Gedmatch-based method of obtaining G25 coordinates

[gixajo]

Run any Gedmatch calculator in which you obtain good distances in "oracle 4 ", then take similar 4 populations samples from G25 pop averages datasheet, and calculate the mean.

In my case I did it with K13 and K15.

K13

1 French_Basque + Southwest_French + Spanish_Galicia + Spanish_Galicia @ 3.908170

So I did this mean (average?) with more similar population samples form G25 datasheet (No Southwest French in that datasheet so I put South French)

Basque_French,+French_South,+Spanish_Galicia,+Span ish_Galicia,

And I obtain these coordinates:


gixajo_fromK13,0.1179402,0.1474335,0.0467299,0.004 5952,0.0473774,-0.0007967,-0.0030140,0.0026110,0.0269159,0.0349802,-0.0050762,0.0072947,-0.0170129,-0.0129758,0.0114701,0.0005020,-0.0063739,0.0001245,-0.0026462,-0.0011295,0.0042237,-0.0010357,-0.0038800,-0.0060226,-0.0014994

I try them adding to this model sources:

http://g25vahaduo.genetics.ovh/G25modern-scaled-averages.htm

And I get that my customized coordinates are my firts sample in my distance list:

Distance to: gixajo_scaled
0.01634115 gixajo_fromK13
0.01658208 Spanish_Aragon
0.01727214 Spanish_Pirineu
0.01859632 Spanish_Terres_de_l'Ebre
0.01886758 Spanish_Cantabria
0.01912200 Spanish_Valencia
0.01950849 Spanish_Peri-Barcelona
0.01976409 Spanish_Catalunya_Central
0.02002144 Spanish_Castilla_La_Mancha
0.02011638 Spanish_Camp_de_Tarragona
0.02034893 Spanish_Castello
0.02040101 Spanish_Barcelones
0.02066881 Spanish_Lleida
0.02103738 Spanish_Cataluna
0.02141164 Spanish_Penedes
0.02180879 Spanish_Eivissa
0.02222523 Spanish_Girona
0.02226842 Spanish_Mallorca
0.02231857 Spanish_Navarra
0.02242790 Spanish_Alacant
0.02243580 French_South
0.02303983 Spanish_Galicia
0.02332999 Spanish_Andalucia
0.02374266 Spanish_Menorca
0.02394533 Spanish_Castilla_Y_Leon
0.02521989 Spanish_Baleares
0.02532658 Portuguese
0.02753658 French_Auvergne
0.02761609 Spanish_Extremadura
0.02830354 Spanish_Murcia
0.02886831 French_Occitanie
0.03065155 Spanish_Pais_Vasco
0.03211235 Basque_French
0.03295970 Spanish_Soria
0.03297847 French_Provence
0.03308185 Spanish_Asturias
0.03367804 Italian_Trentino-Alto-Adige
0.03384616 Swiss_French
0.03394874 Italian_Aosta_Valley
0.03475637 Basque_Spanish
0.03550088 Spanish_La_Rioja
0.03876068 Italian_Veneto
0.03970081 Italian_Bergamo
0.04156026 French_Paris
0.04181608 Italian_Lombardy
0.04269814 Italian_Northeast
0.04280247 Swiss_German
0.04582266 French_Nord
0.04584494 French_Alsace
0.04633465 Italian_Liguria

So it´s not a perfect match, but these coordinates work relatively well.

I did not check this method with different oracle 4 K13 results, or with different calculators in which I obtain better distances, surely I could get better coordinates searching more, this is only to explain the method.

I hope this method helps someone, and remember that this does not replace authentic G25 coordinates made with your raw data directly.

