The demonym for the people of the VUR is VURian or VURer.
I think they got it from me, and I maybe first saw it in some paper like Tambets et al. 2018.
It's still 24% in my first model on the left, even though the average distance is crap. Adding GEO_CHG improves the average distance a lot, but then the combined proportion of TUR_Barchin_N and GEO_CHG is still 37% for Yamnaya_KAZ_Mereke.
Here's the combined percentage of TUR_Barchin_N and GEO_CHG in the second model above:
64.6 Yamnaya_UKR_Ozera_o
62.0 Yamnaya_BGR
44.6 Yamnaya_RUS_Caucasus
44.4 RUS_Progress_En
41.8 Yamnaya_KAZ_Karagash
41.4 Yamnaya_UKR
40.8 RUS_Afanasievo
40.4 Yamnaya_RUS_Kalmykia
40.0 Yamnaya_RUS_Samara
37.0 Yamnaya_KAZ_Mereke
I didn't realize that Yamnaya had this much churka/wog ancestry.
Yeah, when I tried to model Yamnaya by putting about 200 mostly neolithic and older population averages in the sources, it was first modeled as mostly RUS_Afanasievo, but then when I removed Afanasievo, RUS_Progress_En became the main component.
Yeah but in the spreadsheet, Udmurts have 13% CHG and Saami have 7%.
This nMonte model for GEO_CHG has shit distance, but you can tell that CHG is a churka component:
$ nm g/25/ma <(aag chg)
Target: GEO_CHG (d=.127)
50.6 Abkhasian
21.0 Ossetian
9.8 Georgian_Imer
9.8 Kubachinian
4.6 Darginian
1.6 Kalash
0.4 Brahui
0.4 Makrani
0.2 Balochi
0.2 Brahmin_Uttar_Pradesh
0.2 Chechen
0.2 Gujar_India
0.2 Gujar_Pakistan
0.2 Lak
0.2 Manyika
0.2 North_Ossetian
0.2 Pashtun
(`nm` is my shell wrapper for nMonte3.R, and `aag` is a function that greps ancient averages.)
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