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View Full Version : Reference points as a key element of autosomal models EgyK3 vs EgyK5



cass
11-07-2024, 12:40 PM
Let's compare two simple models EgyK3 and EgyK5

EgyK3

Population,European,African,Asian,
Adygei,90.20,0.01,9.79,
Albanian,97.18,0.30,2.52,
Algerian,75.42,24.45,0.13,
Altaian,25.61,0.00,74.39,
Armenian,96.25,0.95,2.79,
Atayal,0.00,0.00,100.00,
BantuKenya,2.00,97.13,0.87,
Basque,98.93,0.03,1.04,
BedouinA,85.95,13.17,0.88,
BedouinB,90.40,9.60,0.00,
Cypriot,96.97,2.17,0.86,
Dai,0.04,0.36,99.60,
Dong,0.00,0.03,99.97,
Druze,94.44,4.14,1.42,
Egyptian,81.78,17.87,0.35,
English,97.01,0.00,2.99,
Estonian,92.57,0.00,7.43,
French,96.79,0.00,3.21,
Gambian,2.54,97.43,0.03,
Georgian,96.01,0.37,3.62,
Greek,97.48,0.32,2.20,
Han,0.08,0.02,99.90,
Hazara,43.55,0.52,55.93,
Hezhen,1.33,0.00,98.67,
Iranian,87.94,2.94,9.13,
Italian_North,98.29,0.22,1.50,
Japanese,0.00,0.00,100.00,
Jew_Ashkenazi,95.12,2.33,2.55,
Jew_Cochin,69.96,4.69,25.35,
Jew_Ethiopian,52.21,47.52,0.27,
Jew_Georgian,94.86,1.55,3.59,
Jew_Iranian,94.78,2.16,3.06,
Jew_Libyan,93.03,6.64,0.32,
Jew_Moroccan,93.65,5.42,0.93,
Jew_Tunisian,93.72,5.98,0.30,
Jew_Turkish,95.36,3.50,1.14,
Jew_Yemenite,91.25,8.58,0.17,
Jordanian,88.35,9.35,2.30,
Ju_hoan_North,0.00,100.00,0.00,
Karitiana,0.00,0.00,100.00,
Lebanese_Christian,95.61,3.53,0.86,
Lebanese_Muslim,92.16,5.63,2.21,
Lithuanian,94.58,0.00,5.42,
Luhya,3.82,95.75,0.43,
Mayan,10.27,0.63,89.10,
Mbuti,0.00,100.00,0.00,
Mongola,4.26,0.12,95.62,
Mordovian,87.29,0.00,12.71,
Mozabite,75.38,24.62,0.00,
Nganasan,4.37,0.00,95.63,
Norwegian,95.52,0.00,4.48,
Orcadian,96.25,0.00,3.75,
Palestinian,89.26,9.58,1.16,
Papuan,19.61,16.35,64.05,
Pathan,75.99,2.01,22.01,
Pima,3.31,0.00,96.68,
Russian,86.87,0.00,13.13,
Saharawi,72.30,27.70,0.00,
Sardinian,99.63,0.37,0.01,
Saudi,91.04,8.38,0.58,
She,0.00,0.00,100.00,
Somali,40.85,58.91,0.24,
Spanish,97.01,1.34,1.65,
Syrian,88.73,8.62,2.65,
Tunisian,76.80,22.86,0.34,
Turkish,89.71,1.11,9.18,
Turkmen,61.59,0.71,37.70,
Tuvinian,16.10,0.04,83.86,
Ukrainian,93.99,0.00,6.00,
Ulchi,0.01,0.00,99.99,
Uzbek,54.25,0.70,45.05,
Xibo,3.68,0.05,96.27,
Yakut,11.91,0.00,88.09,
Yi,0.21,0.47,99.32,
Yoruba,0.02,99.96,0.02,
Zapotec,7.12,0.00,92.88,


