817,-0.03963,0.002121,0.035595,0.004181,0.01169,-0.007879,-0.009982,0.002968,-0.01405,-0.010122,-0.008742
TUR_Boncuklu_N:ZKO_BON001___BC_7950___Coverage_50.63%,0.112685,0.17264,0.008674,-0.073967,0.059088,-0.039881,0.00235,-0.002538,0.031088,0.072712,0.008769,0.013638,-0.0278,-0.004266,-0.03963,0,0.040941,0.005828,0.004022,-0.005002,-0.008984,0.011747,-0.006902,-0.017352,0.001676
TUR_Boncuklu_N:ZMOJ_BON014___BC_7950___Coverage_45.31%,0.111547,0.170609,0.001508,-0.071383,0.051702,-0.034861,-0.011986,-0.001846,0.030679,0.071801,0.015427,0.014987,-0.0278,-0.004954,-0.03773,0.00769,0.04081,-0.002154,0.014581,-0.010255,-0.007237,0.007296,-0.005669,-0.007712,-0.011975
TUR_Tepecik_Ciftlik_N:Tep002___BC_6537___Coverage_28.20%,0.10927,0.171624,-0.010559,-0.098192,0.035391,-0.040718,-0.00376,-0.002769,0.02986,0.070708,0.014128,0.013488,-0.017988,-0.011698,-0.042616,0.013126,0.022687,-0.000127,0.012318,0.004002,-0.005865,0.002102,-0.005793,-0.004338,-0.013651
TUR_Tepecik_Ciftlik_N:Tep003___BC_6469___Coverage_46.90%,0.111547,0.174671,-0.017725,-0.0969,0.014772,-0.02761,0.00705,-0.011076,0.016157,0.045195,0.016401,0.009292,-0.005352,0.012937,-0.032301,-0.003713,0.011865,-0.001014,0.010307,-0.003001,0.003868,0.008161,-0.010723,-0.005181,-0.002036
TUR_Tepecik_Ciftlik_N:Tep004___BC_6287___Coverage_23.36%,0.103579,0.17264,-0.017725,-0.099484,0.033852,-0.047411,-0.013631,-0.006231,0.032315,0.055035,0.000974,0.010041,-0.005946,0.016652,-0.038409,-0.02612,0.001043,-0.005701,0.013827,-0.008754,0.010357,0.007543,0.000246,-0.003374,-0.005389
TUR_Tepecik_Ciftlik_N:Tep006___BC_6149___Coverage_11.40%,0.110408,0.173656,-0.011314,-0.10756,0.024312,-0.04518,-0.00799,0,0.026588,0.058862,0.002273,-0.000599,-0.011447,0.003028,-0.027551,-0.025192,-0.00013,0.008615,-0.015084,-0.005378,0.002371,0,-0.012448,-0.00241,0.002754
TUR_Pinarbasi_HG:ZBC_IPB001___BC_13461___Coverage_73.74%,0.113823,0.166547,0.029793,-0.082688,0.070782,-0.04016,-0.005875,0.001846,0.04745,0.079637,0.006008,0.009142,-0.021407,-0.009358,-0.042073,-0.003713,0.0442,-0.002787,0.008045,-0.001251,-0.013851,0.003339,-0.003451,-0.009278,-0.005628
UKR_Meso:I1733___BC_8250___Coverage_22.12%,0.122929,0.076165,0.131615,0.195739,0.027697,0.06024,0.003055,-0.001846,0.009613,-0.07089,0.005034,-0.016485,0.025272,-0.027937,0.020222,0.031556,0.00678,-0.005448,-0.011564,0.024637,0.016845,0.001607,-0.008874,-0.036873,0.003113