:wink

[Defcon2]

1 French_Basque + French_Basque + Spanish_Cataluna + Tunisian @ 4.281778

Basque_French + Basque_French + Spanish_Cataluna + Tunisian


K13,0.08054175,0.1454174,0.03528595,-0.01178075,0.04490703,-0.00641453,-0.00673693,0.00351228,0.03448318,0.03317423,-0.00374983,0.00530935,-0.00780445,-0.01221858,0.01208793,-0.002356,-0.00705065,-0.0021284,-0.0078922,-0.00115325,0.00401528,-0.00589685,-0.00076618,-0.00590288,0.00032773



Distance to: Juan_scaled
0.02910453 Spanish_Castilla_Y_Leon
0.03060658 Spanish_Andalucia
0.03207120 Spanish_Murcia
0.03254586 Portuguese
0.03321372 Spanish_Extremadura
0.03357197 Spanish_Galicia
0.03396093 Spanish_Asturias
0.03519913 Spanish_Castilla_La_Mancha
0.03564540 Spanish_Valencia
0.03572431 Spanish_Aragon
0.03575547 Spanish_Alacant
0.03579724 Spanish_Menorca
0.03689213 Spanish_Eivissa
0.03726761 Spanish_Baleares
0.03763331 Spanish_Cataluna
0.03783351 K13
0.03866352 Spanish_Cantabria
0.03918715 Spanish_Terres_de_l'Ebre
0.03940735 Spanish_Pirineu
0.04021304 Spanish_Barcelones
0.04023849 Spanish_Mallorca
0.04029485 Spanish_Canarias
0.04040945 Spanish_Peri-Barcelona
0.04043393 Spanish_Lleida
0.04043567 Spanish_Navarra

[gixajo]

1 French_Basque + French_Basque + Spanish_Cataluna + Tunisian @ 4.281778

[/CODE]



Edito: pensé que usaste las mías...:rolleyes:

Me refiero a que, no tienes porqué coger el K13, si hay otro oracle que te da mejores distancias, escoge ese.

Or even an oracle with only 2 populations.

[Defcon2]

Edito: pensé que usaste las mías...:rolleyes:

Me refiero a que, no tienes porqué coger el K13, si hay otro oracle que te da mejores distancias, escoge ese.

Or even an oracle with only 2 populations.

El K13 es el mejor pero los oracles son un poco peste en ambos, el de 2 pops es Aragón/Andalucía y el de 3 es un 50% basque, 25% Cataluña/Tunecino, vamos una pérdida de tiempo.

K15 mejor distancia de 4 pops: 1 French_Basque + Orcadian + Sardinian + Spanish_Murcia @ 5.391935 (...........)

[Schwop]

How can i do this? Do i need g25?

K13

++++++++++++++++++++++++++++++++++++++++++++++++++ +++++++++
1 Belorussian + North_Swedish + Southwest_English + Southwest_Finnish @ 1.563990

[gixajo]

El K13 es el mejor pero los oracles son un poco peste en ambos, el de 2 pops es Aragón/Andalucía y el de 3 es un 50% basque, 25% Cataluña/Tunecino, vamos una pérdida de tiempo.

K15 mejor distancia de 4 pops: 1 French_Basque + Orcadian + Sardinian + Spanish_Murcia @ 5.391935 (...........)

Mis distancias tampoco son espectaculares en el K13, pero bajan algo respecto el sample de medias en Vahaduo.

La idea es dar una alternativa a los que no tienen G25 pero subieron sus raw data a Gedmatch.

The idea is to give an alternative option to those who don´t have G25 coordinates but have uploaded their raw data to Gedmacht.

[gixajo]

How can i do this? Do i need g25?

K13

++++++++++++++++++++++++++++++++++++++++++++++++++ +++++++++
1 Belorussian + North_Swedish + Southwest_English + Southwest_Finnish @ 1.563990

These would be your scaled coordinates:


Schwop_fromK13,0.13174588,0.12088580,0.07458703,0. 06142590,0.03868860,0.02191873,0.00748860,0.010548 30,0.00357365,-0.01182523,-0.00211280,-0.00181365,0.00321303,0.00473933,0.00664963,0.0005 2630,-0.00721523,0.00128703,0.00316880,0.00245710,0.0036 7430,0.00067810,0.00272143,0.00596593,0.00062950

Made with more similar population samples I found in average pop, sorry, not North_Swedish or SouthWest_Finnish.

