Does anyone know why this happens? (Vahaduo)

Ack

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I was trying to model some populations and this happened:


Target: Irish
Distance: 4.9374% / 0.04937387
49.8 Yamnaya_RUS_Samara
36.4 Anatolia_Barcin_N
13.8 WHG


Target: Polish:polish16
Distance: 4.6207% / 0.04620698
37.2 Anatolia_Barcin_N
28.6 Yamnaya_RUS_Samara
24.4 RUS_Karelia_HG
9.8 WHG


Target: Estonian
Distance: 6.4167% / 0.06416713
32.0 Anatolia_Barcin_N
30.4 RUS_Karelia_HG
27.2 Yamnaya_RUS_Samara
10.4 WHG

Yamnaya numbers fall in eastern Europe and Karelia HG ( EHG population without Yamnaya CHG mixture) goes up


I added 'Corded_Ware_Baltic_early' to the source to see if the model would stop pulling an additional Karelia mix to Eastern Europe. The model has become more efficient and distances have fallen, but eastern Europe continues with an additional mixture of pre-Yamnaya EHG ( it seems to coincide with regions where the R1b haplogroup is currently less common)


Target: Irish
Distance: 4.0625% / 0.04062541
51.8 Corded_Ware_Baltic_early
36.4 Anatolia_Barcin_N
11.8 WHG


Target: Polish: Polish16
Distance: 3.9425% / 0.03942502
37.6 Corded_Ware_Baltic_early
34.8 Anatolia_Barcin_N
17.0 RUS_Karelia_HG
10.6 WHG


Target: Estonian
Distance: 5.7087% / 0.05708720
38.8 Corded_Ware_Baltic_early
28.8 Anatolia_Barcin_N
20.6 RUS_Karelia_HG
11.8 WHG




What could explain the difference?
 
Interesting observation ACK.
Here is hoping that someone can explain the phenomena... cause I personally can't.
 
I've always believed that especially in the northeast, the Yamnaya related Corded Ware people absorbed a lot of EHG people who had nothing to do with the Indo-Europeans, or those populations were absorbed later.

Those supposedly extremely high steppe admixture numbers were, imo, giving a slightly incorrect impression, and the actual highest percentages of Corded Ware/Yamnaya type ancestry were highest in Scandinavia, and perhaps more isolated areas of the British Isles.

In Britain, when the Beaker people arrived the farmer population had been decimated by climate change related food shortages, and they had clear ground. At that time, Scandinavia was really not optimal for Neolithic style farming, and populations weren't very high, so again, there was more "replacement.

This may be showing that.
 
Yep, also in my models, this happens because Pre-Indo-European Eastern Europe/Comb Ceramic Culture is overwhelmingly EHG and in my models the highest Yamnaya related ancestry is in the Dutch,Danes and Northwestgermans according to G25 Coordinates. Eastern Europe just looks more like Yamnaya because they are more EHG than Western Europe. But this is according to the G25, I don't know how reliable they are. I link high steppe ancestry in Europe to the Single Grave Culture.

Edit: It is not much higher than in the Irish, about 50%, but in some samples from Northwestern Germany you can get 55% Yamnaya but that's it, I never saw someone above 55%.
 
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Yep, also in my models, this happens because Pre-Indo-European Eastern Europe/Comb Ceramic Culture is overwhelmingly EHG and in my models the highest Yamnaya related ancestry is in the Dutch,Danes and Northwestgermans according to G25 Coordinates. Eastern Europe just looks more like Yamnaya because they are more EHG than Western Europe. But this is according to the G25, I don't know how reliable they are. I link high steppe ancestry in Europe to the Single Grave Culture.

Edit: It is not much higher than in the Irish, about 50%, but in some samples from Northwestern Germany you can get 55% Yamnaya but that's it, I never saw someone above 55%.

I wouldn't be so sure, though, that G25 is accurate, and not just because of who created it. The sample selection may be funky.
 
This is from the paper "The Genetic History of Northern Europe"
https://www.researchgate.net/figure...n-Northern-European-prehistory_fig2_314208372



Modern Baltic is somewhere in between PWC / Narva and Steppe Eneolithic. Following the study the direct EHG contribution
to mesolithic Eastern Baltic should be only very small. Could you try to model a Lithuanian? Would they also get the same result?