UKR_Meso:I1763___BC_8131___Coverage_70.73%,0.122929,0.06804,0.140289,0.19154,0.032929,0.05773,-0.00987,0,0.007772,-0.066334,0.018188,-0.017235,0.035679,-0.022708,0.028637,0.029965,-0.005867,-0.000633,-0.003142,0.020885,0.023708,0.017682,0.001725,-0.027112,0.000239
UKR_Meso:I1819___BC_8708___Coverage_69.20%,0.120652,0.07718,0.144437,0.193478,0.036314,0.049364,-0.003995,0.005307,0.007772,-0.060685,0.013965,-0.010191,0.026462,-0.027112,0.024701,0.03633,-0.000522,0.001394,0,0.026388,0.015847,0.009892,0.008134,-0.039885,-0.000239
UKR_Meso:I5876___BC_6882___Coverage_40.60%,0.12862,0.089367,0.145946,0.17862,0.069859,0.047411,0.006345,0.008307,0.020248,-0.05376,-0.000487,-0.017534,0.031516,-0.014175,0.031487,0.036992,0.008084,0.002914,0.000754,0.035767,0.034439,0.012613,-0.012695,-0.053622,0.009101
UKR_Meso:I5885___BC_6149___Coverage_14.17%,0.120652,0.099522,0.149717,0.188633,0.060319,0.049643,0.003995,0.01223,0.038655,-0.041003,0.006333,-0.028175,0.04103,-0.009083,0.013708,0.036064,0.01708,-0.006461,-0.008296,0.038018,0.042425,0.012242,-0.00456,-0.074348,-0.002275
Wales_Meso:I6754___BC_7630___Coverage_30.27%,0.113823,0.116786,0.186675,0.194124,0.162492,0.064424,0.025146,0.031845,0.090604,0.009841,-0.019324,-0.008842,0.003271,-0.001514,0.062431,0.065897,0.000522,0.010515,-0.002011,0.057903,0.105938,0.017188,-0.045725,-0.174241,0.01916
Wales_Meso:SB460A3_lib___BC_7630___Coverage_26.81%,0.118376,0.114755,0.188937,0.196708,0.163415,0.064145,0.023501,0.029537,0.092445,0.010205,-0.020786,-0.003147,0.00669,-0.001651,0.060803,0.063378,-0.002608,0.009755,-0.006788,0.061404,0.105439,0.019537,-0.048929,-0.176531,0.016406
CMR_Shum_Laka_8000BP:I10871___BC_5963___Coverage_99.70%,-0.607815,0.050776,0.015085,0.026486,-0.001846,0.007809,0.128316,-0.100842,0.010226,-0.006014,-0.00065,-0.024878,-0.022448,-0.002752,0.001221,-0.001193,0.011474,0.02065,-0.003897,-0.002126,-0.004617,0.001113,-0.000246,-0.000361,-0.006466
CMR_Shum_Laka_8000BP:I10872___BC_5870___Coverage_47.21%,-0.597571,0.059916,0.014708,0.026163,-0.011079,0.002231,0.120325,-0.098996,0.017385,-0.008018,-0.00065,-0.023679,-0.018285,-0.007707,0.002986,-0.002387,0.013951,0.014062,0.001508,-0.006003,-0.002371,-0.001855,0.003451,-0.001446,0.002275