Belarusian+Swedish+English_Cornwall+Finnish

[Defcon2]

Mis distancias tampoco son espectaculares en el K13, pero bajan algo respecto el sample de medias en Vahaduo.

La idea es dar una alternativa a los que no tienen G25 pero subieron sus raw data a Gedmatch.

The idea is to give an alternative option to those who don´t have G25 coordinates but have uploaded their raw data to Gedmacht.

Para averiguar eso sería suficiente con saber los orígenes de cada ascendencia.

[gixajo]

Para averiguar eso sería suficiente con saber los orígenes de cada ascendencia.

Ese método ya lo usamos por ejemplo cuando customizamos coordenadas del K13 para Samnium, pero creo que este tiene una base más sólida para que le funcione mejor a la gente. Mi padre es andaluz y plotea mejor como aragonés, y mi madre como navarra, así aunque a algunos les funcione bien ese método, creo que este debería ir mejor.

Lo que tú dices también pensé hacerlo,con todas las regiones limítrofes, en mi caso a mi madre le pondría:

Basque_french+Castilla y León+Navarra+La Rioja

y a mi padre:

Andalucía+Castilla_La_Mancha+Alicante(o Murcia)

y luego hacer una media de los dos, a ver que tal son mis distancias con eso.

[JohnnyP]

Can you do for me ?
puntDNAL k13
1 Montenegrin + Greek_Central + Italian_Abruzzo + Belarusian @ 1.700765

Eurogenes k13
1 Ashkenazi + Bulgarian + Central_Greek + Lithuanian @ 2.106948

[InfamousAngel99]

Run any Gedmatch calculator in which you obtain good distances in "oracle 4 ", then take similar 4 populations samples from G25 pop averages datasheet, and calculate the mean.

In my case I did it with K13 and K15.

K13

1 French_Basque + Southwest_French + Spanish_Galicia + Spanish_Galicia @ 3.908170

So I did this mean (average?) with more similar population samples form G25 datasheet (No Southwest French in that datasheet so I put South French)

Basque_French,+French_South,+Spanish_Galicia,+Span ish_Galicia,

And I obtain these coordinates:


gixajo_fromK13,0.1179402,0.1474335,0.0467299,0.004 5952,0.0473774,-0.0007967,-0.0030140,0.0026110,0.0269159,0.0349802,-0.0050762,0.0072947,-0.0170129,-0.0129758,0.0114701,0.0005020,-0.0063739,0.0001245,-0.0026462,-0.0011295,0.0042237,-0.0010357,-0.0038800,-0.0060226,-0.0014994

I try them adding to this model sources:

http://g25vahaduo.genetics.ovh/G25modern-scaled-averages.htm

And I get that my customized coordinates are my firts sample in my distance list:

