Best calculator

[ColaGusano]

Hello, I'm new here and I'd like to know which is the best calculator. Thank you.

[ScandinavianCelt]

Too subjective to answer. Many good ones. Create your own for your own known and suspected background, new and old.

I suggest you get the DNAGenics Admixture Studio v2.52 (or newer?) app. It helps a lot to isolate anything for analyzing-- by chromosome, combination of chromosomes, segments, etc., and it allows you to use multiple calculators to measure your selections-- genomewide or individual.

[ColaGusano]

Too subjective to answer. Many good ones. Create your own for your own known and suspected background, new and old.

I suggest you get the DNAGenics Admixture Studio v2.52 (or newer?) app. It helps a lot to isolate anything for analyzing-- by chromosome, combination of chromosomes, segments, etc., and it allows you to use multiple calculators to measure your selections-- genomewide or individual.

I've tried some of these calculators and their results differ from illustrativedna. I got 0.2% south amerindian on illustrativedna with 23andme rawndata and 0% with ancestrydna raw data. In adittion, when I run my coordinates on these calculators I don't get any amerindian whatsoever. Ia that noise?

[ScandinavianCelt]

I've tried some of these calculators and their results differ from illustrativedna. I got 0.2% south amerindian on illustrativedna with 23andme rawndata and 0% with ancestrydna raw data. In adittion, when I run my coordinates on these calculators I don't get any amerindian whatsoever. Ia that noise?

It is more than likely related to some common Mongolian genetics you share with Amerindians, but in your case probably coming throuth Central and South Asia. Probably some nomadic group like the Tatars, I would think. Ghengis Khan left his mark all over the world!

[ScandinavianCelt]

Try this one: https://www.exploreyourdna.com/calculator/93/test-moderne-2022-samuel-marques.htm

[ColaGusano]

Try this one: https://www.exploreyourdna.com/calculator/93/test-moderne-2022-samuel-marques.htm

Thanks for sharing the calculator. No amerindian. I couldn't screenshot the results because I'm using a computer, not my phone.

[Eurafricanid]

Thanks for sharing the calculator. No amerindian. I couldn't screenshot the results because I'm using a computer, not my phone.

Don't worry too much about the Amerindian, they are close to (Northern) Europeans anyways, outside of West Eurasia, of course.

[ScandinavianCelt]

Thanks for sharing the calculator. No amerindian. I couldn't screenshot the results because I'm using a computer, not my phone.

Try MDLP World 22 on Gedmatch for best free public potential matching with Amerindian groups. Run that calculator by chromosomes so you can see each chromosome and what might show up and where. You could then run the painting function and see what it might be running with.

[JerryS.]

Try running your G25 against the TA members here.

[Figaro]

It is more than likely related to some common Mongolian genetics you share with Amerindians, but in your case probably coming throuth Central and South Asia. Probably some nomadic group like the Tatars, I would think. Ghengis Khan left his mark all over the world!

I doubt it, in the case of an Iberian. Probably just ANE signals.

[ColaGusano]

I doubt it, in the case of an Iberian. Probably just ANE signals.

What's ANE?

MDLP world 22: 0.1 south ameridian with 23andme raw data and 0 % on every ameridian category with ancestrydna's raw data. I also got 0.8% papuan with 23andme raw data on illustrativedna. However, I haven't gotten any amerindian nor papuan on any of the calculators I've tried.

[Figaro]

What's ANE?

MDLP world 22: 0.1 south ameridian with 23andme raw data and 0 % on every ameridian category with ancestrydna's raw data. I also got 0.8% papuan with 23andme raw data on illustrativedna. However, I haven't gotten any amerindian nor papuan on any of the calculators I've tried.

Ancient North Eurasian. Every european has it, most of it coming from our Steppe ancestry. It has a distant connection to Native Americans. It is not impossible for your scores to be due to some foreign admixture, just didn't think it's AS likely as perhaps the less exciting explanation of some substructural thing. I mean, I have a couple matches on 23andme who score almost fully Balto-Slav with trace Polynesian or other far flung people. I wouldn't take everything literally.

[ColaGusano]

Ancient North Eurasian. Every european has it, most of it coming from our Steppe ancestry. It has a distant connection to Native Americans. It is not impossible for your scores to be due to some foreign admixture, just didn't think it's AS likely as perhaps the less exciting explanation of some substructural thing. I mean, I have a couple matches on 23andme who score almost fully Balto-Slav with trace Polynesian or other far flung people. I wouldn't take everything literally.

I have quite a few matches from Denmark, Sweden, the Netherlands, Hungary, and Poland.

[gixajo]

I have quite a few matches from Denmark, Sweden, the Netherlands, Hungary, and Poland.

Try the good old Davidski´s Ancient Standard model:


