#444286

Anonymous

Just got my mom’s results from 23 and Me. Her DNA run through a few Gedmatch calculators:

MDLP K16 Modern – 

#PopulationPercent
1NorthEastEuropean29.18
2Neolithic26.20
3Caucasian24.85
4Steppe19.08

Finished reading population data. 517 populations found.
16 components mode.


Least-squares method.

Using 1 population approximation:
1 Hungarian_Hungary @ 3.254623
2 Hungarian_Budapest @ 3.940319
3 Slovak_Slovakia @ 4.033525
4 Pole_EastPoland @ 4.509163
5 German_Lipsian_(Saxony) @ 4.520008
6 Croat_Croatia @ 4.527967
7 Slovenian_Slovenia @ 4.726914
8 Pole_Wroclaw @ 5.010838
9 Czech_Czechia @ 5.243520
10 Sorb_Lusatia @ 5.270284
11 Ukrainian_Ukraine @ 5.534884
12 Pole_WestPoland @ 5.556050
13 Ukrainians_west_WestUkraine @ 5.760574
14 Croat_Bosnia-Herzegovina @ 6.057488
15 Dutch_Netherlands @ 6.142982
16 Bosnian_Bosnia-Herzegovina @ 6.149072
17 Serbian_Bosnia-Herzegovina @ 6.345817
18 German_Germany @ 6.641535
19 German_SouthGermany @ 6.943242
20 Cossack_Zaporozhie @ 6.949210

Using 2 populations approximation:
1 50% German_Lipsian_(Saxony) +50% Hungarian_Budapest @ 2.883641

Using 3 populations approximation:
1 50% Belarusian_Belarus +25% Bulgarian_Bulgaria +25% German_Germany @ 2.636602

Using 4 populations approximation:
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
1 Bulgarian_Bulgaria + German_Germany + Lithuanian_Lithuania + Pole_EastPoland @ 2.461924
2 Bulgarian_Bulgaria + German_Germany + Lithuanian_Lithuania + Sorb_Lusatia @ 2.542519
3 Bulgarian_Bulgaria + German_Germany + Lithuanian_Lithuania + Pole_WestPoland @ 2.543197
4 Bulgarian_Bulgaria + German_Germany + Lithuanian_Lithuania + Slovak_Slovakia @ 2.581973
5 German_Germany + Hungarian_Budapest + Lithuanian_Lithuania + Serbian_Serbia @ 2.593828
6 Bulgarian_Bulgaria + German_Germany + Hungarian_Hungary + Lithuanian_Lithuania @ 2.619565
7 German_Germany + Hungarian_Budapest + Hungarian_Budapest + Pole_EastPoland @ 2.621728
8 Belarusian_Belarus + Bulgarian_Bulgaria + German_Germany + Pole_WestPoland @ 2.623447
9 Belarusian_Belarus + German_Germany + Hungarian_Budapest + Serbian_Bosnia-Herzegovina @ 2.632957
10 Belarusian_Belarus + Belarusian_Belarus + Bulgarian_Bulgaria + German_Germany @ 2.636602
11 Belarusian_Belarus + Bulgarian_Bulgaria + German_Germany + Sorb_Lusatia @ 2.657141
12 Bulgarian_Bulgaria + German_Lipsian_(Saxony) + German_Germany + Lithuanian_Lithuania @ 2.670877
13 Bulgarian_Bulgaria + German_Germany + Lithuanian_Lithuania + Ukrainian_Ukraine @ 2.679160
14 Bulgarian_Bulgaria + German_Germany + Lithuanian_Lithuania + Pole_Wroclaw @ 2.688608
15 Bulgarian_Bulgaria + German_Germany + Hungarian_Budapest + Lithuanian_Lithuania @ 2.689154
16 Belarusian_Belarus + Belarusian_Zhytkavichy_Homel + Bulgarian_Bulgaria + German_Germany @ 2.692001
17 German_Germany + Hungarian_Budapest + Lithuanian_Lithuania + Macedonian_Macedonia @ 2.696229
18 Belarusian_Belarus + Bulgarian_Bulgaria + German_Germany + Pole_EastPoland @ 2.699082
19 German_Germany + Hungarian_Budapest + Hungarian_Budapest + Pole_WestPoland @ 2.707211
20 Belarusian_Belarus + Croat_Croatia + German_Germany + Hungarian_Budapest @ 2.710641

puntDNAL K15-

#PopulationPercent
1NE_European60.08
2Mediterranean28.96
3Caucasian6.32
4SW_Asian1.88
5Oceanian1.61