Distance to: gixajo_scaled
0.01634115 gixajo_fromK13
0.01658208 Spanish_Aragon
0.01727214 Spanish_Pirineu
0.01859632 Spanish_Terres_de_l'Ebre
0.01886758 Spanish_Cantabria
0.01912200 Spanish_Valencia
0.01950849 Spanish_Peri-Barcelona
0.01976409 Spanish_Catalunya_Central
0.02002144 Spanish_Castilla_La_Mancha
0.02011638 Spanish_Camp_de_Tarragona
0.02034893 Spanish_Castello
0.02040101 Spanish_Barcelones
0.02066881 Spanish_Lleida
0.02103738 Spanish_Cataluna
0.02141164 Spanish_Penedes
0.02180879 Spanish_Eivissa
0.02222523 Spanish_Girona
0.02226842 Spanish_Mallorca
0.02231857 Spanish_Navarra
0.02242790 Spanish_Alacant
0.02243580 French_South
0.02303983 Spanish_Galicia
0.02332999 Spanish_Andalucia
0.02374266 Spanish_Menorca
0.02394533 Spanish_Castilla_Y_Leon
0.02521989 Spanish_Baleares
0.02532658 Portuguese
0.02753658 French_Auvergne
0.02761609 Spanish_Extremadura
0.02830354 Spanish_Murcia
0.02886831 French_Occitanie
0.03065155 Spanish_Pais_Vasco
0.03211235 Basque_French
0.03295970 Spanish_Soria
0.03297847 French_Provence
0.03308185 Spanish_Asturias
0.03367804 Italian_Trentino-Alto-Adige
0.03384616 Swiss_French
0.03394874 Italian_Aosta_Valley
0.03475637 Basque_Spanish
0.03550088 Spanish_La_Rioja
0.03876068 Italian_Veneto
0.03970081 Italian_Bergamo
0.04156026 French_Paris
0.04181608 Italian_Lombardy
0.04269814 Italian_Northeast
0.04280247 Swiss_German
0.04582266 French_Nord
0.04584494 French_Alsace
0.04633465 Italian_Liguria

So it´s not a perfect match, but these coordinates work relatively well.

I did not check this method with different oracle 4 K13 results, or with different calculators in which I obtain better distances, surely I could get better coordinates searching more, this is only to explain the method.

I hope this method helps someone, and remember that this does not replace authentic G25 coordinates made with your raw data directly.

:wink

Do you mind doing it for me? I'm not quite understanding your explanation.

23andMe Kit:
Eurogenes K13
1 Austrian + South_Dutch + Southeast_English + Southwest_English @ 1.972643

AncestryDNA Kit:
Eurogenes K13
1 East_German + South_Dutch + South_Dutch + Southwest_English @ 1.593018

[gixajo]

Can you do for me ?
puntDNAL k13
1 Montenegrin + Greek_Central + Italian_Abruzzo + Belarusian @ 1.700765

Eurogenes k13
1 Ashkenazi + Bulgarian + Central_Greek + Lithuanian @ 2.106948

I used those samples form scaled G25 modern pop averages:

Montenegrin+Greek_Thessaly+Italian_Abruzzo+Belarus ian

There was another sample option that was quite good "Central_Greek_Macedonia", but I add Greek_Thessaly to stick more to the result of the PuntDnalk13.

I did only PuntDNAL K13, because you get better distances with it.

Scaled coordinates:


JohnnyP_fromPuntDnalK13,0.12260648,0.13853333,0.03 193050,0.00717343,0.02677683,0.00409503,0.00414290 ,0.00441735,0.00090980,0.00437415,-0.00023990,-0.00052678,0.00143100,0.00988238,-0.00985725,-0.00163038,0.00293355,-0.00031335,0.00468455,-0.00283870,-0.00496808,-0.00019000,0.00442085,-0.00052740,-0.00070805

[gixajo]

Do you mind doing it for me? I'm not quite understanding your explanation.

23andMe Kit:
Eurogenes K13
1 Austrian + South_Dutch + Southeast_English + Southwest_English @ 1.972643

AncestryDNA Kit:
Eurogenes K13
1 East_German + South_Dutch + South_Dutch + Southwest_English @ 1.593018

Choose one of both, please, I have a hard time calculating each average.

[Luke35]

Very clever my friend, well done.

Now you I expect you are going to get quite a few requests for coordinates :)

[InfamousAngel99]

Choose one of both, please, I have a hard time calculating each average.

I'm sorry, I should have added in my motive of including both. I was just giving you the option of which one to do. AncestryDNA, if you want me to choose.

[gixajo]

Very clever my friend, well done.

Now you I expect you are going to get quite a few requests for coordinates :)

I can help some, but people should learn to make coordinate means, it is a bit heavy, but it is easy.