TUR_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
TUR_Tepecik_Ciftlik_N,0.108701,0.1731478,-0.0143308,-0.100534,0.0270818,-0.0402298,-0.0045828,-0.005019,0.02623,0.05745,0.008444,0.0080555,-0.0101832,0.0052298,-0.0352192,-0.0104748,0.0088662,0.0004432,0.005342,-0.0032828,0.0026827,0.0044515,-0.0071795,-0.0038258,-0.0045805
BRA_LapaDoSanto_9600BP,0.050765,-0.3095332,0.1206032,0.098515,-0.1156522,-0.017626,-0.284645,-0.3400012,-0.0136212,-0.0184422,0.002241,-0.003267,0.0004162,0.017478,-0.0065688,0.0064438,0.006493,-0.001267,0.0026898,0.003727,-0.0010482,0.007963,-0.002662,-0.0043378,0.001413
Dinka,-0.577083,0.050776,-0.000377,-0.00751,-0.005386,-0.001673,-0.017685,0.020422,0.081145,-0.09695,-0.02107,0.022742,-0.038317,-0.00117,0.010145,-0.021347,0.018612,-0.009438,0.024197,-0.024168,0.002402,0.003308,0.001479,0.000904,0.009 7
ETH_4500BP,-0.511066,0.043668,0.000754,0.000969,-0.00277,-0.011435,0.050997,-0.045229,0.089172,-0.087838,-0.012991,-0.002997,-0.031219,0.000688,0.02158,-0.029965,0.027772,0.039273,0.00176,-0.009004,0.000374,0.006183,-0.003451,-0.00241,-0.000838
Han,0.0206952,-0.4507105,-0.0082967,-0.0651579,0.0780846,0.0374475,0.0029055,-0.004804,-0.0150232,-0.0031146,-0.0495875,-0.0070573,0.0072707,-0.0081072,-0.0043305,0.0012535,0.0017542,-0.0008638,-0.0020455,-0.0102206,0.0122397,0.0069582,0.0141063,-0.0012925,-0.0022315
IRN_Ganj_Dareh_N,0.0430252,0.0664158,-0.1550722,0.0047158,-0.122669,0.0235384,0.017109,-0.0011998,-0.082546,-0.0544158,-0.0028258,-0.0016186,0.0044896,-0.0062756,0.0316498,0.0561384,-0.0054242,0.0068664,0.0136508,-0.0334162,0.00856,-0.028836,-0.0110678,-0.039331,0.0222254
IRN_Shahr_I_Sokhta_BA2_I8728,0.033009,-0.081242,-0.184789,0.125325,-0.09848,0.06777,0.002585,0.007615,0.03661,0.02606,-0.002273,0.010041,-0.005798,0.006744,0.004479,0.001326,0.008605,0.001 267,0.00352,0.001376,0.003743,-0.004946,-0.00037,-0.00253,-0.007305
Jarawa,-0.021982,-0.243028,-0.132416,0.098697,0.032372,-0.004584,-0.01012,0.006505,0.054697,0.023805,0.022806,0.0027 35,-0.004153,0.010356,-0.010807,-0.011444,0.009453,-0.001908,-0.006222,0.028678,-0.00464,0.011136,-0.01234,0.002267,0.004985
Kura-Araxes_ARM_Kaps,0.1013025,0.133034,-0.07071,-0.043605,-0.0498555,-0.0092035,0.008108,-0.011653,-0.066368,-0.01631,0.0030855,0.011015,-0.019846,0.005849,0.0042075,-0.0102095,-0.0001305,-0.003927,-0.001697,0.0032515,0.003494,-0.000247,-0.0036975,-0.0090975,-0.0030535
Levant_PPNB,0.072847,0.1639064,-0.0316026,-0.1361132,0.0332986,-0.0645352,-0.0134426,-0.0147684,0.0741604,0.03601,0.0188046,-0.0150764,0.035738,0.0025596,-0.0217696,0.006099,0.0098048,-0.0013176,-0.0047264,0.0188088,-0.001797,0.0071472,0.0008872,-0.0056874,-0.0037602
MAR_Taforalt,-0.189857,0.0814452,-0.0242866,-0.085595,0.027636,-0.0552202,-0.0705968,0.0184146,0.155397,0.003499,0.0209156,-0.0318316,0.0747168,-0.0513334,0.0711988,-0.0363032,0.0052676,-0.066106,-0.1424162,0.0389938,-0.0376836,-0.1255322,0.0730118,-0.0137606,0.0164534
Nganassan,0.047692,-0.406618,0.155789,0.00239,-0.159445,-0.088213,0.028507,0.043337,0.031088,0.012848,0.102 857,0.009412,-0.004073,-0.026162,-0.021973,-0.012331,-0.001095,0.013416,0.026837,-0.00085,0.043136,-0.011895,0.03361,0.000398,0.013556
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
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,-0.004537
Yoruba,-0.630062,0.062501,0.022113,0.016708,0.000503,0.012 474,-0.044417,0.047767,-0.048881,0.032769,0.004621,0.00079,0.023056,0.0009 51,0.012523,-0.009607,0.007076,0.000449,0.006022,-0.00299,0.001554,0.002316,-0.001759,-0.000471,-0.000425

[Figaro]

I have quite a few matches from Denmark, Sweden, the Netherlands, Hungary, and Poland.

I have matches in many places too. Do you know the full scope of ancestry of your matches? They could be full or part Iberian.

[ColaGusano]

Try the good old Davidski´s Ancient Standard model:


TUR_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
TUR_Tepecik_Ciftlik_N,0.108701,0.1731478,-0.0143308,-0.100534,0.0270818,-0.0402298,-0.0045828,-0.005019,0.02623,0.05745,0.008444,0.0080555,-0.0101832,0.0052298,-0.0352192,-0.0104748,0.0088662,0.0004432,0.005342,-0.0032828,0.0026827,0.0044515,-0.0071795,-0.0038258,-0.0045805
BRA_LapaDoSanto_9600BP,0.050765,-0.3095332,0.1206032,0.098515,-0.1156522,-0.017626,-0.284645,-0.3400012,-0.0136212,-0.0184422,0.002241,-0.003267,0.0004162,0.017478,-0.0065688,0.0064438,0.006493,-0.001267,0.0026898,0.003727,-0.0010482,0.007963,-0.002662,-0.0043378,0.001413
Dinka,-0.577083,0.050776,-0.000377,-0.00751,-0.005386,-0.001673,-0.017685,0.020422,0.081145,-0.09695,-0.02107,0.022742,-0.038317,-0.00117,0.010145,-0.021347,0.018612,-0.009438,0.024197,-0.024168,0.002402,0.003308,0.001479,0.000904,0.009 7
ETH_4500BP,-0.511066,0.043668,0.000754,0.000969,-0.00277,-0.011435,0.050997,-0.045229,0.089172,-0.087838,-0.012991,-0.002997,-0.031219,0.000688,0.02158,-0.029965,0.027772,0.039273,0.00176,-0.009004,0.000374,0.006183,-0.003451,-0.00241,-0.000838
Han,0.0206952,-0.4507105,-0.0082967,-0.0651579,0.0780846,0.0374475,0.0029055,-0.004804,-0.0150232,-0.0031146,-0.0495875,-0.0070573,0.0072707,-0.0081072,-0.0043305,0.0012535,0.0017542,-0.0008638,-0.0020455,-0.0102206,0.0122397,0.0069582,0.0141063,-0.0012925,-0.0022315
IRN_Ganj_Dareh_N,0.0430252,0.0664158,-0.1550722,0.0047158,-0.122669,0.0235384,0.017109,-0.0011998,-0.082546,-0.0544158,-0.0028258,-0.0016186,0.0044896,-0.0062756,0.0316498,0.0561384,-0.0054242,0.0068664,0.0136508,-0.0334162,0.00856,-0.028836,-0.0110678,-0.039331,0.0222254
IRN_Shahr_I_Sokhta_BA2_I8728,0.033009,-0.081242,-0.184789,0.125325,-0.09848,0.06777,0.002585,0.007615,0.03661,0.02606,-0.002273,0.010041,-0.005798,0.006744,0.004479,0.001326,0.008605,0.001 267,0.00352,0.001376,0.003743,-0.004946,-0.00037,-0.00253,-0.007305
Jarawa,-0.021982,-0.243028,-0.132416,0.098697,0.032372,-0.004584,-0.01012,0.006505,0.054697,0.023805,0.022806,0.0027 35,-0.004153,0.010356,-0.010807,-0.011444,0.009453,-0.001908,-0.006222,0.028678,-0.00464,0.011136,-0.01234,0.002267,0.004985
Kura-Araxes_ARM_Kaps,0.1013025,0.133034,-0.07071,-0.043605,-0.0498555,-0.0092035,0.008108,-0.011653,-0.066368,-0.01631,0.0030855,0.011015,-0.019846,0.005849,0.0042075,-0.0102095,-0.0001305,-0.003927,-0.001697,0.0032515,0.003494,-0.000247,-0.0036975,-0.0090975,-0.0030535
Levant_PPNB,0.072847,0.1639064,-0.0316026,-0.1361132,0.0332986,-0.0645352,-0.0134426,-0.0147684,0.0741604,0.03601,0.0188046,-0.0150764,0.035738,0.0025596,-0.0217696,0.006099,0.0098048,-0.0013176,-0.0047264,0.0188088,-0.001797,0.0071472,0.0008872,-0.0056874,-0.0037602
MAR_Taforalt,-0.189857,0.0814452,-0.0242866,-0.085595,0.027636,-0.0552202,-0.0705968,0.0184146,0.155397,0.003499,0.0209156,-0.0318316,0.0747168,-0.0513334,0.0711988,-0.0363032,0.0052676,-0.066106,-0.1424162,0.0389938,-0.0376836,-0.1255322,0.0730118,-0.0137606,0.0164534
Nganassan,0.047692,-0.406618,0.155789,0.00239,-0.159445,-0.088213,0.028507,0.043337,0.031088,0.012848,0.102 857,0.009412,-0.004073,-0.026162,-0.021973,-0.012331,-0.001095,0.013416,0.026837,-0.00085,0.043136,-0.011895,0.03361,0.000398,0.013556
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
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,-0.004537
Yoruba,-0.630062,0.062501,0.022113,0.016708,0.000503,0.012 474,-0.044417,0.047767,-0.048881,0.032769,0.004621,0.00079,0.023056,0.0009 51,0.012523,-0.009607,0.007076,0.000449,0.006022,-0.00299,0.001554,0.002316,-0.001759,-0.000471,-0.000425