Here are the results:

Palermo Trapani · Feb 10, 2022

Duarte: How are you? I have a question about the G25 model, which I can't run on my own DNA since I don't have the coordinates. Do the scaled values for G25 allow for comparisons across populations of different time periods, or would you need a scale from the same period, etc. By scale I assume in G25 variables are being divided by some common denominator, which is thus the scaler used to calculate the data. The reason I ask is that on a site that I visit (Italianthro) the blogger who runs that site posted heat maps for the Roman Samples from Antonio et al 2019 and Ancient Greeks using some models developed by a Antrogenica poster (a site that I am not a member of) and compared them to modern Italians and Greeks (thread 8 October 2020). My assumption is the model was perhaps G25, although the Heat map does resemble what one would get using Eurogenes K36.

The other day a similar map was put up using Iron Age Balkan samples and how they are close to modern Italians (8 February 2022).

Interestingly, Hannah Moots posted in the thread regarding the Roman samples from Antonio et al 2019 (she is a co-author on that paper) asking about scaling and comparing across time periods. So if the G25 model using scaling allows for a comparison of population groups from different time periods, that might be a way to address her question. (her question was posted 17 June 2021, and is still there in the thread).

Duarte · Feb 11, 2022

Palermo Trapani said:
Duarte: How are you? I have a question about the G25 model, which I can't run on my own DNA since I don't have the coordinates. Do the scaled values for G25 allow for comparisons across populations of different time periods, or would you need a scale from the same period, etc. By scale I assume in G25 variables are being divided by some common denominator, which is thus the scaler used to calculate the data. The reason I ask is that on a site that I visit (Italianthro) the blogger who runs that site posted heat maps for the Roman Samples from Antonio et al 2019 and Ancient Greeks using some models developed by a Antrogenica poster (a site that I am not a member of) and compared them to modern Italians and Greeks (thread 8 October 2020). My assumption is the model was perhaps G25, although the Heat map does resemble what one would get using Eurogenes K36.

The other day a similar map was put up using Iron Age Balkan samples and how they are close to modern Italians (8 February 2022).

Interestingly, Hannah Moots posted in the thread regarding the Roman samples from Antonio et al 2019 (she is a co-author on that paper) asking about scaling and comparing across time periods. So if the G25 model using scaling allows for a comparison of population groups from different time periods, that might be a way to address her question. (her question was posted 17 June 2021, and is still there in the thread).

Hello @PT. I'm fine thanks.

I also don't frequent Antrogenica or The Apricity but I am curious when the theme is ancient calculators.

About your question, you can use the G25 scaled coordinates of ancient populations as source, labeled according to the country where the sample was found, its estimated age, the archaeological population to which it belongs and the quality of the sample, by accessing the following Vahaduo link (see source data):

https://vahaduo.genetics.ovh/G25ancientdate.html

If you don't have your own coordinates to compare, you can use as target the scaled coordinates of modern, individual and/or average samples. They are also available in Vahaduo G25 modern calculators.

Fraternal hugs.

Palermo Trapani · Feb 11, 2022

Duarte: Ok, thanks. I guess I need to first find out what Calculator was used for those comparisons of Ancient Romans and Greeks to modern Italians and Greeks over at Italianthro. I assumed, probably incorrectly, it was G25 since it was produced by a member at Anthrogenica.

Duarte · Feb 11, 2022

Palermo Trapani said:
Duarte: Ok, thanks. I guess I need to first find out what Calculator was used for those comparisons of Ancient Romans and Greeks to modern Italians and Greeks over at Italianthro. I assumed, probably incorrectly, it was G25 since it was produced by a member at Anthrogenica.

You are welcome PT. I don't know if I was able to help you with anything, but what I did in post #84 was compare the samples of modern Iberians (average) with ancient populations from the Epipaleolithic/Mesolithic/Neolithic periods of western Eurasia and North Africa and try to isolate the % of Iberomaurisian in every modern Iberian pop.

Palermo Trapani · Feb 11, 2022

Duarte said:
You are welcome PT. I don't know if I was able to help you with anything, but what I did in post #84 was compare the samples of modern Iberians (average) with ancient populations from the Epipaleolithic/Mesolithic/Neolithic periods of western Eurasia and North Africa and try to isolate the % of Iberomaurisian in every modern Iberian pop.

Duarte: Your Models were good, I think you did a good job with those. Seem you captured the genetic source populations of Iberia and got really good fits.

Regio X · Feb 12, 2022

@Duarte
Looks better. These last numbers for Iberomaurusian in Portuguese seem more realistic than ~10%, in my opinion.

Model with pre-Neolithic pops mainly, as Iberomaurisians were.

