A new Uzbek average for K13 to replace the legacy one
Code:Uzbek,8.55,11.84,2.11,23.96,8.12,0.77,9.98,13.84,18.76,1.66,0.15,0.09,0.17
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A new Uzbek average for K13 to replace the legacy one
Code:Uzbek,8.55,11.84,2.11,23.96,8.12,0.77,9.98,13.84,18.76,1.66,0.15,0.09,0.17
This new average is significantly less East Eurasian and has more steppe. How many samples does it contain?Quote:
Originally Posted by Leto
15, from a well-known academic source. No need to question my competence in this regard.Quote:
Originally Posted by CommonSense
I'm not questioning your competence, it was just curiosity. Usually updates to a population average don't end up changing it so significantly.Quote:
Originally Posted by Leto
That old average is of completely unknown origin with an unknown sample size. Possibly half the number I used. All of them were undoubtedly Central Asian, I wouldn't have included blatantly mixed individuals like half Russian or Korean.Quote:
Originally Posted by CommonSense
Lucas, please replace these averages. I updated /added these a while back but they got nuked when you replaced the spreadsheet with an older version.
And add theseCode:Bashkir,0.0888769,-0.1176745,0.0640005,0.0304428,-0.0401099,-0.0040439,0.0087149,0.0110764,-0.0073629,-0.0195981,0.0027403,-0.0034532,0.0093099,-0.0203797,-0.0038962,-0.003486,-0.003955,-0.0009132,-0.0026606,-0.0026784,-0.0097225,0.0015869,-0.0018385,0.0015062,-0.0023102
Buryat,0.0433518,-0.3658114,0.0778508,-0.0272163,-0.0680259,-0.0389598,0.0184127,0.0260056,0.007265,0.0131052,-0.0217812,0.0015247,-0.0021394,0.0056605,0.0049744,0.0040527,-0.0003912,-0.0019334,0.0055307,0.0166982,-0.0208002,-0.0098546,-0.0233207,-0.0021322,0.0001823
Code:Iraqi_Arab,0.0407233,0.1170114,-0.0605489,-0.0604189,-0.0272698,-0.0185153,-0.0044651,-0.0036023,0.0064198,-0.005376,0.0054671,-0.0103658,0.0205731,-0.0005887,0.0016137,0.0116457,-0.0084388,0.0027942,0.0011103,0.0016535,0.0032236,0.0024524,-0.0030949,0.0009371,-0.0013505
Syrian_Kurd,0.0942835188567,0.1067998546933,-0.05084851017,-0.0347763402886,-0.035647840463,-0.007855334905,0.0013708336075,-0.0060381678743,-0.0216453376624,-0.01251366917,-0.000108333355,-0.001773333688,0.0031713339676,-0.0035555007111,-0.0020131670694,0.0117561690179,0.00319466731,0.0007180001436,0.0038968341127,-0.0101508353635,0.0007486668164,-0.003421167351,-0.00061633345,-0.0016065003,0.0036921674051
Syrian_West,0.0786518,0.13293275,-0.0495347,-0.0658597,-0.01586445,-0.02165585,-0.00254975,-0.0043382,-0.00287355,0.002287,0.00376745,-0.00451855,0.0097074,-0.00197495,-0.0040784,0.00872445,0.0014474,0.0010262,0.0015084,-0.00095665,-0.0008485,0.00055635,-0.0021692,0.00116285,0.00046695
Syrian_East,0.038808199287,0.11673750231,-0.052150281183,-0.065753505675,-0.018538171938,-0.021195740709,-0.00324523485,-0.00376909147,0.008492562936,-0.005041804482,0.004894758,-0.00964856178,0.018320553108,0.00030814255,-0.00004528567,0.011169084069,-0.0049731856,0.001351331982,0.00210095029,0.003346758559,0.002602521207,0.00478713807,-0.002300569128,0.002633711652,-0.00089518958
