2




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| Received: 5,514/44 Given: 1,505/11 |





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| Received: 15,697/315 Given: 8,913/358 |
Target: Daos_mom
Distance: 2.2525% / 2.25247234 | ADC: 0.25x
67.4 South_Polish
21.4 Belorussian
4.8 La_Brana-1
3.2 Yemenite_Jewish
2.8 Southwest_Finnish
0.2 Hungarian
0.2 Karitiana
Target: Daos_mom
Distance: 1.3829% / 1.38288947
66.0 Belorussian
8.2 Ashkenazi
7.6 Southwest_Finnish
6.0 La_Brana-1
5.8 Bulgarian
3.8 Norwegian
2.2 Spanish_Valencia
0.4 Karitiana
DODECAD
Distance to: Daos_mom
2.87706448 Ukrainian
3.53256281 Rus_Smolensk
3.63568425 PL_Mazovia
3.99996250 Rus_Kostroma
5.60406995 Rus_Tver
5.68471635 Southwest_Rus
7.05171610 Sorb_Lusatia
9.71794217 Hungarians
10.27404010 Mixed_Slav
13.68930239 Belorussian
Target: Daos_mom
Distance: 1.5042% / 1.50416989 | ADC: 0.25x
59.8 Ukrainian
19.4 PL_Mazovia
15.6 Mixed_Slav
4.2 Bulgarians
1.0 Dai
Quite strongly Xoxol![]()





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What are her Euro K15 and EUtest results? Maybe they would be accurate. Also MDLP K23b is worth trying (wait until it loads).








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Euro K15
Admix Results (sorted):
# Population Percent
1 North_Sea 26.16
2 Baltic 24.63
3 Eastern_Euro 20.27
4 Atlantic 12.65
5 West_Med 6.32
6 East_Med 4.06
7 West_Asian 3.27
8 Southeast_Asian 0.82
9 Amerindian 0.66
10 Siberian 0.5
11 Red_Sea 0.42
12 Sub-Saharan 0.23
Single Population Sharing:
# Population (source) Distance
1 Ukrainian 4.89
2 Ukrainian_Lviv 5.82
3 South_Polish 6.41
4 Polish 7.44
5 Estonian 8.46
6 Southwest_Russian 9.12
7 Finnish 9.16
8 Ukrainian_Belgorod 9.54
9 Hungarian 9.85
10 Russian_Smolensk 10.04
11 East_Finnish 10.1
12 Belorussian 10.36
13 Croatian 10.42
14 Estonian_Polish 10.62
15 Southwest_Finnish 10.68
16 Kargopol_Russian 10.85
17 Moldavian 10.93
18 East_German 12.14
19 Lithuanian 12.77
20 Erzya 13.18
K23b
Admix Results (sorted):
# Population Percent
1 European_Hunters_Gatherers 48.18
2 Caucasian 29.57
3 European_Early_Farmers 12.05
4 Ancestral_Altaic 4.64
5 Archaic_African 1.14
6 South_East_Asian 1.04
Finished reading population data. 620 populations found.
23 components mode.
--------------------------------
Least-squares method.
Using 1 population approximation:
1 Ukrainian_West_ @ 4.440203
2 Slovak_ @ 5.296364
3 Kashub_ @ 6.277735
4 Ukrainian_Center_ @ 6.588534
5 Belarusian-East_ @ 7.044806
6 Sorb_ @ 7.047407
7 Russian_North_ @ 7.212347
8 Belarusian_West_ @ 7.428010
9 Czech_ @ 7.434169
10 Russian-West_ @ 7.619694
11 Ukrainian_East_ @ 7.622297
12 Russian_South_ @ 7.710407
13 German_ @ 7.904573
14 Russian_Meshtchyora_ @ 7.906970
15 Russian-Upper-Volga_ @ 8.642891
16 Russian-North-West_ @ 9.009881
17 Croat_BH_ @ 9.238192
18 Hungarian_ @ 9.244235
19 Slovenian_ @ 9.248827
20 Ukrainian_ @ 9.256211
Using 2 populations approximation:
1 50% Balt_ +50% Serb_Serbia_ @ 3.930012
Using 3 populations approximation:
1 50% Belarusian-East_ +25% Russian-West_ +25% Serb_Serbia_ @ 3.635014





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Why no oracles?![]()





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Eu K15 is quite poor as is often the case
Target: Daos_mom
Distance: 3.6065% / 3.60651381
51.8 Ukrainian
23.0 Erzya
17.6 West_Norwegian
5.2 Estonian
1.2 Lebanese_Druze
1.2 Yemenite_Jewish








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Updated with Oracles.





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MDLP is pretty much spot on. I told you it would load if you wait for a few seconds. As you probably know, the four pop mode gives somewhat bigger distances than mixed mode.
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