Target	Distance	AHG	CHG	CMR_Shum_Laka_8000BP	EHG	IRN_HotuIIIb_Meso	KEN_Early_Pastoral_N	Natufian	Taforalt	WHG
Moroccan_South_Avg	0.05911990	31.6	3.2	22.4	0.0	3.2	4.4	0.0	35.2	0.0
Moroccan_North_Avg	0.03070748	43.6	6.6	5.6	1.2	4.8	0.0	9.0	28.8	0.4
Spanish_Asturias_Avg	0.06501181	58.8	12.0	0.0	15.8	0.0	0.0	0.0	4.0	9.4
Spanish_Castilla_Y_Leon_Avg	0.05381195	58.8	11.6	0.0	17.2	1.0	0.0	0.4	3.8	7.2
Portuguese_Avg	0.04882801	58.4	10.4	0.0	15.4	3.6	0.0	1.6	3.4	7.2
Spanish_Extremadura_Avg	0.04858755	58.4	8.4	0.0	14.0	6.8	0.0	1.0	3.2	8.2
Spanish_Galicia_Avg	0.05045096	58.6	9.2	0.0	16.2	4.2	0.0	1.0	2.8	8.0
Spanish_Andalucia_Avg	0.05066866	58.4	10.0	0.0	13.6	4.6	0.0	2.0	2.4	9.0
Spanish_Murcia_Avg	0.04444479	60.2	9.2	0.0	15.2	3.8	0.0	2.2	1.8	7.6
Spanish_Cantabria_Avg	0.05088297	61.2	8.6	0.0	15.0	4.4	0.0	0.0	1.2	9.6
Spanish_Cataluna_Avg	0.05008250	60.2	10.0	0.0	15.8	3.2	0.0	0.0	1.2	9.6
Spanish_Aragon_Avg	0.05584008	61.8	10.8	0.0	15.4	2.2	0.0	0.0	1.0	8.8
Spanish_Valencia_Avg	0.05103732	60.2	9.6	0.0	15.0	4.0	0.0	1.0	0.8	9.4
Spanish_Castilla_La_Mancha_Avg	0.05247349	60.4	9.8	0.0	15.0	3.6	0.0	2.4	0.4	8.4
Spanish_La_Rioja_Avg	0.05073410	62.6	9.4	0.0	14.0	3.4	0.0	0.0	0.0	10.6
Spanish_Navarra_Avg	0.06100040	61.6	6.8	0.0	15.6	5.2	0.0	1.4	0.0	9.4
Spanish_Pais_Vasco_Avg	0.06779314	61.2	9.0	0.0	15.6	1.2	0.0	0.0	0.0	13.0

The "classic" model, based mainly in Neolithics.