No native american at all.

[ColaGusano]

The majority have no iberian at all. I also score 1.6% Eastern Europe on illustrativedna DIY.

[ColaGusano]

I have matches in many places too. Do you know the full scope of ancestry of your matches? They could be full or part Iberian.


The majority have no iberian at all. I also score 1.6% Eastern Europe on illustrativedna DI

[gixajo]

No native american at all.

I don´t know what you mean with that.

This reference
BRA_LapaDoSanto_9600BP is there to measure any "Amerindian".

[Figaro]

The majority have no iberian at all. I also score 1.6% Eastern Europe on illustrativedna DI

That is interesting.

[vader]

No native american at all.

if you could, could you post your results here?

I score this:

Target: Algarvio_scaled
Distance: 2.8282% / 0.02828203
53.6 TUR_Barcin_N
28.6 Yamnaya_RUS_Samara
11.6 WHG
4.6 MAR_Taforalt
1.0 Dinka
0.6 Han

[ColaGusano]

[QUOTE=va

[ColaGusano]

if you could, could you post your results here?

I score this:

Target: Algarvio_scaled
Distance: 2.8282% / 0.02828203
53.6 TUR_Barcin_N
28.6 Yamnaya_RUS_Samara
11.6 WHG
4.6 MAR_Taforalt
1.0 Dinka
0.6 Han

23andme raw data:
Target: User_scaled
Distance: 3.6769% / 0.03676856
49.6 TUR_Barcin_N
27.2 Yamnaya_RUS_Samara
12.2 WHG
5.4 MAR_Taforalt
4.8 TUR_Tepecik_Ciftlik_N
0.6 Dinka
0.2 Yoruba

Ancestrydna raw data:
Target: User_scaled
Distance: 3.7584% / 0.03758399
47.6 TUR_Barcin_N
27.8 Yamnaya_RUS_Samara
11.0 WHG
7.2 TUR_Tepecik_Ciftlik_N
6.4 MAR_Taforalt

[Upsilander]

23andme raw data:
Target: User_scaled
Distance: 3.6769% / 0.03676856
49.6 TUR_Barcin_N
27.2 Yamnaya_RUS_Samara
12.2 WHG
5.4 MAR_Taforalt
4.8 TUR_Tepecik_Ciftlik_N
0.6 Dinka
0.2 Yoruba

Ancestrydna raw data:
Target: User_scaled
Distance: 3.7584% / 0.03758399
47.6 TUR_Barcin_N
27.8 Yamnaya_RUS_Samara
11.0 WHG
7.2 TUR_Tepecik_Ciftlik_N
6.4 MAR_Taforalt

You have many calculators to try now with G25 :)

Curious what you score here : https://www.theapricity.com/forum/showthread.php?388627-GAC-vs-MAC-(V2)

But there are plenty more.

[ColaGusano]

You have many calculators to try now with G25 :)

Curious what you score here : https://www.theapricity.com/forum/showthread.php?388627-GAC-vs-MAC-(V2)

But there are plenty more.

Can you explain what the results on my last post mean? I'll try that one.

[ColaGusano]

You have many calculators to try now with G25 :)

Curious what you score here : https://www.theapricity.com/forum/showthread.php?388627-GAC-vs-MAC-(V2)

But there are plenty more.

23andme raw data:
Target: User_caled
Distance: 3.0262% / 0.03026233
54.4 GlobularAmphora
15.0 Russia_Karelia_HG
13.8 Macedonia_N
8.2 Iran_N
3.4 Morocco_Taforalt
2.6 Israel_Natufian
1.4 African_Nigerian
1.2 Georgia_CHG

Ancestry raw data:

Target: User_scaled
Distance: 3.3096% / 0.03309572
53.0 GlobularAmphora
16.0 Macedonia_N
14.0 Russia_Karelia_HG
10.0 Iran_N
5.6 Morocco_Taforalt
1.2 Georgia_CHG
0.2 African_Nigerian

[Upsilander]

Can you explain what the results on my last post mean? I'll try that one.

You are a normal mix for Iberian of ENF (about half) that absorbed mesolithic WHG down the line in the neolthic era (your 11-12% WHG). Then came some IE from the Steppe but most likely some groups already present in southern France (Aquitania imo) or elsewhere, so that makes you a bit more than 1/4 Indo European. The rest Taforalt and Tepecik are north African influences as well as broadly speaking "east med" influences (possibly Roman).

This is in a nutshell what it means.


By the way my model creates better distances for you than the supposed "gold standard". For me as well.

[ColaGusano]

You are a normal mix for Iberian of ENF (about half) that absorbed mesolithic WHG down the line in the neolthic era (your 11-12% WHG). Then came some IE from the Steppe but most likely some groups already present in southern France (Aquitania imo) or elsewhere, so that makes you a bit more than 1/4 Indo European. The rest Taforalt and Tepecik are north African influences as well as broadly speaking "east med" influences (possibly Roman).

This is in a nutshell what it means.

What about this last one I've posted?

[Upsilander]

What about this last one I've posted?

It's the same thing, more broken down. With two neolithic, one WHG rich (GlobularAmphora), one simply early neolithic similar to the one found in ancient west Anatolia (Macedonia N). That's why you don't score WHG anymore in this model, because its all hidden in the GAC now.

Your IE is broken down as such: a mix of Karelia, CHG, and some parts of Iran_N but you might have some extra of that from another source (NA/Roman or else).

[ColaGusano]

It's the same thing, more broken down. With two neolithic, one WHG rich (GlobularAmphora), one simply early neolithic similar to the one found in ancient west Anatolia (Macedonia N). That's why you don't score WHG anymore in this model, because its all hidden in the GAC now.

Your IE is broken down as such: a mix of Karelia, CHG, and some parts of Iran_N but you might have some extra of that from another source (NA/Roman or else).

Amazing, I'm very impressed. So that means the papuan and the amerindian are not real?

[Upsilander]

Amazing, I'm very impressed. So that means the papuan and the amerindian are not real?