The Eastern Syrian sample is heavily black.Quote:
Originally Posted by Dr_Maul
Target: Syrian_East
Distance: 1.8507% / 0.01850742
73.4 Levant_Megiddo_MLBA
9.6 KAZ_Aktogai_MLBA
7.4 KEN_Nyarindi_3500BP
5.4 IRN_Tepe_Hissar_C
2.2 IRN_Shahr_I_Sokhta_BA2
2.0 MNG_Ulaanzuukh_Slab_Grave
Target: Syrian_West
Distance: 1.0579% / 0.01057902
55.6 Levant_Megiddo_MLBA
21.0 TUR_Kaman-Kalehoyuk_MLBA
11.6 KAZ_Aktogai_MLBA
9.0 IRN_Tepe_Hissar_C
2.2 KEN_Nyarindi_3500BP
0.6 MNG_Ulaanzuukh_Slab_Grave
And the Syrian Kurd one has substantial Steppe
Target: Syrian_Kurd
Distance: 1.3307% / 0.01330744
30.4 IRN_Tepe_Hissar_C
25.0 Levant_Megiddo_MLBA
23.4 TUR_Kaman-Kalehoyuk_MLBA
17.6 KAZ_Aktogai_MLBA
2.2 MNG_Ulaanzuukh_Slab_Grave
1.0 RUS_Yakutia_Ymyiakhtakh_LN
0.4 IRN_Shahr_I_Sokhta_BA2
I’m sorry but this is fucking hilarious. One of the “wise men” from Anthrogenica who collected that data consistently harassed me and another female STEM student and would gossip about “how retarded” we were, and told me that G25 was not a reliable source, yet he’s going on and sending requests for hundreds of coordinates. And it’s funny because this dataset literally shows where the vast majority of Italians plot on a PCA but the dumbfuck literally included 4 Peruvian outliers in his new Apulian average. Who’s the retarded one now, 23abc? ;)Quote:
Originally Posted by Lucas
For K13 and K12b Ancient
Code:KAZ_Aktogai_MLBA,41.77,30.72,0.67,18.92,0,0,3.64,0,0.7,2.58,0.34,0.13,0.52
Image:cool:Code:KAZ_Aktogai_MLBA,18.03,1.74,0,0,22.66,50.53,0.07,0.32,0,0,6.16,0.48
Does anybody have Moksha results in K13?
Is anyone planning to make average for different Arabian countries or regions? It would be interesting to see how different they actually are from Levantines.
Most of the Arabian peninsula is relatively homogenous, especially inner Bedouins and whatnot. From what I have seen the distinction comes from historically city-bound individuals especially in the Gulf and Yemen where we see African, South Asian or Iranian ancestryQuote:
Originally Posted by CommonSense
Why only 4 of Krakauer Berg samples are added to Vahaduo?:
Code:DEU_Krakauer_Berg_MA:KRA001,0.129758,0.125926,0.075424,0.072029,0.046778,0.026774,0.011986,0.010384,-0.001636,-0.021322,-0.003085,-0.006294,0.008028,0.021194,-0.013843,0.013789,0.019036,-0.005701,0.00352,0.005378,0.004991,-0.008408,0.000986,-0.006145,0.001796
DEU_Krakauer_Berg_MA:KRA002,0.126344,0.129988,0.067127,0.059109,0.03693,0.019243,0.007755,0.010615,0.001227,-0.023508,-0.001949,-0.008842,0.012339,0.014313,0.000136,0.009149,0.007823,-0.007728,0.002263,0.006128,-0.003369,-0.005935,0.00419,-0.002048,-0.008502
DEU_Krakauer_Berg_MA:KRA003,0.127482,0.121864,0.07995,0.072675,0.052317,0.013108,0.008695,0.012461,0.004704,-0.023144,-0.00341,-0.005695,0.016204,0.007019,-0.005836,0.021745,0.020861,-0.001267,0.00176,0.002501,-0.008984,-0.005193,0.005546,0.00976,0.005748