Target	Distance	CMR_Shum_Laka_8000BP	IRN_Ganj_Dareh_N	KEN_Pastoral_N	Levant_PPNB	MAR_EN	TUR_Barcin_N	TUR_Tepecik_N	WHG	Yamnaya_Samara
Moroccan_South_Avg	0.05234851	20.2	2.0	9.8	0.0	35.6	28.4	0.0	1.6	2.4
Moroccan_North_Avg	0.01512080	5.2	4.4	2.6	1.6	31.2	33.8	12.2	2.6	6.4
Portuguese_Avg	0.02099203	0.0	0.0	0.0	0.0	6.0	51.2	0.0	10.4	32.4
Spanish_Extremadura_Avg	0.01978206	0.0	0.0	0.0	0.0	6.0	51.0	0.0	10.4	32.6
Spanish_Castilla_Y_Leon_Avg	0.02557971	0.0	0.0	0.0	0.0	5.8	50.4	0.0	11.8	32.0
Spanish_Asturias_Avg	0.03316790	0.0	0.0	0.0	0.0	5.4	51.4	0.0	14.4	28.8
Spanish_Andalucia_Avg	0.02023283	0.0	0.0	0.0	0.0	5.2	52.2	0.0	11.8	30.8
Spanish_Galicia_Avg	0.02232224	0.0	0.0	0.0	0.0	5.2	50.8	0.0	11.4	32.6
Spanish_Murcia_Avg	0.01925924	0.0	0.0	0.0	0.0	4.4	53.4	0.0	11.6	30.6
Spanish_Cantabria_Avg	0.02554839	0.0	0.0	0.0	0.0	3.2	52.6	0.0	13.2	31.0
Spanish_Castilla_La_Mancha_Avg	0.02200687	0.0	0.0	0.0	0.0	3.2	53.4	0.0	11.8	31.6
Spanish_Cataluna_Avg	0.02431932	0.0	0.0	0.0	0.0	3.2	51.8	0.0	13.6	31.4
Spanish_Valencia_Avg	0.02218860	0.0	0.0	0.0	0.0	3.2	52.4	0.0	12.8	31.6
Spanish_Aragon_Avg	0.02783089	0.0	0.0	0.0	0.0	2.8	53.0	0.0	12.8	31.4
Spanish_Navarra_Avg	0.03486921	0.0	0.0	0.0	0.0	2.6	53.4	0.0	13.2	30.8
Spanish_La_Rioja_Avg	0.02560487	0.0	0.0	0.0	0.0	2.0	54.0	0.0	14.2	29.8
Spanish_Pais_Vasco_Avg	0.03973552	0.0	0.0	0.0	0.0	0.2	53.4	0.0	17.6	28.8

Bekas · Feb 12, 2022

I don't want to be a debbie downer but for those of you who trust g25 to extract conclusions maybe you should have a look at the following:

This was posted by the creator of nmonte on the blogspot of eurogenes:

January 23, 2022 at 2:15 AM
Blogger huijbregts said...
I was surprised to find Matt yesterday explaining the place of nMonte in genetic history. I was not aware of this all.
Hopefully David will permit me a few supplementary remarks.
I wrote nMonte as an experiment because I was curious whether a simple random walk algorithm could identify relevant groups.
I was pleasantly surprises when it did. Actually it identified a single set of non-unique samples; next it used the naming labels within this set to infer distances to well known predefined groups.
I am still surprised that the simple trick worked so well.
By then (about 2015) I knew next to nothing about mathematical genetics.
By now I better understand the problems with this kind of algorithms.
In the first place there is the problem of overfitting. The ancients division of Global25 contains some five thousand samples. This permits no more 12 binary choices (because 2^12 = 4096).
And if you select a subset, the number is still smaller. So if you use 25 dimensions, you are are heavily overfitting.
Many guys have tried to repair this by by what they call "scaling" the data, but which is really an anti-scaling and does not solve the problem of too many dimensions. It is much better to truncate the dimensions at a much lower value than 25.
In nMonte3 I have limited the damage of overfitting by applying a penalty on larger distances. Unfortunately I also offered the opportunity to switch off this penalizing by using the option pen=0. In spite of my repeated warning not to use this, if you do not perfectly understand what you are doing, many users interpreted this as an opportunity to prove there expert status

If I were younger, I might try to improve nMonte by using a Bayesian algorithm.
As it is, I incidentally use nMonte as a quick and dirty simple method.
But mostly I am content with visualizing the data with algorithms like UMAP, which I think is underestimated, especially at this forum.

And this is the relevant paper of why you shouldn't trust smartPCA:

https://www.biorxiv.org/content/10.1101/2021.04.11.439381v4.full

Duarte · Feb 12, 2022

Bekas said:
I don't want to be a debbie downer but for those of you who trust g25 to extract conclusions maybe you should have a look at the following:

This was posted by the creator of nmonte on the blogspot of eurogenes:

And this is the relevant paper of why you shouldn't trust smartPCA:

https://www.biorxiv.org/content/10.1101/2021.04.11.439381v4.full

Yes, in fact, all conclusions should be taken with a grain of salt and everything should be seen as pure fun and not as an absolute and indisputable fact.