EgyK5

Population,Near_East,Amerindian,East_Asian,African ,Baltic_Sea,
Adygei,39.94,2.33,6.47,0.00,51.27,
Albanian,35.50,0.50,0.78,0.20,63.02,
Algerian,55.07,0.10,0.33,21.20,23.31,
Altaian,2.05,8.45,65.03,0.00,24.48,
Armenian,59.57,0.65,1.76,0.00,38.02,
Atayal,0.00,0.00,100.00,0.00,0.00,
BantuKenya,3.73,0.15,0.36,95.77,0.00,
Basque,18.31,0.12,0.06,0.04,81.47,
BedouinA,67.79,1.00,0.80,9.43,20.97,
BedouinB,93.58,0.88,0.14,3.93,1.47,
Cypriot,60.91,0.30,0.68,0.04,38.08,
Dai,0.16,0.12,99.72,0.00,0.00,
Dong,0.00,0.01,99.99,0.00,0.00,
Druze,64.51,0.87,1.04,1.35,32.23,
Egyptian,66.20,0.30,0.93,13.98,18.58,
English,13.30,1.49,0.09,0.01,85.11,
Estonian,0.79,2.65,2.73,0.00,93.84,
French,18.70,1.28,0.38,0.05,79.59,
Gambian,3.97,0.00,0.00,96.00,0.03,
Georgian,53.57,1.11,1.77,0.00,43.55,
Greek,39.19,0.75,0.48,0.06,59.52,
Han,0.04,0.60,99.30,0.00,0.06,
Hazara,15.56,5.11,50.08,0.09,29.16,
Hezhen,0.47,5.80,92.70,0.00,1.03,
Iranian,52.60,2.64,6.59,0.94,37.22,
Italian_North,34.61,0.43,0.09,0.02,64.85,
Japanese,0.00,2.42,97.58,0.00,0.00,
Jew_Ashkenazi,46.18,0.31,1.79,0.96,50.76,
Jew_Cochin,40.65,3.58,21.77,2.79,31.20,
Jew_Ethiopian,55.89,0.09,1.17,42.85,0.00,
Jew_Georgian,61.37,1.33,2.23,0.00,35.08,
Jew_Iranian,65.53,1.06,2.26,0.00,31.15,
Jew_Libyan,59.94,0.19,0.34,3.99,35.54,
Jew_Moroccan,55.31,0.40,0.63,3.22,40.45,
Jew_Tunisian,61.46,0.15,0.49,3.32,34.58,
Jew_Turkish,54.30,0.66,0.42,1.60,43.01,
Jew_Yemenite,81.90,0.74,0.73,4.05,12.58,
Jordanian,63.29,0.84,2.13,6.22,27.52,
Ju_hoan_North,0.00,0.00,0.00,99.96,0.04,
Karitiana,0.00,100.00,0.00,0.00,0.00,
Lebanese_Christian,65.50,0.16,1.10,0.77,32.46,
Lebanese_Muslim,62.00,0.85,1.83,2.92,32.40,
Lithuanian,1.01,2.17,1.17,0.00,95.65,
Luhya,5.50,0.07,0.13,94.29,0.00,
Mayan,1.53,86.46,5.75,0.96,5.31,
Mbuti,0.00,0.00,0.00,100.00,0.00,
Mongola,1.05,4.07,91.27,0.00,3.60,
Mordovian,4.13,3.68,7.20,0.00,84.99,
Mozabite,57.86,0.00,0.01,21.19,20.95,
Nganasan,0.00,12.93,81.19,0.00,5.88,
Norwegian,9.25,2.39,0.43,0.00,87.93,
Orcadian,10.37,1.90,0.22,0.00,87.51,
Palestinian,66.48,0.75,1.21,6.18,25.38,
Papuan,0.00,0.00,62.77,15.03,22.20,
Pathan,31.42,5.09,16.29,1.20,46.01,
Pima,0.02,98.39,0.88,0.00,0.71,
Russian,2.63,3.70,7.57,0.00,86.10,
Saharawi,59.46,0.00,0.00,24.00,16.54,
Sardinian,40.05,0.00,0.00,0.01,59.94,
Saudi,82.03,0.71,0.87,3.99,12.40,
She,0.00,0.02,99.98,0.00,0.00,
Somali,44.70,0.15,0.69,54.46,0.00,
Spanish,27.36,0.43,0.18,1.09,70.93,
Syrian,62.95,0.88,2.45,5.65,28.08,
Tunisian,58.19,0.16,0.71,19.39,21.55,
Turkish,48.49,1.61,7.08,0.19,42.63,
Turkmen,24.75,4.62,32.34,0.18,38.11,
Tuvinian,0.14,8.32,74.59,0.00,16.94,
Ukrainian,9.43,2.12,2.12,0.00,86.34,
Ulchi,0.00,9.60,90.25,0.00,0.15,
Uzbek,19.22,5.07,39.20,0.19,36.31,
Xibo,0.94,3.72,92.33,0.00,3.01,
Yakut,0.09,9.07,78.09,0.00,12.76,
Yi,0.24,2.29,97.10,0.00,0.36,
Yoruba,0.99,0.01,0.02,98.98,0.00,
Zapotec,0.05,88.73,7.65,0.00,3.57,

The first of these - EgyK3 bases the European's anchor point on the Sardinian, a cool isolated and drifted population.

G25 works quite similarly, with many reference points placed at the western edge of the white man's world.

And this is a completely correct model, provided that you understand its assumptions.

EgyK5 (Population:Near_East,Amerindian,East_Asian,Africa n,Baltic_Sea,)
contains more variables and different reference points. For caucasoid - Baltic and Near_East points.