Finished reading population data. 157 populations found.
15 components mode.


Least-squares method.

Using 1 population approximation:
1 Norwegian @ 2.395719
2 Scottish @ 3.259484
3 North_German @ 3.894126
4 Swedish @ 3.902694
5 Orcadian @ 4.403058
6 English @ 4.856182
7 Irish @ 5.869881
8 Austrian @ 6.997369
9 Slovenian @ 7.318913
10 Polish @ 7.556068
11 Hungarian @ 8.465282
12 Utahn_White @ 8.481057
13 South_German @ 9.287176
14 Croatian @ 10.507570
15 French @ 12.812986
16 Belarusian @ 14.747437
17 Russian @ 15.141205
18 Serbian @ 15.176813
19 Mordovian @ 15.306679
20 Karelian @ 16.164349

Using 2 populations approximation:
1 50% Norwegian +50% Norwegian @ 2.395719

Using 3 populations approximation:
1 50% Lithuanian +25% South_German +25% Basque @ 1.948970

Using 4 populations approximation:
++++++++++++++++++++++++++++++++++++++++
1 Lithuanian + Lithuanian + South_German + Basque @ 1.948970
2 Lithuanian + Lithuanian + Utahn_White + Basque @ 1.990598
3 Lithuanian + Belarusian + Irish + Basque @ 1.993109
4 Lithuanian + Belarusian + English + Basque @ 2.015485
5 Lithuanian + Polish + Swedish + Basque @ 2.029220
6 Lithuanian + Belarusian + Scottish + Basque @ 2.032162
7 Belarusian + Polish + Polish + Basque @ 2.044300
8 Lithuanian + Belarusian + Orcadian + Basque @ 2.088394
9 Belarusian + Belarusian + Scottish + Basque @ 2.096753
10 Lithuanian + Belarusian + North_German + Basque @ 2.129710
11 Lithuanian + Polish + North_German + Basque @ 2.142991
12 Belarusian + Belarusian + North_German + Basque @ 2.148122
13 Lithuanian + Polish + Norwegian + Basque @ 2.165959
14 Lithuanian + Belarusian + Utahn_White + Basque @ 2.171517
15 Lithuanian + Lithuanian + French + Basque @ 2.207957
16 Belarusian + Belarusian + Norwegian + Basque @ 2.227334
17 Lithuanian + Swedish + Swedish + Basque @ 2.232596
18 Belarusian + Polish + Swedish + Basque @ 2.245929
19 Lithuanian + Belarusian + South_German + Basque @ 2.279269
20 Belarusian + Belarusian + Swedish + Basque @ 2.286893

Eurogenes K36 – 

Population  
Amerindian–    
Arabian–    
Armenian0.57
Basque0.84
Central_African–    
Central_Euro2.97
East_African–    
East_Asian–    
East_Balkan6.21
East_Central_Asian–    
East_Central_Euro14.00
East_Med–    
Eastern_Euro4.08
Fennoscandian6.02
French7.97
Iberian7.06
Indo-Chinese–    
Italian14.91
Malayan–    
Near_Eastern–    
North_African–    
North_Atlantic14.43
North_Caucasian1.46
North_Sea18.64
Northeast_African–    
Oceanian0.24
Omotic–    
Pygmy–    
Siberian–    
South_Asian–    
South_Central_Asian–    
South_Chinese–    
Volga-Ural0.60
West_African–    
West_Caucasian–    
West_Med–    

 

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