Duarte · Feb 12, 2022

Regio X said:
@Duarte
Looks better. These last numbers for Iberomaurusian in Portuguese seem more realistic than ~10%, in my opinion.

Model with pre-Neolithic pops mainly, as Iberomaurisians were.

Target Distance AHG CHG CMR_Shum_Laka_8000BP EHG IRN_HotuIIIb_Meso KEN_Early_Pastoral_N Natufian Taforalt WHG
Moroccan_South_Avg 0.05911990 31.6 3.2 22.4 0.0 3.2 4.4 0.0 35.2 0.0
Moroccan_North_Avg 0.03070748 43.6 6.6 5.6 1.2 4.8 0.0 9.0 28.8 0.4
Spanish_Asturias_Avg 0.06501181 58.8 12.0 0.0 15.8 0.0 0.0 0.0 4.0 9.4
Spanish_Castilla_Y_Leon_Avg 0.05381195 58.8 11.6 0.0 17.2 1.0 0.0 0.4 3.8 7.2
Portuguese_Avg 0.04882801 58.4 10.4 0.0 15.4 3.6 0.0 1.6 3.4 7.2
Spanish_Extremadura_Avg 0.04858755 58.4 8.4 0.0 14.0 6.8 0.0 1.0 3.2 8.2
Spanish_Galicia_Avg 0.05045096 58.6 9.2 0.0 16.2 4.2 0.0 1.0 2.8 8.0
Spanish_Andalucia_Avg 0.05066866 58.4 10.0 0.0 13.6 4.6 0.0 2.0 2.4 9.0
Spanish_Murcia_Avg 0.04444479 60.2 9.2 0.0 15.2 3.8 0.0 2.2 1.8 7.6
Spanish_Cantabria_Avg 0.05088297 61.2 8.6 0.0 15.0 4.4 0.0 0.0 1.2 9.6
Spanish_Cataluna_Avg 0.05008250 60.2 10.0 0.0 15.8 3.2 0.0 0.0 1.2 9.6
Spanish_Aragon_Avg 0.05584008 61.8 10.8 0.0 15.4 2.2 0.0 0.0 1.0 8.8
Spanish_Valencia_Avg 0.05103732 60.2 9.6 0.0 15.0 4.0 0.0 1.0 0.8 9.4
Spanish_Castilla_La_Mancha_Avg 0.05247349 60.4 9.8 0.0 15.0 3.6 0.0 2.4 0.4 8.4
Spanish_La_Rioja_Avg 0.05073410 62.6 9.4 0.0 14.0 3.4 0.0 0.0 0.0 10.6
Spanish_Navarra_Avg 0.06100040 61.6 6.8 0.0 15.6 5.2 0.0 1.4 0.0 9.4
Spanish_Pais_Vasco_Avg 0.06779314 61.2 9.0 0.0 15.6 1.2 0.0 0.0 0.0 13.0

The "classic" model, based mainly in Neolithics.