My "method" of making averages with these coordinates is quite primitive, it takes a while to do them, and since there is some almost manual step, I can make a mistake in some specific coordinate.

I test the coordinates first to see if they work, but I do not find that I was wrong in any sign, or in any specific number.

[17571imre]

could you do mine also? my K13 is in my signature :)

[SUPREEEEEME]

An interesting concept to try:

Eurogenes K13:
Ashkenazi + Lebanese_Druze + Orcadian + Tunisian_Jewish @ 2.904971



Distance to: EurogenesK13
0.01260794 Ashkenazi_Ukraine
0.01421605 Ashkenazi_Belarussia
0.01438098 Ashkenazi_Russia
0.01457427 Ashkenazi_Poland
0.01492614 Ashkenazi_Lithuania
0.02259246 SUPREEEEEME_scaled
0.02300262 Maltese
0.02427001 Ashkenazi_Germany
0.02444455 Sicilian_West
0.02696802 Sicilian_East
0.02738237 Italian_Campania
0.02818467 Italian_Basilicata
0.02873378 Italian_Abruzzo
0.02938817 Italian_Apulia
0.02944813 Italian_Calabria
0.03173050 Italian_Molise
0.03257270 Greek_Crete
0.03376178 Italian_Jew
0.03423348 Greek_Izmir
0.03488281 Sephardic_Jew
0.03617092 Italian_Marche
0.03656840 Italian_Lazio
0.03827573 Italian_Umbria
0.04059465 Greek_Kos
0.04225482 Romaniote_Jew


Eurogenes K15:
Armenian + Austrian + French_Basque + Yemenite_Jewish @ 2.490110



Distance to: EurogenesK15
0.02429384 Ashkenazi_Ukraine
0.02571141 Ashkenazi_Belarussia
0.02577822 Ashkenazi_Poland
0.02719497 Ashkenazi_Russia
0.02760463 Sicilian_West
0.02781425 Ashkenazi_Lithuania
0.03202623 SUPREEEEEME_scaled
0.03234857 Sicilian_East
0.03277894 Italian_Abruzzo
0.03340608 Ashkenazi_Germany
0.03352224 Maltese
0.03434744 Italian_Campania
0.03490969 Italian_Basilicata
0.03508306 Italian_Apulia
0.03631896 Italian_Molise
0.03643710 Italian_Marche
0.03692703 Italian_Lazio
0.03854648 Italian_Calabria
0.03913371 Greek_Izmir
0.03973891 Greek_Crete
0.04102572 Italian_Umbria
0.04145410 Italian_Jew
0.04452293 Italian_Tuscany
0.04526021 Sephardic_Jew
0.04529752 Greek_Peloponnese


Dodecad V3:
Morocco_Jews_Behar + Morocco_Jews_Behar + Orkney_1000 Genomes + Syrians_Behar @ 2.049217



Distance to: DodecadV3
0.02155344 Ashkenazi_Ukraine
0.02305175 Ashkenazi_Poland
0.02312494 Ashkenazi_Russia
0.02327012 Ashkenazi_Lithuania
0.02333045 Ashkenazi_Belarussia
0.02608516 Maltese
0.02622386 SUPREEEEEME_scaled
0.02940600 Ashkenazi_Germany
0.02941739 Sicilian_West
0.03509351 Sicilian_East
0.03657074 Italian_Campania
0.03747450 Sephardic_Jew
0.03768772 Italian_Jew
0.03775957 Italian_Calabria
0.03805287 Italian_Basilicata
0.03833067 Italian_Abruzzo
0.03911677 Italian_Apulia
0.03946353 Moroccan_Jew
0.04131109 Italian_Molise
0.04265878 Greek_Crete
0.04407546 Italian_Lazio
0.04457088 Italian_Marche
0.04498429 Greek_Izmir
0.04529159 Romaniote_Jew
0.04559064 Italian_Umbria