DEU_Krakauer_Berg_MA:KRA004,0.12862,0.131003,0.082967,0.075259,0.048624,0.025937,0.00752,0.011999,0.002863,-0.019135,0.002111,-0.008692,0.020218,0.021607,-0.0095,0.009546,0.007953,-0.0019,0.005531,0.008504,-0.011355,0.005688,0.005916,-0.01699,-0.004191
DEU_Krakauer_Berg_MA:KRA005,0.120652,0.137096,0.071276,0.071706,0.049548,0.01004,0.01081,0.014538,-0.009408,-0.018041,-0.00341,-0.001499,0.003419,0.018717,0.00285,-0.004773,0.003129,-0.002154,0.005154,0.004502,-0.009858,-0.004946,0.008381,-0.007591,0.001796
DEU_Krakauer_Berg_MA:KRA006,0.130897,0.125926,0.062979,0.063308,0.040623,0.019801,0.00329,0.013846,0.001227,-0.020046,-0.00065,-0.01079,0.016353,0.026148,-0.015065,-0.01538,-0.002738,-0.003547,0.005405,-0.007379,0.000624,0.003462,0.00493,-0.006627,-0.001078
DEU_Krakauer_Berg_MA:KRA007,0.129758,0.133034,0.082967,0.070737,0.049548,0.026216,0.005405,0.011769,-0.002659,-0.036447,0.003735,-0.01124,0.018285,0.023946,-0.009365,-0.014452,-0.002738,0.001014,-0.001131,0.010755,0.000374,0.001237,-0.001972,-0.009158,0.012214
DEU_Krakauer_Berg_MA:KRA008,0.132035,0.135065,0.076555,0.06137,0.043085,0.025937,0.00564,0.007384,0.002045,-0.02041,-0.010555,-0.005995,0.014569,0.004129,-0.012758,0.001856,0.022035,-0.000633,0.005531,0.002501,-0.00025,-0.002349,-0.001849,-0.006748,0.001078
DEU_Krakauer_Berg_MA:KRA010,0.129758,0.123895,0.065996,0.065246,0.042777,0.025937,0.007755,0.009461,-0.005113,-0.018588,-0.002273,-0.009442,0.013528,0.021469,-0.00665,-0.012331,-0.009648,-0.007221,0.006662,-0.007504,-0.000499,0.000866,0.007518,-0.003253,-0.000958
DEU_Krakauer_Berg_MA:KRA011,0.125205,0.129988,0.078818,0.072675,0.047701,0.027889,0.013161,0.006692,0.005522,-0.020593,-0.00065,-0.009292,0.018583,0.027249,-0.011672,-0.010342,-0.006389,0.00266,0.008045,0.002876,-0.011729,-0.008037,0.007272,-0.003494,0.003952
Could you update Polish k13:
Code:Poland_Lemko,27.74,37.63,14.89,7.34,9.48,0.24,0.42,0.58,0.56,0.60,0.52,0.00,0.00
Polish_Greater Poland,31.45,43.92,10.26,5.30,5.52,0.80,0.87,0.09,0.23,0.65,0.48,0.37,0.06
Polish_Kielce,29.3,45.17,10.56,5.45,5.36,0.76,1.36,0.15,0.37,0.81,0.4,0.28,0.03
Polish_Kujawy,31.83,45.41,9.95,4.66,3.33,1.47,1.02,0.20,0.79,0.93,0.00,0.41,0.00
Polish_Lesser_Poland,31.00,43.23,11.15,5.26,5.63,0.55,0.47,0.06,0.80,0.85,0.57,0.29,0.16
Polish_Mazovia,28.33,46.20,10.70,5.60,5.04,0.54,1.20,0.15,0.69,0.66,0.50,0.18,0.20
Polish_North_Wielkopolska,31.98,43.23,10.06,5.79,5.57,0.87,0.73,0.17,0.19,1.00,0.03,0.35,0.03
Polish_Podlaskie,29.87,46.68,7.30,4.42,6.83,1.65,1.33,0.00,1.06,0.35,0.52,0.00,0.00
Polish_Silesia,29.25,43.03,12.16,6.16,5.57,0.39,1.25,0.29,0.64,0.70,0.42,0.16,0.00
Polish_Southeast,28.71,42.67,11.10,6.04,7.21,1.18,0.44,0.11,1.70,0.23,0.12,0.35,0.13
Polish_Staropolska,29.08,46.18,10.22,4.40,6.59,0.77,0.73,0.00,0.45,0.75,0.37,0.46,0.00
Polish_WarmiaMasuria,32.51,44.26,10.88,4.19,3.27,0.95,1.21,0.16,1.06,0.51,0.33,0.29,0.39
I think only Yemen is overwhelmingly local whereas the oil producing states are up to 80% non-citizen. But Yemen will be extremely far from the Levant, 'cause it's heavily black.Quote:
Originally Posted by CommonSense
In general Dodecad Vahaduo has a lot more West Asian/Middle Eastern pops than K13.