Target Distance CMR_Shum_Laka_8000BP IRN_Ganj_Dareh_N KEN_Pastoral_N Levant_PPNB MAR_EN TUR_Barcin_N TUR_Tepecik_N WHG Yamnaya_Samara
Moroccan_South_Avg 0.05234851 20.2 2.0 9.8 0.0 35.6 28.4 0.0 1.6 2.4
Moroccan_North_Avg 0.01512080 5.2 4.4 2.6 1.6 31.2 33.8 12.2 2.6 6.4
Portuguese_Avg 0.02099203 0.0 0.0 0.0 0.0 6.0 51.2 0.0 10.4 32.4
Spanish_Extremadura_Avg 0.01978206 0.0 0.0 0.0 0.0 6.0 51.0 0.0 10.4 32.6
Spanish_Castilla_Y_Leon_Avg 0.02557971 0.0 0.0 0.0 0.0 5.8 50.4 0.0 11.8 32.0
Spanish_Asturias_Avg 0.03316790 0.0 0.0 0.0 0.0 5.4 51.4 0.0 14.4 28.8
Spanish_Andalucia_Avg 0.02023283 0.0 0.0 0.0 0.0 5.2 52.2 0.0 11.8 30.8
Spanish_Galicia_Avg 0.02232224 0.0 0.0 0.0 0.0 5.2 50.8 0.0 11.4 32.6
Spanish_Murcia_Avg 0.01925924 0.0 0.0 0.0 0.0 4.4 53.4 0.0 11.6 30.6
Spanish_Cantabria_Avg 0.02554839 0.0 0.0 0.0 0.0 3.2 52.6 0.0 13.2 31.0
Spanish_Castilla_La_Mancha_Avg 0.02200687 0.0 0.0 0.0 0.0 3.2 53.4 0.0 11.8 31.6
Spanish_Cataluna_Avg 0.02431932 0.0 0.0 0.0 0.0 3.2 51.8 0.0 13.6 31.4
Spanish_Valencia_Avg 0.02218860 0.0 0.0 0.0 0.0 3.2 52.4 0.0 12.8 31.6
Spanish_Aragon_Avg 0.02783089 0.0 0.0 0.0 0.0 2.8 53.0 0.0 12.8 31.4
Spanish_Navarra_Avg 0.03486921 0.0 0.0 0.0 0.0 2.6 53.4 0.0 13.2 30.8
Spanish_La_Rioja_Avg 0.02560487 0.0 0.0 0.0 0.0 2.0 54.0 0.0 14.2 29.8
Spanish_Pais_Vasco_Avg 0.03973552 0.0 0.0 0.0 0.0 0.2 53.4 0.0 17.6 28.8

Thanks Regio

Palermo Trapani · Feb 12, 2022

Duarte said:
Yes, in fact, all conclusions should be taken with a grain of salt and everything should be seen as pure fun and not as an absolute and indisputable fact.

Duarte: Well said. My take when running these models and looking at results is how well they converge to what is reported in the extant genetic literature. So if there are several studies showing X and one of these calculators can produce results similar to X that align with what is reported in several papers, I take those results as being relatively accurate. So when some of these calculators produce results that are not with what is in the published papers (by that I mean several studies showing the same basic genetic admixture in populations) my default position is what is 1) what is published in the literature and 2) Amateur Calculator results that produce results that most align with the published literature.

As for G25, I can't personally speak to it as I don't have my coordinates for that model to run my own DNA on it to see how it aligns with published papers and what other calculators give me (e.g., Dodecad which works well for me personally)

Duarte · Feb 12, 2022

Palermo Trapani said:
Duarte: Well said. My take when running these models and looking at results is how well they converge to what is reported in the extant genetic literature. So if there are several studies showing X and one of these calculators can produce results similar to X that align with what is reported in several papers, I take those results as being relatively accurate. So when some of these calculators produce results that are not with what is in the published papers (by that I mean several studies showing the same basic genetic admixture in populations) my default position is what is 1) what is published in the literature and 2) Amateur Calculator results that produce results that most align with the published literature.

As for G25, I can't personally speak to it as I don't have my coordinates for that model to run my own DNA on it to see how it aligns with published papers and what other calculators give me (e.g., Dodecad which works well for me personally)

I totally agree with you PT.

Regio X · Feb 13, 2022

Duarte said:
Yes, in fact, all conclusions should be taken with a grain of salt and everything should be seen as pure fun and not as an absolute and indisputable fact.

Agreed. It's mainly for fun, and it should not be taken literally.