In the case of the first model, the Sardinian appears as 100% European and the Nordic populations deviate by 5% towards the Mongoloid.

In the case of the second model, the Northern European populations naturally correlate with the Baltic anchor. In such a model, the Basques have as much as 81.47% convergence with the Baltic point. However, the Sardinians have as much as 40% convergence with the Near Eastern point.


As you can see, the results are a derivative of reference points taken quite subjectively by the model creators.


I hope this helps clarify the matter.

cass
11-07-2024, 12:48 PM
btw Russki decoded the G25 enigma some time ago



Atlantic-Baltic,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 ,0,0,0
Sub-Saharan_African,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
West_Med,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 ,0,0,0,0
East_Asian,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
Northwestern_Eurasian,0,0,1,0,0,0,0,0,0,0,0,0,0,0, 0,0,0,0,0,0,0,0,0,0,0
South_Asian,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
Northern_Eurasian,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0, 0,0,0,0,0,0,0,0,0
East_Med,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
Non-African,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0, 0,0,0,0
East_Eurasian,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
East_Eurasian,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0, 0,0,0,0,0,0,0
Oceanian,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
Pygmy,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0, 0,0,0
Amerindian,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
East_Asian,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0 ,0,0,0,0,0
Amerindian,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
Northeast_African,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0, 0,0,0,0,0,0,0,0,0
West_Asian,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
West_Med,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0 ,0,0,0,0
Northern_Eurasian,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0
Northeast_Asian,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0, 0,0,0,0,0,0,0,0
East_Eurasian,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0
East_Asian,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0 ,0,0,0,0,0
Red_Sea,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0
Red_Sea,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0, 0,0,0,0
Caucasus,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0
Baltic,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0 ,0,0,0
East_Asian,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0
Non-African,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0, 0,0,0,0
West_Med,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0
South_Asian,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0, 0,0,0,0,0,0
Caucasus,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0
West_Med,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0 ,0,0,0,0
South_Asian,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0
Khoisan,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0, 0,0,0,0
Non-African,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0
East_Asian,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0 ,0,0,0,0,0
North_African,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0
West_Asian,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1 ,0,0,0,0,0
South_Asian,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0
Northwestern_Eurasian,0,0,0,0,0,0,0,0,0,0,0,0,0,0, 0,0,0,0,0,0,1,0,0,0,0
East_Asian,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 ,-1,0,0,0,0
Northern_Eurasian,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0, 0,0,0,0,0,1,0,0,0
North_African,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0, 0,0,0,-1,0,0,0
Western_Non-African,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0, 0,1,0,0
Eastern_Non-African,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0, 0,-1,0,0
Northern_Eurasian,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0, 0,0,0,0,0,0,0,1,0
Northwestern_Eurasian,0,0,0,0,0,0,0,0,0,0,0,0,0,0, 0,0,0,0,0,0,0,0,0,-1,0
East_Eurasian,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0, 0,0,0,0,0,0,1
Maori,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0, 0,0,-1


Of course, G25 has its advantages including a huge antique database.

cass
11-07-2024, 01:05 PM
It is worth noting that a small number of reference points leads to flattening of the model and imprecise results. Below are my results

EgyK3
83,80% Norwegian
12,20% Orcadian
01,60% French
01,00% Georgian
00,80% English
00,40% Tuvinian
00,20% Uzbek

EgyK5
62,20% English
24,00% French
07,20% Mordovian
04,40% Ukrainian
00,80% Uzbek
00,60% Turkmen
00,40% Basque
00,20% Pathan
00,20% Pima

Both are quite absurd.

This is one of the advantages of multidimensional models, e.g. G25.

Upsilander
11-07-2024, 01:23 PM
That just looks like Eurogenes K13/K15 fst in binary.

ScandinavianCelt
11-07-2024, 06:11 PM
It is worth noting that a small number of reference points leads to flattening of the model and imprecise results. Below are my results

EgyK3
83,80% Norwegian
12,20% Orcadian
01,60% French
01,00% Georgian
00,80% English
00,40% Tuvinian
00,20% Uzbek

EgyK5
62,20% English
24,00% French
07,20% Mordovian
04,40% Ukrainian
00,80% Uzbek
00,60% Turkmen
00,40% Basque
00,20% Pathan
00,20% Pima

Both are quite absurd.

This is one of the advantages of multidimensional models, e.g. G25.

Are these nMonte scores? It's not normal Global Admixture for the calc.

cass
11-07-2024, 09:39 PM
Are these nMonte scores? It's not normal Global Admixture for the calc.

Monte. If there are few dimensions it flattens the results.

Cluster K-Means K3
https://i.ibb.co/6wTHMc4/egyk3.png (https://ibb.co/T274fDH)

My goal was to show not to be manipulated.
I don't believe in the theories about the purity of Sardinians or Barcin Turk at all, and it is easy to prove it.