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Target: Dorquest_scaled
Distance: 3.0486% / 0.03048593
65.4 Denmark_Jutland_IA.SG(n=42)
22.6 France_SouthEast_IA2.AG(n=5)
10.2 Italy_Imperial.SG(n=36)
1.8 Poland_EarlyMedieval_Slavic.SG(n=45)
Distance to: Dorquest_scaled
0.04187859 Netherlands_Valkenburg_IA.SG(n=19)
0.04474257 Denmark_Jutland_IA.SG(n=42)
0.05046602 Germany_Hallstat_IronAge.AG(n=28)
0.05877693 France_SouthEast_IA2.AG(n=5)
0.08033559 Austria_MigrationPeriod_Pannonian.SG(n=14)
0.08167094 Poland_EarlyMedieval_Slavic.SG(n=45)
0.14403211 Italy_Imperial.SG(n=36)
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Target: Kestrel_scaled
Distance: 2.0577% / 0.02057721
34.4 Germany_Hallstat_IronAge.AG(n=28)
27.6 France_SouthEast_IA2.AG(n=5)
15.4 Denmark_Jutland_IA.SG(n=42)
13.4 Italy_Imperial.SG(n=36)
9.2 Poland_EarlyMedieval_Slavic.SG(n=45)
Distance to: Kestrel_scaled
0.02422706 Germany_Hallstat_IronAge.AG(n=28)
0.03585431 France_SouthEast_IA2.AG(n=5)
0.05467056 Austria_MigrationPeriod_Pannonian.SG(n=14)
0.06174398 Netherlands_Valkenburg_IA.SG(n=19)
0.06798960 Denmark_Jutland_IA.SG(n=42)
0.09369152 Poland_EarlyMedieval_Slavic.SG(n=45)
0.11746869 Italy_Imperial.SG(n=36)
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Try adding this:
Ukraine_IA_WesternScythian.SG,0.116479,0.0741337,0 .0331867,0.0454353,0.0015387,0.0114347,-0.00141,0.0062307,-0.0141123,-0.0132427,0.000974,-0.005295,-0.010307,-0.0090833,0.011627,0.0012817,0.002651,0.00511,-0.0024303,-0.0010423,-0.005116,-0.0051937,0.000534,-0.0057837,-0.0021953
Target: SC_23andMe
Distance: 2.3481% / 0.02348113
51.8 Netherlands_Valkenburg_IA.SG(n=19)
15.4 Denmark_Jutland_IA.SG(n=42)
15.2 Austria_MigrationPeriod_Pannonian.SG(n=14)
9.0 Poland_EarlyMedieval_Slavic.SG(n=45)
8.6 Ukraine_IA_WesternScythian.SG
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I don't know about you, but Vahaduo is just a calculator—it gives the best possible result within the G25 space. It looks for the number that’s closest (in terms of distance). That doesn’t necessarily have to be true, especially with so many samples.
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Target: Ryo_scaled
Distance: 3.3953% / 0.03395281
69.4 Denmark_Jutland_IA.SG(n=42)
20.6 France_SouthEast_IA2.AG(n=5)
10.0 Italy_Imperial.SG(n=36)
Target: G25K13SimRyoHazuki
Distance: 1.1332% / 0.01133153
40.2 Denmark_Jutland_IA.SG(n=42)
23.6 France_SouthEast_IA2.AG(n=5)
20.4 Germany_Hallstat_IronAge.AG(n=28)
11.6 Netherlands_Valkenburg_IA.SG(n=19)
2.8 Italy_Imperial.SG(n=36)
1.4 Poland_EarlyMedieval_Slavic.SG(n=45)
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Target: Nisko
Distance: 1.7699% / 0.01769942
30.2 Denmark_Jutland_IA.SG(n=42)
24.0 Netherlands_Valkenburg_IA.SG(n=19)
16.8 Poland_EarlyMedieval_Slavic.SG(n=45)
13.6 Italy_Imperial.SG(n=36)
10.6 Germany_Hallstat_IronAge.AG(n=28)
4.8 France_SouthEast_IA2.AG(n=5)
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Mixing eras is a very risky and unwise idea.
Target: cass
Distance: 1.1445% / 0.01144546
57.0 Poland_EarlyMedieval_Slavic.SG(n=45)
25.6 Denmark_Jutland_IA.SG(n=42)
12.4 Germany_Hallstat_IronAge.AG(n=28)
5.0 Italy_Imperial.SG(n=36)
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Target: cass
Distance: 1.3652% / 0.01365177
50.8 Denmark_Jutland_PreRoman_IA-Protoslavic?
28.6 Denmark_Jutland_IA.SG(n=42)
20.6 Austria_MigrationPeriod_Pannonian.SG(n=14)
Using a Proto-Slavic (Pomeranian culture?) sample instead of Slavic MA
Denmark_Jutland_PreRoman_IA-Protoslavic?:CGG106486_CGG106491__BC_202__Cov_67.5 0%,0.130897,0.125926,0.084852,0.070737,0.044316,0. 031515,0.013631,0.015461,-0.002045,-0.020593,-0.006008,-0.007343,0.017245,0.027937,-0.007872,-0.006629,-0.010431,0.006334,0.001634,0.001876,-0.009358,-0.004081,0.001232,-0.016147,0.002515
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Target: Mallisharrit
Distance: 2.3574% / 0.02357382
49.2 Italy_Imperial.SG(n=36)
21.4 Austria_MigrationPeriod_Pannonian.SG(n=14)
21.0 Poland_EarlyMedieval_Slavic.SG(n=45)
8.4 Germany_Hallstat_IronAge.AG(n=28)
Distance to: Mallisharrit
0.03521280 Austria_MigrationPeriod_Pannonian.SG(n=14)
0.06778317 Italy_Imperial.SG(n=36)
0.06818939 Germany_Hallstat_IronAge.AG(n=28)
0.07869758 France_SouthEast_IA2.AG(n=5)
0.11002517 Netherlands_Valkenburg_IA.SG(n=19)
0.11748648 Denmark_Jutland_IA.SG(n=42)
0.12319357 Poland_EarlyMedieval_Slavic.SG(n=45)