OK, thanks for the info.Quote:
Originally Posted by Leto
And while you're here I want to ask you about the Baltic (Lithuanian and Latvian) averages. On K13, all we have are those averages from the original spreadsheet. Is anyone working on adding new ones, perhaps with regions included?
The Latvian is not from the original, someone added it back when this Vahaduo thing began. I can't possibly do that myself, those are very small countries anyway, do we actually need 3-5 regional averages for each of them? I did LT and LV for Dodecad (15-20 samples each) and they're good enough IMO. That's my main calculator, K13 comes only second.Quote:
Originally Posted by CommonSense
Overall Gedmatch keeps losing popularity, soon my "expertise" will be for naught :ohwell:
Lucas, I sent you this weeks ago and you haven't added it yet - an updated Dutch avg for D K12b:
Code:Dutch,7.40,0.19,0.03,0.12,37.25,44.28,0.57,0.27,0.54,0.02,9.09,0.25
addedQuote:
Originally Posted by Dr_Maul
addedQuote:
Originally Posted by Kaazi
addedQuote:
Originally Posted by Leto
Distance to: PolishQuote:
Originally Posted by vbnetkhio
1.85121582 Polish_Kujawy
2.13494731 Polish_Kielce
2.65977443 Polish_GreaterPoland
2.76150321 Polish_Mazovia
2.95392959 Polish_WarmiaMasuria
3.27172737 Polish_Lesser_Poland
3.38942473 Polish_North_Wielkopolska
3.45464904 Polish_Staropolska
3.94474334 Polish_Silesia
4.26261657 Russian_Smolensk
4.69146033 South_Polish
4.85679936 Polish_Podlaskie
4.86716550 Ukrainian
4.95362494 Polish_Silesia
5.14665911 Polish_Southeast
5.48327457 Belorussian
5.63055947 Belarusian_Minsk
5.85506618 Sorb_Lusatia
6.35389644 Russian_Southwest
6.91896669 Russian_average
7.75010968 Ukrainian_Galicia
8.30082526 Moldova_Ukrainian
8.76454220 Estonian
9.14512438 Russian_Kostroma
9.58539514 Lithuanian
Distances seem very good to the national average. Would you also update the national average for Poland now that you have additional regions? Should South_Polish be kept when there is also Polish_Southwest? As can be seen repeatedly, Poles are really different from fellow West Slav speaking nations.
Please update my current averages for Eurogenes K13..exactly one year has passed since my last update.