Very unlikely. The Amerindian signals a tiny excess of ANE that couldn't fit in the calculator model that gave you that. As for the Papuan same thing, it's the remnant of an eastern Eurasian influence (most likely IE). You don't have any recent Papuan or Amerindian ancestor.

To assess by how much exactly your affinities is with them, try this:
https://www.theapricity.com/forum/showthread.php?387903-AreYouWhite-G25-Calculator-(AYW)&p=8046129#post8046129

Clickbait title but informative.

[ColaGusano]

Very unlikely. The Amerindian signals a tiny excess of ANE that couldn't fit in the calculator model that gave you that. As for the Papuan same thing, it's the remnant of an eastern Eurasian influence (most likely IE). You don't have any recent Papuan or Amerindian ancestor.

To assess by how much exactly your affinities is with them, try this:
https://www.theapricity.com/forum/showthread.php?387903-AreYouWhite-G25-Calculator-(AYW)&p=8046129#post8046129

Clickbait title but informative.

23andme raw data:
Distance to: User_scaled
0.59780861 Amerindian_Native
0.60868598 East_Asian
0.74477600 African_Nigerian
0.79929448 Oceanian_Papuan

Ancestry raw data:
Distance to: User_scaled
0.60236699 Amerindian_Native
0.61024492 East_Asian
0.74713714 African_Nigerian
0.80541095 Oceanian_Papuan

You're been really helpful, I really appreciate that.

[Upsilander]

23andme raw data:
Distance to: User_scaled
0.59780861 Amerindian_Native
0.60868598 East_Asian
0.74477600 African_Nigerian
0.79929448 Oceanian_Papuan

Ancestry raw data:
Distance to: User_scaled
0.60236699 Amerindian_Native
0.61024492 East_Asian
0.74713714 African_Nigerian
0.80541095 Oceanian_Papuan

You're been really helpful, I really appreciate that.

As you can see the Amerindian is an easy pass, about 2 pts margin, other scores are standard for Iberians. Many people in Europe will be closer to Amerindians without new world ancestry and without scoring any in calculators, so it can be miselading at first sight seeing some in calculators.

The Papuan is at the limit at least on 23andme data but i have seen this regularly in Iberians and i'm not quite sure why because it isn't due to ANE or East Eurasian affinity but specifically Papuan. It's a very complex question, it could be something that dates back to mesolithic and how the WHGs were slightly different there than elsewhere (El Miron cluster to LaBrana). Reminds me i have to investigate this further but we are still talking about decimals of percentages.

You are white by all means anyway with these distances (this is just an arbitrary "pass" i created for fun :))

[vader]

23andme raw data:
Target: User_scaled
Distance: 3.6769% / 0.03676856
49.6 TUR_Barcin_N
27.2 Yamnaya_RUS_Samara
12.2 WHG
5.4 MAR_Taforalt
4.8 TUR_Tepecik_Ciftlik_N
0.6 Dinka
0.2 Yoruba

Ancestrydna raw data:
Target: User_scaled
Distance: 3.7584% / 0.03758399
47.6 TUR_Barcin_N
27.8 Yamnaya_RUS_Samara
11.0 WHG
7.2 TUR_Tepecik_Ciftlik_N
6.4 MAR_Taforalt

Completely normal results for a Portuguese ancient admixture. What part of Portugal are you from?

[Fabricius]

G25 coordinates have the great advantage of allowing us to make the calculators we want with the populations we want. There are thousands of samples, some modern and some old. But asking to calculate with all possible populations gives strange and impossible results.
I, for example, usually score "Afrikaner", if I use a thousand samples. From this I do not conclude that I am descended from Boers, but rather I conclude that the Dutch from South Africa must have some SSA mixture.

With 10927 samples:

Target: Fabricius_simulated_g25_scaled
Distance: 1.0872% / 0.01087230 | ADC: 0.5x RC
63.4 Spanish_Canarias
23.6 Moldovan
9.8 Afrikaner
3.2 Esan_Nigeria

Target: Fabricius_simulated_g25_scaled
Distance: 0.8588% / 0.00858798 | ADC: 0.25x
66.2 Spanish_Canarias
10.4 German
9.8 Moldovan
6.2 Romanian
2.8 Esan_Nigeria
2.4 Hungarian
2.0 Afrikaner
0.2 Roma_Bilbao


I was hoping to have greater precision, as there are many samples from the same population, but small changes in your personal calculator can result in big changes.

For me, the best calculator remains the Eurogenes EUtest V2 K15 from GEDmatch (there is another Eurogenes K15 calculator, but I'm referring to the one mentioned!).
It was the one who best confirmed my expectations without me needing to intervene (as I need to intervene with G25 calculators).

[ColaGusano]

Completely normal results for a Portuguese ancient admixture. What part of Portugal are you from?

Father from Mogadouro and mother from Freixo de espada-à-cinta, both in trás-os-montes.

[ColaGusano]

As you can see the Amerindian is an easy pass, about 2 pts margin, other scores are standard for Iberians. Many people in Europe will be closer to Amerindians without new world ancestry and without scoring any in calculators, so it can be miselading at first sight seeing some in calculators.

The Papuan is at the limit at least on 23andme data but i have seen this regularly in Iberians and i'm not quite sure why because it isn't due to ANE or East Eurasian affinity but specifically Papuan. It's a very complex question, it could be something that dates back to mesolithic and how the WHGs were slightly different there than elsewhere (El Miron cluster to LaBrana). Reminds me i have to investigate this further but we are still talking about decimals of percentages.

You are white by all means anyway with these distances (this is just an arbitrary "pass" i created for fun :))

Amazing! Thank you for your feedback. I was thinking how odd it would be to have papuan, it makes no sense.

[ColaGusano]

G25 coordinates have the great advantage of allowing us to make the calculators we want with the populations we want. There are thousands of samples, some modern and some old. But asking to calculate with all possible populations gives strange and impossible results.
I, for example, usually score "Afrikaner", if I use a thousand samples. From this I do not conclude that I am descended from Boers, but rather I conclude that the Dutch from South Africa must have some SSA mixture.

With 10927 samples:

Target: Fabricius_simulated_g25_scaled
Distance: 1.0872% / 0.01087230 | ADC: 0.5x RC
63.4 Spanish_Canarias
23.6 Moldovan
9.8 Afrikaner
3.2 Esan_Nigeria

Target: Fabricius_simulated_g25_scaled
Distance: 0.8588% / 0.00858798 | ADC: 0.25x
66.2 Spanish_Canarias
10.4 German
9.8 Moldovan
6.2 Romanian
2.8 Esan_Nigeria
2.4 Hungarian
2.0 Afrikaner
0.2 Roma_Bilbao


I was hoping to have greater precision, as there are many samples from the same population, but small changes in your personal calculator can result in big changes.

For me, the best calculator remains the Eurogenes EUtest V2 K15 from GEDmatch (there is another Eurogenes K15 calculator, but I'm referring to the one mentioned!).
It was the one who best confirmed my expectations without me needing to intervene (as I need to intervene with G25 calculators).