Gedrosia K12:
Jordanian + Norwegian + Sicilian + Turks_Kayseri @ 2.838285



Distance to: GedrosiaK12
0.02394046 Ashkenazi_Russia
0.02478904 Ashkenazi_Belarussia
0.02507918 Ashkenazi_Lithuania
0.02563015 Ashkenazi_Ukraine
0.02874552 Ashkenazi_Poland
0.02989003 SUPREEEEEME_scaled
0.03653944 Sicilian_West
0.03895415 Maltese
0.03947538 Italian_Basilicata
0.03952838 Italian_Abruzzo
0.03953027 Italian_Molise
0.03956256 Ashkenazi_Germany
0.04029752 Sicilian_East
0.04039317 Greek_Izmir
0.04107891 Italian_Campania
0.04146303 Italian_Apulia
0.04241046 Italian_Calabria
0.04269616 Greek_Crete
0.04384849 Italian_Marche
0.04526306 Italian_Umbria
0.04631528 Turkish_Istanbul
0.04651832 Greek_Thessaly
0.04664399 Italian_Lazio
0.04689676 Greek_Peloponnese
0.04906006 Turkish_Balkans


puntDNAL K12:
French_South + Nogai + Palestinian + Sicilian_East @ 2.818830



Distance to: PuntDNALK12
0.03958626 Turkish_Balikesir
0.04290517 Turkish_Northwest
0.04369618 Turkish_Aydin
0.04658357 Turkish_Southwest
0.05393699 Turkish_Istanbul
0.05399289 Turkish_North
0.05561363 Turkish_South
0.05596321 Turkish_Balkans
0.05975494 Turkish_Central
0.06567750 Turkish_Adana
0.06759569 Roma_Barcelona
0.06909055 Ashkenazi_Russia
0.06951240 Turkish_Kayseri
0.07027432 Roma_Madrid
0.07087969 Ashkenazi_Lithuania
0.07172046 Ashkenazi_Belarussia
0.07223867 Ashkenazi_Ukraine
0.07443974 SUPREEEEEME_scaled
0.07479269 Ashkenazi_Poland
0.07844304 Roma_Bilbao
0.07919150 Roma_Granada
0.08333259 Ashkenazi_Germany
0.08342967 Roma_Porto
0.08394351 Azeri
0.08401258 Sicilian_West


In theory, it's not bad - except for the last one.

[Kyp]

Who can do my father's?

Afghan_Pashtun + Druze + Turkish_Trabzon + Uzbek @ 2.024647

[mitalit]

o bicho que se devora a si mesmo

[Chris596]

Wow is this for real? I wanted to buy G25 coordinates but now I might as well just do this. Yeah can someone do this for me? (pleeeaaase)

And what would be better? Can you help me to choose one? For example:

Eurogenes K13: 1 Bulgarian + Bulgarian + Serbian + Ukrainian_Belgorod @ 2.184501
PuntDNAL K13: 1 French + Norwegian + Orcadian + Turkish_Aydin @ 2.122946
Dodecad K12b: 1 Belorussian_Behar + Belorussian_Behar + Kumyks_Yunusbayev + Sardinian_HGDP @ 2.121763
Harappaworld: 1 belorussian_behar + lithuanian_behar + north-ossetian_yunusbayev + sardinian_hgdp @ 1.425610
Gedrosia K12: 1 BA_Sintashta + Sardinian + Turks_Istanbul + Turks_Istanbul @ 2.760295
PuntDNAL K12 Modern: 1 Balkar + Russian + Sardinian + Scottish_West @ 1.105825
MDLP K23b: 1 Kosovar_ + Kosovar_ + Mordovian_ + South_German_ @ 1.737589

[gixajo]

I'm sorry, I should have added in my motive of including both. I was just giving you the option of which one to do. AncestryDNA, if you want me to choose.

2XEnglish_Cornwall+Dutch+Austrian(no SouthDutch sample)

Scaled coordinates.