In the spirit of Bekas' post, here're the results for Portugal using nMonte3 in R and the default penalty. The results vary in each run, so they're not perfectly reproducible.
1) Portugal_avg (nMonte3, penalty+)
AHG: 61.6
WHG: 10.2
EHG: 8.6
CHG: 8.4
Natufian: 4
Iran Meso: 3.8
Taforalt: 1.8
WSHG: 1.6

2) Portugal_avg (nMonte3, penalty+)
AHG: 61.6
WHG: 10.6
CHG: 9
EHG: 7.8
Iran Meso: 4.2
Natufian: 2.8
WSHG: 1.8
Taforalt: 1.6
KEN_EN: 0.6

3) Portugal_avg (nMonte3, penalty+)
AHG: 61
EHG: 9,8
WHG: 9.8
CHG: 7.4
Iran Meso: 5
Natufian: 3.6
Taforalt: 1.6
WSHG: 1.4
KEN_EN: 0.4

@Bekas
I get what you mean. Unfortunately, we amateurs have few alternatives to play with nowadays.
It's really a pity Dienekes quit.

Duarte · Feb 14, 2022

Regio X said:
Agreed. It's mainly for fun, and it should not be taken literally.

In the spirit of Bekas' post, here're the results for Portugal using nMonte3 in R and the default penalty. The results vary in each run, so they're not perfectly reproducible.
1) Portugal_avg (nMonte3, penalty+)
AHG: 61.6
WHG: 10.2
EHG: 8.6
CHG: 8.4
Natufian: 4
Iran Meso: 3.8
Taforalt: 1.8
WSHG: 1.6

2) Portugal_avg (nMonte3, penalty+)
AHG: 61.6
WHG: 10.6
CHG: 9
EHG: 7.8
Iran Meso: 4.2
Natufian: 2.8
WSHG: 1.8
Taforalt: 1.6
KEN_EN: 0.6

3) Portugal_avg (nMonte3, penalty+)
AHG: 61
EHG: 9,8
WHG: 9.8
CHG: 7.4
Iran Meso: 5
Natufian: 3.6
Taforalt: 1.6
WSHG: 1.4
KEN_EN: 0.4

@Bekas
I get what you mean. Unfortunately, we amateurs have few alternatives to play with nowadays.
It's really a pity Dienekes quit.

Thank you Regio. I was curious about the WSHG - West Siberian Hunter-Gatherer. I could see that they were described by Narasimhan et al 2019 from three individuals. Two of them are in the G25 database (Sosonivoy_HG and Tyumen_HG). I could see that this ancestry is heavy on Native Americans, Saami and some Russian populations.

PS: I couldn’t see this before: The fits of Native American in this model are terrible. This model is not for them.

Regio X · Feb 15, 2022

Duarte said:
Thank you Regio. I was curious about the WSHG - West Siberian Hunter-Gatherer. I could see that they were described by Narasimhan et al 2019 from three individuals. Two of them are in the G25 database (Sosonivoy_HG and Tyumen_HG). I could see that this ancestry is heavy on Native Americans, Saami and some Russian populations.

PS: I couldn’t see this before: The fits of Native American in this model are terrible. This model is not for them.

Thanks.
Indeed. IIRC I used those two samples for WSHG.

These traces of WSHG in Western Europeans could be linked to the "Steppe" ancestry perhaps.

There're some Native American ancient samples that could be used in the model. The fits would get much better.

Duarte · Feb 17, 2022

Regio X said:
Thanks.
Indeed. IIRC I used those two samples for WSHG.

These traces of WSHG in Western Europeans could be linked to the "Steppe" ancestry perhaps.

There're some Native American ancient samples that could be used in the model. The fits would get much better.

Thanks Regio.
This is it. Nice fits for Native American using Paleo- Indian in data source.

AIexSuvorov · Jul 22, 2023

Target: Russki_scaled Distance: 1.6048% / 0.01604773
87.6	Slavic

6.8	Finno-Ugrian

5.6	Pannonian_IA

G25 G25 Central, Eastern and South Eastern Europe Iron Age Calculator

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