K15v2 with ancestrydna raw data:

North_Sea19.11 Pct
Atlantic30.87 Pct
Baltic6.79 Pct
Eastern_Euro0.87 Pct
West_Med18.92 Pct
West_Asian- * *
East_Med14.13 Pct
Red_Sea4.54 Pct
South_Asian0.6 Pct
Southeast_Asian- * *
Siberian0.48 Pct
Amerindian- * *
Oceanian0.06 Pct
Northeast_African3.57 Pct
Sub-Saharan0.05 Pct

23andme raw data:

North_Sea18.19 Pct
Atlantic28.72 Pct
Baltic7.1 Pct
Eastern_Euro1.75 Pct
West_Med19.74 Pct
West_Asian- * *
East_Med15.99 Pct
Red_Sea4.34 Pct
South_Asian- * *
Southeast_Asian- * *
Siberian0.16 Pct
Amerindian0.3 Pct
Oceanian0.82 Pct
Northeast_African1.34 Pct
Sub-Saharan1.55 Pct

[Fabricius]

K15v2 with ancestrydna raw data:

North_Sea19.11 Pct
Atlantic30.87 Pct
Baltic6.79 Pct
Eastern_Euro0.87 Pct
West_Med18.92 Pct
West_Asian- * *
East_Med14.13 Pct
Red_Sea4.54 Pct
South_Asian0.6 Pct
Southeast_Asian- * *
Siberian0.48 Pct
Amerindian- * *
Oceanian0.06 Pct
Northeast_African3.57 Pct
Sub-Saharan0.05 Pct

23andme raw data:

North_Sea18.19 Pct
Atlantic28.72 Pct
Baltic7.1 Pct
Eastern_Euro1.75 Pct
West_Med19.74 Pct
West_Asian- * *
East_Med15.99 Pct
Red_Sea4.34 Pct
South_Asian- * *
Southeast_Asian- * *
Siberian0.16 Pct
Amerindian0.3 Pct
Oceanian0.82 Pct
Northeast_African1.34 Pct
Sub-Saharan1.55 Pct



I like these results by regions, there's less chance of being wrong and besides that's a bit of fun trying to connect the information.
On the other hand, sometimes we want the precision of discovering specific populations. In addition to this percentage result, share with us your result of Oracle-4, please. Let us know what you think.

[RyoHazuki]

Try this one: https://www.exploreyourdna.com/calculator/93/test-moderne-2022-samuel-marques.htm

Target: G25K13SimRyoHazuki
Distance: 0.5353% / 0.00535273
30.6 North_West_Europe
27.4 British_Islanders
25.8 Basque_&_SW_France
10.2 Baltic
5.0 Scandinavian
1.0 Arabian_Peninsula

Target: Ryo_scaled
Distance: 2.1101% / 0.02110072
55.0 British_Islanders
24.8 Basque_&_SW_France
7.0 Finland
3.8 Scandinavian
3.0 North_West_Europe
2.6 Spain
2.2 Arabian_Peninsula
1.6 Egypt

Target: G25K13SimRyoHazuki
Distance: 0.6286% / 0.00628597 | R5P | ADC: 0.25x RC
48.8 North_West_Europe
22.8 British_Islanders
21.2 Basque_&_SW_France
7.2 Baltic

Target: Ryo_scaled
Distance: 2.1762% / 0.02176238 | R5P | ADC: 0.25x RC
59.4 British_Islanders
19.4 Basque_&_SW_France
9.0 Spain
8.6 Finland
3.6 Arabian_Peninsula

Distance to: G25K13SimRyoHazuki
0.01152837 North_West_Europe:French_Oïl_Normandy_Manche
0.01351130 North_West_Europe:Breton_Ille-et-Vilaine_Rennes
0.01445712 British_Islanders:Welsh
0.01515142 North_West_Europe:French_Oïl_Normandy_Seine-Maritime
0.01617930 North_West_Europe:Breton_Finistere
0.01647283 British_Islanders:English
0.01701742 North_West_Europe:French_Oïl_Hauts-de-France_Pas-de-Calais
0.01727666 North_West_Europe:French_Oïl_Pays_de_la_Loire_Main e-et-Loire
0.01733969 North_West_Europe:Breton_Ille-et-Vilaine
0.01766091 North_West_Europe:Belgian_(Walloon_Profile)
0.01777651 North_West_Europe:Belgian_(Flemish_Profile)
0.01818819 Germanic_europe:Dutch
0.01836454 North_West_Europe:Breton_Cotes-d'Armor
0.01849273 North_West_Europe:Breton_Loire-Atlantique
0.01855698 North_West_Europe:French_Oïl_Hauts-de-France_Somme
0.01987893 Germanic_europe:German
0.02037685 North_West_Europe:French_(Breton/Norman_Profile)
0.02139803 British_Islanders:Scottish
0.02157474 North_West_Europe:French_Oïl_Hauts-de-France_Nord
0.02204068 British_Islanders:Orcadian
0.02256016 Germanic_europe:German_Bavaria_Erlangen
0.02264699 North_West_Europe:Breton_Morbihan
0.02472961 British_Islanders:Irish
0.02477347 North_West_Europe:French_Oïl_Ile-de-France_Paris
0.02513169 Germanic_europe:German_Hamburg

Distance to: Ryo_scaled
0.03102677 North_West_Europe:Breton_Cotes-d'Armor
0.03139421 British_Islanders:English
0.03209624 North_West_Europe:French_Oïl_Normandy_Manche
0.03328922 British_Islanders:Welsh
0.03340701 British_Islanders:Scottish
0.03417816 British_Islanders:Orcadian
0.03437492 Germanic_europe:Dutch
0.03443614 North_West_Europe:French_Oïl_Normandy_Seine-Maritime
0.03477145 North_West_Europe:French_(Breton/Norman_Profile)
0.03535764 North_West_Europe:Breton_Ille-et-Vilaine_Rennes
0.03548538 British_Islanders:Irish
0.03557437 British_Islanders:Scottish_Argyll_and_Bute
0.03609482 North_West_Europe:French_Oïl_Pays_de_la_Loire_Main e-et-Loire
0.03650333 North_West_Europe:Breton_Finistere
0.03694460 North_West_Europe:French_Oïl_Hauts-de-France_Pas-de-Calais
0.03786340 North_West_Europe:Belgian_(Walloon_Profile)
0.03855702 Scandinavian:Danish
0.03900141 Scandinavian:Icelandic
0.03902464 Scandinavian:Norwegian
0.03902754 Germanic_europe:German
0.03912120 North_West_Europe:French_Oïl_Hauts-de-France_Nord
0.03962467 North_West_Europe:Breton_Morbihan
0.03962627 North_West_Europe:French_Oïl_Grand_Est_Ardennes
0.03979909 North_West_Europe:French_Oïl_Normandy_Eure
0.03985875 North_West_Europe:Belgian_(Flemish_Profile)

clear output mode - single max output number:
25
add gradient - yes
gradient from:
0
gradient to:
0.2
run all
Ryo_scaledG25K13SimRyoHazuki

[ScandinavianCelt]