PCA-and-ADMIXTURE-analysis-reflecting-three-time-periods-in-Northern-European-prehistory.png



Despite its geographically vicinity to EHG, the eastern Baltic individual associated
with the Mesolithic Kunda culture shows a very close affinity to WHG in all our
analyses, with a small but significant contribution from EHG or SHG, as revealed by
significant D-statistics of the form D(Kunda, WHG; EHG/SHG, Mbuti) (Z>3;
Supplementary Information Table S2).
SHG appear intermediate between WHG/Kunda and EHG in PCA space, and the
statistic D(SHG,WHG; EHG, Mbuti) is strongly significant for excess allele sharing
of SHG and EHG (Z=12.8). Neither the Kunda individual nor SHG exhibit the major
ADMIXTURE component shared between EHG and CHG (green in Figure 2b),
bringing into question a direct contribution of EHG into the Mesolithic individuals
from Scandinavia and the eastern Baltic.
 
I wouldn't be so sure, though, that G25 is accurate, and not just because of who created it. The sample selection may be funky.

Yes might be to the samples why some Germans have 55%, but Dutch,Danes,Swedes,Norwegians,Northwestern Germans all descend from the Single Grave culture and the Irish and to some degree the British from the Dutch Bell Beakers which are an offshoot of the Single Grave Culture in my opinion. I think that is why there is the most Yamnaya ancestry, today. But the other half of their ancestry is from European Farmers and that's what pulls them away from Yamnaya when using the Distance option in Vahaduo. For Eastern Europe the difference adding EHG to models is huge, Yamnaya ancestry literally breaks-off.
 
@Dagne The same model for all Lithuanians in G25:

Bildschirmfoto 2020-05-04 um 19.27.35.png
 
This is strange for a modern Lithuanian not to pick Corded_Ware_Baltic_early, what is this Corded Ware Baltic early then? Is it Scandinavian CWC or East Baltic CWC? Scandinavian one may have some components (SHG or early farmer) that shift the modelling off.
 
This is strange for a modern Lithuanian not to pick Corded_Ware_Baltic_early, what is this Corded Ware Baltic early then? Is it Scandinavian CWC or East Baltic CWC? Scandinavian one may have some components (SHG or early farmer) that shift the modelling off.

I didn´t run the model with CWC Baltic just Yamnaya for Steppe, but here is one with early CWC Baltic:

Bildschirmfoto 2020-05-04 um 21.01.13.png
 
I've always believed that especially in the northeast, the Yamnaya related Corded Ware people absorbed a lot of EHG people who had nothing to do with the Indo-Europeans, or those populations were absorbed later.

Those supposedly extremely high steppe admixture numbers were, imo, giving a slightly incorrect impression, and the actual highest percentages of Corded Ware/Yamnaya type ancestry were highest in Scandinavia, and perhaps more isolated areas of the British Isles.

In Britain, when the Beaker people arrived the farmer population had been decimated by climate change related food shortages, and they had clear ground. At that time, Scandinavia was really not optimal for Neolithic style farming, and populations weren't very high, so again, there was more "replacement.

This may be showing that.

Angela, your explanation made a lot of sense. Thank you!
 
I think its the minor / noise percentages and sometimes the calculation over compensates. I noticed that when I was trying to model myself with my known ancestry components and adding / subtraction populations one at a time that would bring me closer to distance.
 
Becomes more noticeable when we compare Western European countries with Russia.

arget: Portuguese:EBC_Portugal1
Distance: 3.3991% / 0.03399058

52.6Anatolia_Barcin_N
31.0Yamnaya_RUS_Samara
11.0WHG
5.4MAR_Iberomaurusian


Target: French_Paris
Distance: 3.9803% / 0.03980288

47.0Anatolia_Barcin_N
40.6Yamnaya_RUS_Samara
12.4WHG


Target: French_Auvergne
Distance: 3.1213% / 0.03121337

51.8Anatolia_Barcin_N
35.6Yamnaya_RUS_Samara
12.6WHG


Target: German:German56
Distance: 5.6763% / 0.05676272

45.0Yamnaya_RUS_Samara
41.4Anatolia_Barcin_N
13.6WHG


Target: Italian_Lombardy:BGD31
Distance: 4.2395% / 0.04239467

57.6Anatolia_Barcin_N
29.2Yamnaya_RUS_Samara
7.4IRN_Ganj_Dareh_Historic
5.6WHG
0.2MAR_Iberomaurusian
 
Target: Russian_Kostroma
Distance: 5.6766% / 0.05676566

37.0RUS_Karelia_HG
34.6Anatolia_Barcin_N
22.8Yamnaya_RUS_Samara
3.0WHG
 
Can you check what happens if you include in your models this sample?:

Scaled:

