Does anyone know why this happens? (Vahaduo)

[Ack]

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?

[Archetype0ne]

Interesting observation ACK.
Here is hoping that someone can explain the phenomena... cause I personally can't.

[Angela]

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.

[Anfänger]

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%.

[Angela]

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.

[Dagne]

This is from the paper "The Genetic History of Northern Europe"
https://www.researchgate.net/figure/...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?




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.

[Anfänger]

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.

[Anfänger]

@Dagne The same model for all Lithuanians in G25:

Bildschirmfoto 2020-05-04 um 19.27.35.png

[Dagne]

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.

[Anfänger]

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

[Ack]

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!

[New Englander]

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.

[Ack]

Becomes more noticeable when we compare Western European countries with Russia.

arget: Portuguese:EBC_Portugal1 Distance: 3.3991% / 0.03399058
52.6	Anatolia_Barcin_N
31.0	Yamnaya_RUS_Samara
11.0	WHG
5.4	MAR_Iberomaurusian

---

Target: French_Paris Distance: 3.9803% / 0.03980288
47.0	Anatolia_Barcin_N
40.6	Yamnaya_RUS_Samara
12.4	WHG

---

Target: French_Auvergne Distance: 3.1213% / 0.03121337
51.8	Anatolia_Barcin_N
35.6	Yamnaya_RUS_Samara
12.6	WHG

---

Target: German:German56 Distance: 5.6763% / 0.05676272
45.0	Yamnaya_RUS_Samara
41.4	Anatolia_Barcin_N
13.6	WHG

---

Target: Italian_Lombardy:BGD31 Distance: 4.2395% / 0.04239467
57.6	Anatolia_Barcin_N
29.2	Yamnaya_RUS_Samara
7.4	IRN_Ganj_Dareh_Historic
5.6	WHG
0.2	MAR_Iberomaurusian

[Ack]

Target: Russian_Kostroma Distance: 5.6766% / 0.05676566
37.0	RUS_Karelia_HG
34.6	Anatolia_Barcin_N
22.8	Yamnaya_RUS_Samara
3.0	WHG

[Dagne]

Sorry deleted

[Tomenable]

Can you check what happens if you include in your models this sample?:

Scaled:

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:

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

[Tomenable]

I was trying to model some populations and this happened

What paremeters were you using? No Dist Col and scaled coordinates?

[Tomenable]

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:

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:

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

[Tomenable]

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):

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:

VahaduoJS 19.11.2.zip

source_populations.zip

target_populations.zip

[Tomenable]

POL Globular Amphora modelled as a mixture of Anatolia Neolithic and POL hunter-gatherer (BKG outlier1):



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



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

[Tomenable]

In my opinion Proto-Balto-Slavs are descended rather from Steppe folks of the Sredni Stog culture - where early R1a-M417 was found - and not from Steppe folks of the Yamnaya culture. This is why I included both of these populations in my model and I just let the algorithm choose the better fitting one - as you can see in my case Sredni Stog is entirely preferred over Yamnaya.

Globular Amphora is a good representation for those "Old Europe" farmers who lived along the way of Steppe folks expansion from Ukraine towards the Baltic Sea.

POL_BKG_N_outlier1 - this person lived in times of Lengyel culture but autosomally was one of the remnants of pure hunter-gatherers along the south Baltic coast.

PS:

Population average "Polish" in this model does score some Yamnaya - contrary to my results - however, just like in my case Sredni Stog is preferred over Yamna.

[Tomenable]

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.

Dagne I think that Corded_Ware_Baltic_Early was a "fresh off the bout" (or rather: "fresh off the horse") migrant straight from Ukraine's Steppe.

Corded_Ware_Baltic_Late - on the other hand - was already mixed with local population, which is why it is more similar to modern Lithuanians.

So it seems CWC_Baltic_Early didn't have any extra components, quite the opposite - it was missing some crucial components, absorbed later.

Edit:

This average includes these 3 individuals:

Corded_Ware_Baltic_early:Gyvakarai1
Corded_Ware_Baltic_early:I4629
Corded_Ware_Baltic_early:Plinkaigalis242

=====

List of populations closest to CWC_Baltic_early based on scaled version of coordinates:

[Tomenable]

Even if I add to this model various Yamnaya subgroups and Poltavka, still Sredny Stog is preferred:

Target: Tomenable_scaled
Distance: 4.5234% / 0.04523438
65.4 UKR_Sredny_Stog_En_o4
18.2 Anatolia_Barcin_N
11.2 POL_BKG_N_o1
5.2 RUS_Poltavka
0.0 POL_Globular_Amphora
0.0 RUS_Karelia_HG
0.0 WHG
0.0 Yamnaya_KAZ_Karagash
0.0 Yamnaya_KAZ_Mereke
0.0 Yamnaya_RUS_Kalmykia
0.0 Yamnaya_RUS_Samara
0.0 Yamnaya_UKR

source_populations2.zip

Of course I realize that sample already had Neolithic Farmer admixture, but it lived in the Steppe.

[Ack]

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:

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:

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

I've always used scaled coordinates.
I use earlier populations as a source. You use later cultures and stay out of context.

[Ack]

Even if I add to this model various Yamnaya subgroups and Poltavka, still Sredny Stog is preferred:
Target: Tomenable_scaled
Distance: 4.5234% / 0.04523438
65.4 UKR_Sredny_Stog_En_o4
18.2 Anatolia_Barcin_N
11.2 POL_BKG_N_o1
5.2 RUS_Poltavka
0.0 POL_Globular_Amphora
0.0 RUS_Karelia_HG
0.0 WHG
0.0 Yamnaya_KAZ_Karagash
0.0 Yamnaya_KAZ_Mereke
0.0 Yamnaya_RUS_Kalmykia
0.0 Yamnaya_RUS_Samara
0.0 Yamnaya_UKR
source_populations2.zip
Of course I realize that sample already had Neolithic Farmer admixture, but it lived in the Steppe.

'UKR_Srendy' you used Already has an 'excess' of EHG and hides the EHG / Rarelia in the east when added to the model.

Target: UKR_Sredny_Stog_En_o4 Distance: 3.5594% / 0.03559414
60.2	Yamnaya_RUS_Samara
26.8	Anatolia_Barcin_N
10.0	RUS_Karelia_HG
2.8	WHG
0.2	MAR_Iberomaurusian