Code:Romania_Moldavia_North,24.89,30.80,15.19,9.09,14.27,1.69,0.84,0.56,1.37,0.53,0.47,0.17,0.13
Romania_Moldavia_South,24.02,26.72,16.79,9.78,17.00,2.06,0.64,0.58,1.14,0.64,0.37,0.10,0.16
Romania_Muntenia,22.61,24.55,17.51,11.08,18.76,2.11,0.62,0.62,1.03,0.54,0.35,0.12,0.09
Romania_Oltenia,23.41,24.91,18.15,10.55,18.10,1.83,0.51,0.71,0.87,0.38,0.37,0.08,0.12
Romania_Dobruja,22.26,25.09,17.69,10.81,18.50,2.16,0.71,0.71,1.15,0.45,0.30,0.06,0.10
Romania_Wallachia,22.69,24.74,17.64,10.95,18.58,2.07,0.62,0.65,1.01,0.49,0.35,0.11,0.10
Romania_Transylvania,24.22,26.32,17.35,9.92,17.02,1.80,0.57,0.56,1.10,0.59,0.38,0.09,0.10
Romania_Maramures,26.03,28.85,16.08,9.29,14.55,1.83,0.84,0.74,0.77,0.46,0.42,0.07,0.06
Romania_Crisana,25.14,27.30,16.89,9.51,16.54,1.32,0.69,0.43,0.91,0.60,0.44,0.12,0.10
Romania_Banat,23.88,25.79,17.43,10.47,17.42,1.87,0.49,0.57,1.19,0.45,0.26,0.11,0.06
Romania_average,23.71,26.24,17.13,10.25,17.33,1.90,0.64,0.60,1.07,0.54,0.38,0.11,0.10
For Euro K13
The Udmurts seem to have the most Iranic type admixture as it is evident in their relatively high West_Asian and South_Asian scores. Though their Y DNA is not very Aryanic.Code:Komi,22.39,43.60,3.11,8.46,0.17,0.31,2.39,0.57,15.43,2.56,0.25,0.21,0.54
Sámi_Finland,23.07,47.80,0.02,2.11,0,1.50,0,0.85,21.77,2.22,0.67,0,0
Udmurt,18.51,36.69,0.51,12.56,0.01,0.17,4.09,0.51,23.10,2.89,0.57,0.12,0.29
Apparently these are now individually labelled as English or Scottish, and from Kent/Cornwall/Argyll/Orkney.Quote:
Originally Posted by Creoda
https://anthrogenica.com/showthread....samples/page14
Anyone able to convert them into K13/K15?
I think they are refs for North Sea / Atlantic and will have 100%. Similar like in K36.Quote:
Originally Posted by Creoda
Cornwall is already in original oracle?
Weird how they got that much West Asian, but without East Med. People from the Caucasus and Iranics, usually carry some Med.Quote:
Originally Posted by Leto
Med tends to be lower in Russia than West Asian. By Iranic I didn't mean the Iranians but the ancient Steppe herders.Quote:
Originally Posted by Ion Basescul
It's definitely Yamnaya admixture.Quote:
Originally Posted by Ion Basescul
So the Southwest English average in the old oracle is actually these Cornish samples? I asked that once but nobody answered. I feel like some of the Kent samples must have been missing from the old SE English average, as it's too Western/Celtic shifted.Quote:
Originally Posted by Lucas
I think it can be deleted, it's probably just one sample and not a real average.Quote:
Originally Posted by Dunai
I don't think so, Davidski collected many Polish samples years ago when he posted as Polako on ABF forum. Probably he made his Eurogenes Polish references based on those.Quote:
Originally Posted by vbnetkhio
I get nicely modeled with updated averages:
Target: Stearsolina
Distance: 3.9296% / 3.92961215 | R2P
72.0 Poland_Lemko
28.0 Swiss_French
Target: Stearsolina
Distance: 1.3183% / 1.31834580
59.8 Poland_Lemko
16.6 South_Polish
9.3 French_Basque
9.0 Abhkasian
5.3 Norwegian
Yep, they should be added to the spreadsheet.