Code:
POL_BKG_N_o1,0.134311,0.11577,0.190446,0.187987,0.136025,0.063866,0.017156,0.03046,0.069743,-0.011481,-0.003897,-0.017534,0.023934,-0.004679,0.03013,0.053168,0.016428,0.004054,-0.002137,0.05315,0.074743,0.012613,-0.035249,-0.135682,0.017364

Unscaled:

Code:
POL_BKG_N_o1,0.134311,0.11577,0.190446,0.187987,0.136025,0.063866,0.017156,0.03046,0.069743,-0.011481,-0.003897,-0.017534,0.023934,-0.004679,0.03013,0.053168,0.016428,0.004054,-0.002137,0.05315,0.074743,0.012613,-0.035249,-0.135682,0.017364
 
I was trying to model some populations and this happened

What paremeters were you using? No Dist Col and scaled coordinates?
 
Target: Polish:polish16
Distance: 4.6207% / 0.04620698
37.2 Anatolia_Barcin_N
28.6 Yamnaya_RUS_Samara
24.4 RUS_Karelia_HG
9.8 WHG

How about my model (using scaled coordinates):

Your populations are still in the model, but I added two extra (my choices) to see which ones will be preferred:

Your samples = black
My populations = red

Polish16:

Target: Polish:polish16
Distance: 4.3672% / 0.04367198
58.6 UKR_Sredny_Stog_En_o4
18.8 Anatolia_Barcin_N
14.2 POL_BKG_N_o1
7.8 RUS_Karelia_HG
0.6 Yamnaya_RUS_Samara
0.0 WHG

Polish average:

Target: Polish
Distance: 5.0922% / 0.05092215
56.0 UKR_Sredny_Stog_En_o4
20.4 Anatolia_Barcin_N
15.0 POL_BKG_N_o1
7.2 Yamnaya_RUS_Samara
1.4 RUS_Karelia_HG
0.0 WHG

=======

Data used:

SOURCE:

Code:
Yamnaya_RUS_Samara,0.1255849,0.089028,0.0426986,0.1153479,-0.0287232,0.0450564,0.0036033,-0.0025642,-0.0559032,-0.0728943,0.0018222,3.32e-05,-0.0026924,-0.0233041,0.0366141,0.0157633,-0.0012316,-0.0017879,-0.0038408,0.0137704,-0.0031749,0.0007557,0.0110649,0.0186102,-0.004537UKR_Sredny_Stog_En_o4:I6561,0.127482,0.11577,0.047894,0.070737,0.010771,0.026216,0.00376,0.008077,-0.017385,-0.030069,-0.008282,0.005845,0.005798,-0.029038,0.013436,0.005834,-0.005215,-0.003801,-0.006034,0.002126,-0.010981,0.004081,0.000616,0.017713,-0.003952
WHG,0.1246365,0.116278,0.184789,0.189279,0.1546445,0.0464355,0.0131605,0.0372675,0.0890705,0.017768,-0.0153455,-0.015811,0.0159065,-0.0030275,0.053338,0.0582065,0.00502,0.016343,-0.0093015,0.055589,0.0944585,0.0111905,-0.049607,-0.160866,0.0170045
POL_BKG_N_o1,0.134311,0.11577,0.190446,0.187987,0.136025,0.063866,0.017156,0.03046,0.069743,-0.011481,-0.003897,-0.017534,0.023934,-0.004679,0.03013,0.053168,0.016428,0.004054,-0.002137,0.05315,0.074743,0.012613,-0.035249,-0.135682,0.017364
Anatolia_Barcin_N,0.1175998,0.180118,0.0035312,-0.101158,0.0510443,-0.0483875,-0.0043582,-0.0069334,0.0362287,0.0807473,0.0079718,0.0118803,-0.0234545,0.0004691,-0.0419807,-0.0101913,0.0233091,0.0019866,0.0136954,-0.0097489,-0.0142249,0.0057723,-0.0041232,-0.0031658,-0.0043437
RUS_Karelia_HG,0.1236877,0.0321583,0.129855,0.2101663,-0.010361,0.0571723,-0.0196627,-0.0234603,-0.002659,-0.0860153,0.0182957,-0.0184337,0.0333497,-0.039085,0.018865,0.0295237,-0.0148203,0.0031673,-0.0044413,0.012506,-0.007487,0.0169817,0.0093667,-0.021007,-0.0103383
UKR_Sredny_Stog_En_o4,0.127482,0.11577,0.047894,0.070737,0.010771,0.026216,0.00376,0.008077,-0.017385,-0.030069,-0.008282,0.005845,0.005798,-0.029038,0.013436,0.005834,-0.005215,-0.003801,-0.006034,0.002126,-0.010981,0.004081,0.000616,0.017713,-0.003952