Target: Ryo_scaled
Distance: 2.1101% / 0.02110072
55.0 British_Islanders
24.8 Basque_&_SW_France
7.0 Finland
3.8 Scandinavian
3.0 North_West_Europe
2.6 Spain
2.2 Arabian_Peninsula
1.6 Egypt

Target: Ryo_scaled
Distance: 2.1762% / 0.02176238 | R5P | ADC: 0.25x RC
59.4 British_Islanders
19.4 Basque_&_SW_France
9.0 Spain
8.6 Finland
3.6 Arabian_Peninsula



This is what I get with NO ADC and with R5P @ .25x:

Target: SC_Official_AVE_Scaled
Distance: 1.5921% / 0.01592108
26.8 British_Islanders
26.8 Scandinavian
11.4 North_West_Europe
10.2 Finland
9.8 East_Europe
7.6 Germanic_europe
2.2 East_Anatolia_&_South_Caucasus
2.0 North_Caucasus
1.8 North_Africa
1.4 Persian

Target: SC_Official_AVE_Scaled
Distance: 1.6348% / 0.01634792 | R5P | ADC: 0.25x RC
63.0 British_Islanders
22.2 East_Europe
8.0 Germanic_europe
3.8 North_Caucasus
3.0 North_Africa

[celticdragongod]

Try the good old Davidski´s Ancient Standard model:


TUR_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
TUR_Tepecik_Ciftlik_N,0.108701,0.1731478,-0.0143308,-0.100534,0.0270818,-0.0402298,-0.0045828,-0.005019,0.02623,0.05745,0.008444,0.0080555,-0.0101832,0.0052298,-0.0352192,-0.0104748,0.0088662,0.0004432,0.005342,-0.0032828,0.0026827,0.0044515,-0.0071795,-0.0038258,-0.0045805
BRA_LapaDoSanto_9600BP,0.050765,-0.3095332,0.1206032,0.098515,-0.1156522,-0.017626,-0.284645,-0.3400012,-0.0136212,-0.0184422,0.002241,-0.003267,0.0004162,0.017478,-0.0065688,0.0064438,0.006493,-0.001267,0.0026898,0.003727,-0.0010482,0.007963,-0.002662,-0.0043378,0.001413
Dinka,-0.577083,0.050776,-0.000377,-0.00751,-0.005386,-0.001673,-0.017685,0.020422,0.081145,-0.09695,-0.02107,0.022742,-0.038317,-0.00117,0.010145,-0.021347,0.018612,-0.009438,0.024197,-0.024168,0.002402,0.003308,0.001479,0.000904,0.009 7
ETH_4500BP,-0.511066,0.043668,0.000754,0.000969,-0.00277,-0.011435,0.050997,-0.045229,0.089172,-0.087838,-0.012991,-0.002997,-0.031219,0.000688,0.02158,-0.029965,0.027772,0.039273,0.00176,-0.009004,0.000374,0.006183,-0.003451,-0.00241,-0.000838
Han,0.0206952,-0.4507105,-0.0082967,-0.0651579,0.0780846,0.0374475,0.0029055,-0.004804,-0.0150232,-0.0031146,-0.0495875,-0.0070573,0.0072707,-0.0081072,-0.0043305,0.0012535,0.0017542,-0.0008638,-0.0020455,-0.0102206,0.0122397,0.0069582,0.0141063,-0.0012925,-0.0022315
IRN_Ganj_Dareh_N,0.0430252,0.0664158,-0.1550722,0.0047158,-0.122669,0.0235384,0.017109,-0.0011998,-0.082546,-0.0544158,-0.0028258,-0.0016186,0.0044896,-0.0062756,0.0316498,0.0561384,-0.0054242,0.0068664,0.0136508,-0.0334162,0.00856,-0.028836,-0.0110678,-0.039331,0.0222254
IRN_Shahr_I_Sokhta_BA2_I8728,0.033009,-0.081242,-0.184789,0.125325,-0.09848,0.06777,0.002585,0.007615,0.03661,0.02606,-0.002273,0.010041,-0.005798,0.006744,0.004479,0.001326,0.008605,0.001 267,0.00352,0.001376,0.003743,-0.004946,-0.00037,-0.00253,-0.007305
Jarawa,-0.021982,-0.243028,-0.132416,0.098697,0.032372,-0.004584,-0.01012,0.006505,0.054697,0.023805,0.022806,0.0027 35,-0.004153,0.010356,-0.010807,-0.011444,0.009453,-0.001908,-0.006222,0.028678,-0.00464,0.011136,-0.01234,0.002267,0.004985
Kura-Araxes_ARM_Kaps,0.1013025,0.133034,-0.07071,-0.043605,-0.0498555,-0.0092035,0.008108,-0.011653,-0.066368,-0.01631,0.0030855,0.011015,-0.019846,0.005849,0.0042075,-0.0102095,-0.0001305,-0.003927,-0.001697,0.0032515,0.003494,-0.000247,-0.0036975,-0.0090975,-0.0030535
Levant_PPNB,0.072847,0.1639064,-0.0316026,-0.1361132,0.0332986,-0.0645352,-0.0134426,-0.0147684,0.0741604,0.03601,0.0188046,-0.0150764,0.035738,0.0025596,-0.0217696,0.006099,0.0098048,-0.0013176,-0.0047264,0.0188088,-0.001797,0.0071472,0.0008872,-0.0056874,-0.0037602
MAR_Taforalt,-0.189857,0.0814452,-0.0242866,-0.085595,0.027636,-0.0552202,-0.0705968,0.0184146,0.155397,0.003499,0.0209156,-0.0318316,0.0747168,-0.0513334,0.0711988,-0.0363032,0.0052676,-0.066106,-0.1424162,0.0389938,-0.0376836,-0.1255322,0.0730118,-0.0137606,0.0164534
Nganassan,0.047692,-0.406618,0.155789,0.00239,-0.159445,-0.088213,0.028507,0.043337,0.031088,0.012848,0.102 857,0.009412,-0.004073,-0.026162,-0.021973,-0.012331,-0.001095,0.013416,0.026837,-0.00085,0.043136,-0.011895,0.03361,0.000398,0.013556
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
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,-0.004537
Yoruba,-0.630062,0.062501,0.022113,0.016708,0.000503,0.012 474,-0.044417,0.047767,-0.048881,0.032769,0.004621,0.00079,0.023056,0.0009 51,0.012523,-0.009607,0.007076,0.000449,0.006022,-0.00299,0.001554,0.002316,-0.001759,-0.000471,-0.000425

Distance to: CDG_scaled
0.15183177 Yamnaya_RUS_Samara
0.20688415 TUR_Tepecik_Ciftlik_N
0.20994545 Kura-Araxes_ARM_Kaps
0.21790130 TUR_Barcin_N
0.26144270 Levant_PPNB
0.33215023 IRN_Ganj_Dareh_N
0.33306373 WHG
0.38540696 IRN_Shahr_I_Sokhta_BA2_I8728
0.46495067 Jarawa
0.48349269 MAR_Taforalt
0.61751779 Han
0.61816061 Nganassan
0.66704718 BRA_LapaDoSanto_9600BP
0.67753663 ETH_4500BP
0.73679259 Dinka
0.77737797 Yoruba