well it's hard to know, but isn't it redundant now that we have more specific Southern Polish averages?Quote:
Originally Posted by Tomenable
The extra West_Asian might also account for the excess steppe ancestry in Udmurts. Let's suppose that Udmurts are 75% West Eurasian but 50% steppe, and steppe is considered 100% West Eurasian, so then 66.7% of the West Eurasian ancestry of Udmurts is steppe. But then neither the North_Atlantic or Baltic component has enough steppe for Udmurts.Quote:
Originally Posted by Leto
I think that in K15, the Eastern_Euro component accounts for some of the extra steppe/Iranian/Caucasian ancestry in the VUR, because in K15, Chuvashes have 3.4% West_Asian and Maris have 1.4%:
But in K13, Chuvashes have 8.7% West_Asian and Maris have 6.3%:Code:North_Sea Atlantic Baltic Eastern_Euro West_Med West_Asian East_Med Red_Sea South_Asian Southeast_Asian Siberian Amerindian Oceanian Northeast_African Sub-Saharan
Chuvash 13.4 5.8 13.5 36.2 0.9 3.4 0.9 0.5 2.0 2.5 17.7 2.4 0.4 0.2 0.3
Erzya 16.8 10.2 27.7 29.1 2.7 3.6 1.1 0.3 1.2 0.5 5.1 1.2 0.0 0.1 0.1
Finnish 29.4 17.4 22.0 18.8 2.5 1.1 0.4 0.1 0.6 0.9 5.3 0.9 0.5 0.1 0.1
Mari 11.4 4.8 11.4 38.4 0.2 1.4 0.2 0.1 3.9 0.8 23.8 2.8 0.3 0.1 0.5
In K15, the Eastern_Euro component is actually closer to the North_Sea and Atlantic components than to the Baltic component:Code:North_Atlantic Baltic West_Med West_Asian East_Med Red_Sea South_Asian East_Asian Siberian Amerindian Oceanian Northeast_African Sub-Saharan
Chuvash 14.9 43.1 2.0 8.7 1.3 0.8 2.3 2.7 20.1 2.8 0.4 0.6 0.4
Finnish 34.2 47.7 4.4 2.2 0.6 0.4 0.5 1.0 6.5 0.9 0.8 0.5 0.3
Komi 22.4 43.6 3.1 8.5 0.2 0.3 2.4 0.6 15.4 2.6 0.2 0.2 0.5
Mari 13.2 42.2 1.2 6.3 0.6 0.4 4.4 0.9 26.3 3.3 0.4 0.2 0.7
Mordovian 22.5 47.7 6.9 7.7 3.5 0.7 1.6 1.0 6.1 1.3 0.5 0.2 0.2
Sámi_Finland 23.1 47.8 0.0 2.1 0.0 1.5 0.0 0.8 21.8 2.2 0.7 0.0 0.0
Udmurt 18.5 36.7 0.5 12.6 0.0 0.2 4.1 0.5 23.1 2.9 0.6 0.1 0.3
FST distance to Eastern_Euro:
0.000 Eastern_Euro
0.020 North_Sea
0.022 Atlantic
0.024 Baltic
0.031 West_Asian
0.032 East_Med
0.038 West_Med
0.056 South_Asian
0.058 Middle_Eastern
0.100 Siberian
0.102 Southeast_Asian
0.108 Northeast_African
0.128 Amerindian
0.142 Sub-Saharan
0.173 Oceanian
In K15, Maris are also closer to the North_Sea and Atlantic components than to the Baltic component:
Also in this MDS plot of the Eurasian components in K15, Eastern_Euro plots further south than Baltic:Code:> t=read.csv("ta/sheet/k15orig",r=1)
> fst=as.matrix(as.dist(read.csv("ta/sheet/k15fst",r=1)))
> mult=as.matrix(t)%*%as.matrix(fst)
> s=sort(mult["Mari",])
> writeLines(paste(sprintf("%.3f",s),names(s)))
3.839 Eastern_Euro
4.607 North_Sea
4.869 Atlantic
4.907 Baltic
5.448 West_Asian
5.556 East_Med
6.344 West_Med
6.457 South_Asian
7.908 Middle_Eastern
7.974 Siberian
9.341 Southeast_Asian
11.905 Northeast_African
12.317 Amerindian
15.075 Sub-Saharan