TARGET:

Code:
Polish,0.1318405,0.1292694,0.0698685,0.0577382,0.0406754,0.0217127,0.0086781,0.0108626,-0.0009329,-0.0185524,-0.0043488,-0.0064187,0.013093,0.0186295,-0.0070244,-0.0005595,0.0015455,-7.41e-05,0.0026948,0.0012872,-0.0031286,-0.0031185,0.0056063,-0.0033328,-8.76e-05
Polish:Polish16,0.137726,0.125926,0.069767,0.06783,0.042162,0.01757,0.00188,0.000462,0.002454,-0.019499,-0.011042,-0.004946,0.010555,0.010735,-0.000679,0.013524,-0.003651,-0.002407,-0.002514,0.001876,-0.00861,-0.004699,0.002835,-0.008314,-0.004431
 
Now let's see what happens, if I remove Anatolia_Barcin_N, and add instead Globular Amphora - who were also Neolithic Farmers, but lived in West Ukraine and Poland (those were exactly the kind of farmers that Steppe invaders encountered when they were moving from Ukraine to the Baltic Sea):

Code:
UKR_Globular_Amphora,0.1229287,0.1689163,0.0605907,-0.0204567,0.0829897,-0.014967,-0.00188,0.003538,0.052017,0.0724693,-0.0002707,0.0051953,-0.0175917,-0.001468,-0.0099073,-0.0019007,0.0051283,0.0057433,0.0051537,-0.0046273,0.0087343,0.0048227,-0.0170493,-0.0229753,0.003233
POL_Globular_Amphora,0.1263436,0.1689961,0.0604725,-0.020045,0.0843053,-0.017849,0.0016865,0.0077916,0.0537897,0.0705682,0.0004012,0.0095386,-0.0161428,-0.0056101,-0.0098915,0.0004289,0.0045635,0.0068486,0.0062036,-0.000846,0.0091822,0.0078046,-0.013956,-0.0272541,0.0009228

Polish average:

Target: Polish
Distance: 5.2133% / 0.05213338
51.6 UKR_Sredny_Stog_En_o4
27.8 UKR_Globular_Amphora
12.2 Yamnaya_RUS_Samara
7.8 POL_BKG_N_o1
0.6 RUS_Karelia_HG
0.0 WHG

Polish16:

Target: Polish:polish16
Distance: 4.4304% / 0.04430381
52.2 UKR_Sredny_Stog_En_o4
26.6 UKR_Globular_Amphora
7.4 POL_BKG_N_o1
7.4 RUS_Karelia_HG
6.4 Yamnaya_RUS_Samara
0.0 WHG

And my result in this model:

Target: Tomenable_scaled
Distance: 4.6473% / 0.04647255
74.0 UKR_Sredny_Stog_En_o4
21.2 POL_Globular_Amphora
4.8 POL_BKG_N_o1
0.0 RUS_Karelia_HG
0.0 WHG
0.0 Yamnaya_RUS_Samara

=====

If I add back Barcin_N, my Globular Amphora gets replaced by a mix of Barcin_N + more POL_BKH_N_o1:

Target: Tomenable_scaled
Distance: 4.5311% / 0.04531122
72.6 UKR_Sredny_Stog_En_o4
16.6 Anatolia_Barcin_N
10.8 POL_BKG_N_o1
0.0 POL_Globular_Amphora
0.0 RUS_Karelia_HG
0.0 WHG
0.0 Yamnaya_RUS_Samara

In other words, Globular Amphora from Poland was a mix of Anatolian Farmers and local hunter-gatherers.

POL_BKG_N_o1 is a hunter-gatherer from central Poland (Kuyavia region).

=====

Parameters which I used in this model:

Coordinates: scaled
Cycles - 16X
Add Dist Col - No
Print Zeroes - Yes

Populations used and Vahado attached:

View attachment VahaduoJS 19.11.2.zip

View attachment source_populations.zip

View attachment target_populations.zip
 
Last edited:
POL Globular Amphora modelled as a mixture of Anatolia Neolithic and POL hunter-gatherer (BKG outlier1):

5TIV8X9.png


^^^
Out of all known so far Mesolithic hunter-gatherer groups, Polish one was most similar to Lithuanian ones:

VqYD5Cv.png


So probably the same model could work well also with Baltic_LTU_Mesolithic instead of POL_BKG_N_o1.
 

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