Target: CDG_scaled
Distance: 5.4104% / 0.05410361
50.0 Yamnaya_RUS_Samara
36.6 TUR_Barcin_N
13.4 WHG

[celticdragongod]

Try this one: https://www.exploreyourdna.com/calculator/93/test-moderne-2022-samuel-marques.htm

Distance to: CDG_scaled
0.01695521 British_Islanders:Orcadian
0.01718678 British_Islanders:Scottish
0.01798938 British_Islanders:Irish
0.01901992 British_Islanders:Welsh
0.01919413 Scandinavian:Danish
0.01923809 British_Islanders:English
0.01974439 Germanic_europe:Dutch
0.01997112 Scandinavian:Norwegian
0.02086141 North_West_Europe:Breton_Cotes-d'Armor
0.02088890 North_West_Europe:Breton_Finistere
0.02186691 Scandinavian:Icelandic
0.02329282 Scandinavian:Norwegian_Bergen
0.02449082 North_West_Europe:French_Oïl_Normandy_Seine-Maritime
0.02594064 North_West_Europe:Breton_Ille-et-Vilaine_Rennes
0.02649644 Germanic_europe:German_Hamburg
0.02747166 North_West_Europe:Belgian_(Flemish_Profile)
0.02766737 North_West_Europe:Breton_Morbihan
0.02799479 British_Islanders:Irish_Ulster
0.02863143 North_West_Europe:French_(Breton/Norman_Profile)
0.02899472 Germanic_europe:German
0.02946580 North_West_Europe:French_Oïl_Normandy_Manche
0.02981075 Scandinavian:Swedish
0.03023810 British_Islanders:Scottish_Argyll_and_Bute
0.03227247 Germanic_europe:German_Bavaria_Erlangen
0.03387248 North_West_Europe:French_Oïl_Pays_de_la_Loire_Main e-et-Loire

Target: CDG_scaled
Distance: 1.4721% / 0.01472124
38.0 Scandinavian:Norwegian
24.6 British_Islanders:Irish
13.2 British_Islanders:Scottish_Argyll_and_Bute
12.2 North_West_Europe:French_Oïl_Grand_Est_Ardennes
5.0 Basque_&_SW_France:French_Occitan_Nouvelle-Aquitaine_Dordogne
4.8 East_Europe:Ukrainian_Zaporizhzhia
1.6 British_Islanders:Irish_Ulster
0.6 North_West_Europe:French_Oïl_Bourgogne-Franche-Comte_Haute-Saone

Target: CDG_scaled
Distance: 1.4721% / 0.01472124
39.4 British_Islanders
38.0 Scandinavian
12.8 North_West_Europe
5.0 Basque_&_SW_France
4.8 East_Europe

[Solitude]

This is what I get with NO ADC and with R5P @ .25x:

Target: SC_Official_AVE_Scaled
Distance: 1.5921% / 0.01592108
26.8 British_Islanders
26.8 Scandinavian
11.4 North_West_Europe
10.2 Finland
9.8 East_Europe
7.6 Germanic_europe
2.2 East_Anatolia_&_South_Caucasus
2.0 North_Caucasus
1.8 North_Africa
1.4 Persian

Target: SC_Official_AVE_Scaled
Distance: 1.6348% / 0.01634792 | R5P | ADC: 0.25x RC
63.0 British_Islanders
22.2 East_Europe
8.0 Germanic_europe
3.8 North_Caucasus
3.0 North_Africa

you have one of the best average calcs here , there's a average calc with only european countries that i can't find anymore , if possible do a another average european countries , your calcs is too good

[Fabricius]

Marques' calculator:

Target: Fabricius_simulated_g25_scaled
Distance: 0.2226% / 0.00222577 | R5P
31.8 Basque_&_SW_France
27.0 Balkans
18.6 South_East_Europe
15.0 North_Africa
7.6 South_France


Basque? Maybe... probably yes, but 27% too much.
Why Balkans and southeast Europe?
Balkans+SE Euro... maybe. 40% (two Grandparents)?! No.
South France... No!

Target: Fabricius_simulated_g25_scaled
Distance: 0.5782% / 0.00578226 | ADC: 0.25x RC
60.2 Portugal
28.8 East_Europe
9.2 North_Africa
1.8 South_France
No France

Target: Fabricius_simulated_g25_scaled
Distance: 0.1937% / 0.00193715
20.8 Balkans
19.4 Basque_&_SW_France
13.8 North_Africa
10.2 North_West_Europe
10.0 South_East_Europe
6.4 Portugal
5.4 Sardinian
5.4 Spain
4.2 East_Europe
2.0 North_&_Central_Italy
1.6 South_France
0.8 Persian

30% Balkans & SE Euro + x% France = No


Edit:

Distances

Distance to: Fabricius_simulated_g25_scaled
0.04728541 Portugal:Portuguese_Azores
0.05065270 Portugal:Portuguese
0.05221439 Spain:Spanish_Extremadura_(Extremaduran)
0.05416246 Spain:Spanish_Galicia_(Galician)
0.05452933 Spain:Spanish_Castile_and_Leon_(Castilian)
0.05578294 Spain:Spanish_Andalusia_(Andalusian)
0.05599293 Spain:Spanish_Murcia_(Murcian)
0.05931870 Spain:Spanish_Valencia_Alicante_(Valencian)
0.06014506 Spain:Spanish_Baleares_Ibiza_(Catalan)
0.06053305 North_&_Central_Italy:Italian_Liguria_(Ligurian)
0.06060938 Spain:Spanish_Baleares_(Catalan)
0.06086588 Spain:Spanish_Baleares_Mallorca_(Catalan)
0.06088979 Spain:Spanish_Castilla-La_Mancha_(Castilian)
0.06099699 Spain:Spanish_Catalonia_(Catalan)
0.06110791 Spain:Spanish_Baleares_Menorca_(Catalan)
0.06237896 Spain:Spanish_Murcia_(Murcia)
0.06272605 Spain:Spanish_Catalonia_Camp_de_Tarragona_(Catalan )
0.06324155 South_France:French_Occitan_Provence-Alpes-Cote_d'Azur
0.06361494 Spain:Spanish_Valencia_(Valencian)
0.06362372 Spain:Spanish_Asturias_(Asturian)
0.06403597 Spain:Spanish_Cantabria_(Cantabrian)
0.06491981 Spain:Spanish_Catalonia_Barcelones_(Catalan)
0.06525527 South_France:French_Occitan_Provence-Alpes-Cote_d'Azur_Bouches-du-Rhone_Marseille
0.06529147 Spain:Spanish_Catalonia_Girona_(Catalan)
0.06569494 Spain:Spanish_Catalonia_Penedes_(Catalan)

[Upsilander]

Target: Upsilander_Scaled
Distance: 1.9337% / 0.01933690
39.0 North_West_Europe:French_Oïl_Hauts-de-France_Somme
22.8 North_West_Europe:French_Oïl_Normandy_Manche
19.8 Baltic:Lithuanian_West_Zemaitija
10.4 North_West_Europe:Breton_Ille-et-Vilaine
8.0 North_West_Europe:Breton_Finistere