17.593 Oceanian
https://i.ibb.co/XyJqdzm/k15mds.png
with myheritage raw data I am closest to Lemko, who are white Croat-Vlach mix :thumbsup
Distance to: Stearsolina
3.88328469 Poland_Lemko
4.43407262 Croat_East
4.48306815 Bosniak_Bosnia
4.58758106 Croat
4.64383462 Croat_North
4.86671347 Hungarian_Alföld
5.52196523 Ukrainian_Carpathian
5.58499776 Moldova_North
5.62725510 Hungarian
5.68233227 Slovenian
5.71636248 Hungarian_North
6.01780691 Hungarian_Transdanubia+Budapest
6.12248316 Croat_South
6.23436444 Croat_West
6.46706270 Bosniak
6.47602502 Slovak
7.03102411 Ukrainian_Galicia
7.04628271 Csángó-Ceangău
7.23221266 Serb_Bosnia
8.14194080 Moldova_Centre
8.30960890 Moldova_average
8.36513000 Romania_Moldavia_North
8.39834508 Hungarian_Transylvania+Székely
8.51442306 Moldova_Ukrainian
8.55248502 Serb_Croatia
Target: Stearsolina
Distance: 2.2453% / 2.24532838 | R2P
94.3 Poland_Lemko
5.7 Ossetian
A stunning steep cline in distances (with the updated Polish K13):
Distance to: rothaer
4.88755563 German_East
6.75366567 Czech
8.30845954 Sorb_Lusatia
9.43970868 Slovak
9.66557810 Austrian
9.68982456 North-Swedish
9.71481858 Southwest_Finnish
9.77789343 Polish_WarmiaMasuria
9.88799778 Sweden_Svealand_East
10.10652759 Polish_North_Wielkopolska
10.41147924 South_Polish
10.48307684 Polish_Lesser_Poland
10.50438480 Slovenian
10.75786689 Polish_GreaterPoland
11.08615353 Hungarian_North
11.23210132 Polish_Kujawy
11.32514901 Hungarian_Transdanubia+Budapest
11.50077389 German
11.76300557 Polish_Silesia
11.78775636 Croat_North
12.14483429 Hungarian
12.15276923 Swedish
12.21082716 Polish
12.24309193 Ukrainian_Galicia
"9.77789343 Polish_Masuria
9.77789343 Polish_WarmiaMasuria"
^^^
Duplicates.
Thanks for the long-ass post. I just don't use K15 much, it's usually worse than K13, maybe for Northwestern Europeans it's just as good or even better.Quote:
Originally Posted by Komintasavalta
What do we know about the Udmurts? Why would they have more Steppe ancestry than the others in the region? Their Y DNA is homogeneous, 70% N1a or whatever it's called now.
I don't know if Udmurts have that much steppe in absolute terms, but for example in the qpGraph model in Tambets et al. 2018, Udmurts had 30% Nganasan, 63% Corded Ware, 1% LBK, and 6% EHG, so the proportion of Corded Ware in their non-Nganasan ancestry was around 90%. The proportion of Corded Ware was 62% in Central Russians and 61% in Mordovians, but both obviously had lower Nganasan.Quote:
Originally Posted by Leto
Also in the G25 model below, out of the ancestry of Udmurts that is not from Krasnoyarsk_BA, about 82% is from Yamnaya (but the model doesn't have an EHG source, and maybe Udmurts have extra EHG that is not from Yamnaya):
Target: Udmurt
Sources: GEO_CHG IRN_Ganj_Dareh_N RUS_Krasnoyarsk_BA TUR_Barcin_N Yamnaya_RUS_Samara
Distance: 0.045
62% Yamnaya_RUS_Samara
24% RUS_Krasnoyarsk_BA
14% TUR_Barcin_N