InfAng99_fromK13A,0.12905843,0.13645385,0.05954918 ,0.04131270,0.03976180,0.01550350,0.00516065,0.006 77618,0.00484180,0.00425410,-0.00489780,0.00458240,-0.00937335,-0.00663813,0.01486420,0.00384645,-0.00826150,0.00157153,0.00374293,0.00253403,0.0033 2940,0.00198870,0.00010463,0.01176275,-0.00003468

I noticed it was SouthEast+SouthWest and not 2XSouthWest so here you have an alternative scaled coordinates:

English+English_Cornwall+Austrian,+Dutch,


InfAng99_fromK13B,0.12947315,0.13577648,0.05965760 ,0.04152030,0.03909395,0.01558765,0.00554813,0.006 61483,0.00453725,0.00393190,-0.00493153,0.00436673,-0.00908428,-0.00666390,0.01482933,0.00394148,-0.00772198,0.00206638,0.00372385,0.00246403,0.0036 1143,0.00187180,-0.00052310,0.01161943,-0.00019950

[gixajo]

o bicho que se devora a si mesmo

El horror, sabía que esto pasaría...:picard1:

[InfamousAngel99]

2XEnglish_Cornwall+Dutch+Austrian(no SouthDutch sample)

Scaled coordinates.




InfAng99_fromK13A,0.12905843,0.13645385,0.05954918 ,0.04131270,0.03976180,0.01550350,0.00516065,0.006 77618,0.00484180,0.00425410,-0.00489780,0.00458240,-0.00937335,-0.00663813,0.01486420,0.00384645,-0.00826150,0.00157153,0.00374293,0.00253403,0.0033 2940,0.00198870,0.00010463,0.01176275,-0.00003468

I noticed it was SouthEast+SouthWest and not 2XSouthWest so here you have an alternative scaled coordinates:

English+English_Cornwall+Austrian,+Dutch,


InfAng99_fromK13B,0.12947315,0.13577648,0.05965760 ,0.04152030,0.03909395,0.01558765,0.00554813,0.006 61483,0.00453725,0.00393190,-0.00493153,0.00436673,-0.00908428,-0.00666390,0.01482933,0.00394148,-0.00772198,0.00206638,0.00372385,0.00246403,0.0036 1143,0.00187180,-0.00052310,0.01161943,-0.00019950

Thank you! It's much appreciated :)

[gixajo]

Who can do my father's?

Afghan_Pashtun + Druze + Turkish_Trabzon + Uzbek @ 2.024647


could you do mine also? my K13 is in my signature :)

Sorry, but I can do already do more, I must go.

You should know how to make means/averages IMO, there are a lot of free software you can get if you don´t have Microsoft office , or excell to do them.

Or take a pen and a paper and...

[gixajo]

Those coordinates probably are not accurate comparing with real ones, they are only for fun...

See you later, I must to do more things.

[gixajo]

Wow is this for real? I wanted to buy G25 coordinates but now I might as well just do this. Yeah can someone do this for me? (pleeeaaase)

And what would be better? Can you help me to choose one? For example:

Eurogenes K13: 1 Bulgarian + Bulgarian + Serbian + Ukrainian_Belgorod @ 2.184501
PuntDNAL K13: 1 French + Norwegian + Orcadian + Turkish_Aydin @ 2.122946
Dodecad K12b: 1 Belorussian_Behar + Belorussian_Behar + Kumyks_Yunusbayev + Sardinian_HGDP @ 2.121763
Harappaworld: 1 belorussian_behar + lithuanian_behar + north-ossetian_yunusbayev + sardinian_hgdp @ 1.425610
Gedrosia K12: 1 BA_Sintashta + Sardinian + Turks_Istanbul + Turks_Istanbul @ 2.760295
PuntDNAL K12 Modern: 1 Balkar + Russian + Sardinian + Scottish_West @ 1.105825
MDLP K23b: 1 Kosovar_ + Kosovar_ + Mordovian_ + South_German_ @ 1.737589

This does not replace authentic coordinates of the G25, they are just a bad substitute for people to entertain themselves until they have the authentic ones since July 1.