Target: Upsilander_Scaled
Distance: 2.0072% / 0.02007210 | ADC: 0.5x RC
74.8 Germanic_europe:German
25.2 North_West_Europe:Breton_Finistere


Distance to: Upsilander_Scaled
0.02426764 Germanic_europe:German
0.02710323 Germanic_europe:German_Bavaria_Erlangen
0.02782186 Germanic_europe:German_Hamburg
0.02854584 North_West_Europe:Belgian_(Flemish_Profile)
0.02857852 British_Islanders:Welsh
0.02936381 North_West_Europe:French_Oïl_Normandy_Seine-Maritime
0.02943165 North_West_Europe:Breton_Finistere
0.02967065 North_West_Europe:French_Oïl_Normandy_Manche
0.03008577 North_West_Europe:Breton_Ille-et-Vilaine_Rennes
0.03014443 British_Islanders:English
0.03078966 North_West_Europe:French_Oïl_Hauts-de-France_Somme
0.03079590 Germanic_europe:Dutch
0.03079902 Germanic_europe:German_Saxony_Leipzig
0.03086450 Scandinavian:Danish
0.03115000 North_West_Europe:Breton_Ille-et-Vilaine
0.03144286 Germanic_europe:Austrian
0.03186110 North_West_Europe:Breton_Loire-Atlantique
0.03218671 North_West_Europe:Breton_Cotes-d'Armor
0.03222651 British_Islanders:Orcadian
0.03269542 North_West_Europe:Belgian_(Walloon_Profile)
0.03286866 North_West_Europe:French_Oïl_Hauts-de-France_Pas-de-Calais
0.03293215 British_Islanders:Scottish
0.03380823 North_West_Europe:French_Oïl_Pays_de_la_Loire_Main e-et-Loire
0.03491415 Scandinavian:Norwegian
0.03529107 North_West_Europe:Breton_Morbihan

[R1b-L51]

Hello, I'm new here and I'd like to know which is the best calculator. Thank you.

The best calculator is the one that Catalan women have in their pussy, which is why it is not recommended for any unwary man to marry a Catalan woman.

[R1b-L51]

Target: G25K13SimRyoHazuki
Distance: 0.5353% / 0.00535273
30.6 North_West_Europe
27.4 British_Islanders
25.8 Basque_&_SW_France
10.2 Baltic
5.0 Scandinavian
1.0 Arabian_Peninsula

Target: Ryo_scaled
Distance: 2.1101% / 0.02110072
55.0 British_Islanders
24.8 Basque_&_SW_France
7.0 Finland
3.8 Scandinavian
3.0 North_West_Europe
2.6 Spain
2.2 Arabian_Peninsula
1.6 Egypt

Target: G25K13SimRyoHazuki
Distance: 0.6286% / 0.00628597 | R5P | ADC: 0.25x RC
48.8 North_West_Europe
22.8 British_Islanders
21.2 Basque_&_SW_France
7.2 Baltic

Target: Ryo_scaled
Distance: 2.1762% / 0.02176238 | R5P | ADC: 0.25x RC
59.4 British_Islanders
19.4 Basque_&_SW_France
9.0 Spain
8.6 Finland
3.6 Arabian_Peninsula

Distance to: G25K13SimRyoHazuki
0.01152837 North_West_Europe:French_Oïl_Normandy_Manche
0.01351130 North_West_Europe:Breton_Ille-et-Vilaine_Rennes
0.01445712 British_Islanders:Welsh
0.01515142 North_West_Europe:French_Oïl_Normandy_Seine-Maritime
0.01617930 North_West_Europe:Breton_Finistere
0.01647283 British_Islanders:English
0.01701742 North_West_Europe:French_Oïl_Hauts-de-France_Pas-de-Calais
0.01727666 North_West_Europe:French_Oïl_Pays_de_la_Loire_Main e-et-Loire
0.01733969 North_West_Europe:Breton_Ille-et-Vilaine
0.01766091 North_West_Europe:Belgian_(Walloon_Profile)
0.01777651 North_West_Europe:Belgian_(Flemish_Profile)
0.01818819 Germanic_europe:Dutch
0.01836454 North_West_Europe:Breton_Cotes-d'Armor
0.01849273 North_West_Europe:Breton_Loire-Atlantique
0.01855698 North_West_Europe:French_Oïl_Hauts-de-France_Somme
0.01987893 Germanic_europe:German
0.02037685 North_West_Europe:French_(Breton/Norman_Profile)
0.02139803 British_Islanders:Scottish
0.02157474 North_West_Europe:French_Oïl_Hauts-de-France_Nord
0.02204068 British_Islanders:Orcadian
0.02256016 Germanic_europe:German_Bavaria_Erlangen
0.02264699 North_West_Europe:Breton_Morbihan
0.02472961 British_Islanders:Irish
0.02477347 North_West_Europe:French_Oïl_Ile-de-France_Paris
0.02513169 Germanic_europe:German_Hamburg

Distance to: Ryo_scaled
0.03102677 North_West_Europe:Breton_Cotes-d'Armor
0.03139421 British_Islanders:English
0.03209624 North_West_Europe:French_Oïl_Normandy_Manche
0.03328922 British_Islanders:Welsh
0.03340701 British_Islanders:Scottish
0.03417816 British_Islanders:Orcadian
0.03437492 Germanic_europe:Dutch
0.03443614 North_West_Europe:French_Oïl_Normandy_Seine-Maritime
0.03477145 North_West_Europe:French_(Breton/Norman_Profile)
0.03535764 North_West_Europe:Breton_Ille-et-Vilaine_Rennes
0.03548538 British_Islanders:Irish
0.03557437 British_Islanders:Scottish_Argyll_and_Bute
0.03609482 North_West_Europe:French_Oïl_Pays_de_la_Loire_Main e-et-Loire
0.03650333 North_West_Europe:Breton_Finistere
0.03694460 North_West_Europe:French_Oïl_Hauts-de-France_Pas-de-Calais
0.03786340 North_West_Europe:Belgian_(Walloon_Profile)
0.03855702 Scandinavian:Danish
0.03900141 Scandinavian:Icelandic
0.03902464 Scandinavian:Norwegian
0.03902754 Germanic_europe:German
0.03912120 North_West_Europe:French_Oïl_Hauts-de-France_Nord
0.03962467 North_West_Europe:Breton_Morbihan
0.03962627 North_West_Europe:French_Oïl_Grand_Est_Ardennes
0.03979909 North_West_Europe:French_Oïl_Normandy_Eure
0.03985875 North_West_Europe:Belgian_(Flemish_Profile)

clear output mode - single max output number:
25
add gradient - yes
gradient from:
0
gradient to:
0.2
run all
Ryo_scaledG25K13SimRyoHazuki

KEN MASTERS, It would be interesting that you try this calculator;

https://www.theapricity.com/forum/showthread.php?388714-Central-EE-calc-revised

[JerryS.]

I'm telling you, modern individuals is best.