From Eurogenes K13.

Bulgarian+Bulgarian,+Serbian+Ukrainian


Chris696_fromEurogenesK13,0.12674963,0.13287928,0. 02984691,0.02052578,0.02919458,0.00565800,0.005904 28,0.00584998,-0.00056930,-0.00112003,-0.00234868,-0.00163760,0.00596498,0.01274340,-0.01318445,-0.00276008,0.00628353,0.00075653,0.00338993,-0.00265770,-0.00539213,-0.00159925,0.00442698,-0.00202065,-0.00107093

[knez01]

Gixajo could you do it for me please?
Eurogenes k13
1 Central_Greek + Lithuanian + Moldavian + Moldavian @ 4.605844

[Lucas]

Also you can use mixed mode oracle proportions:) But in such case you need weighted average for calculation (60%+40% or 90%+10% for example).

For me very well works.

Distance to: Lukasz_scaled
0.02283665 lm_k13
0.02469798 Russian_Smolensk
0.02587988 Belarusian
0.02835025 Russian_Voronez
0.03025788 Polish
0.03080252 Ukrainian
0.03324837 Russian_Orel
0.03541132 Cossack_Ukrainian
0.03592490 Sorb_Niederlausitz
0.03643668 Lithuanian
0.03719018 Russian_Kursk
0.04620656 Russian_Tver
0.04641220 Estonian
0.04676215 Moldovan_o
0.04739836 Czech
0.04759863 Latvian
0.04774378 German_East
0.04858081 Slovakian
0.05297392 Slovenian
0.05578805 Croatian
0.05630159 Hungarian
0.06333579 Russian_Kostroma
0.06500159 Cossack_Kuban
0.06506494 Bosnian
0.06667317 Mordovian

[Lucas]

This does not replace authentic coordinates of the G25, they are just a bad substitute for people to entertain themselves until they have the authentic ones since July 1.



No, no, it's quite good actually. Don't be shy.
But you must choose as much similar refs as possible. Not exactly top one if refs are not replicated in G25.

[Dr_Maul]

Which sample is "Turkish_Behar" correspond to in G25? all of the ones there are regional Adana, Aydin etc.

[Lucas]

Which sample is "Turkish_Behar" correspond to in G25? all of the ones there are regional Adana, Aydin etc.

Check MDLP K16 or K23b it should have Turkish regional in Gedmatch.

[gixajo]

No, no, it's quite good actually. Don't be shy.
But you must choose as much similar refs as possible. Not exactly top one if refs are not replicated in G25.

yeah. I know it, but it is only a proposal and an approximation.Datasheets are what are.

The original idea is that each one makes its own coordinates, comparing the results of various calculators, with the references that best suit him.

Spanish, Italians, frenchs or Turks have more country reference than others, so for us would be more accurate.

I´ve already tried several coordinates of the same person made with different calculators, and doesn´t alway fit well among them.Even i check averages/means made from several customized coordinates with this method trying to improve them,

For Europeans or European ancestry mainly, I would advice the traditional K13, or maybe K15.

But it is very hard work with the means and the time I can expend in this, so I proposed a path, and anyone starting from this base, is free to improve what I started.

And as I said several times, nothing remplaces the original G25 coordinates, this is only for fun.

[Dr_Maul]

Check MDLP K16 or K23b it should have Turkish regional in Gedmatch.

Well, now in MDLP I don't even get a Turkish result XD but thanks anyway, I'll just pick the closest one by comparing the numbers

[gixajo]

Gixajo could you do it for me please?
Eurogenes k13
1 Central_Greek + Lithuanian + Moldavian + Moldavian @ 4.605844

Greek_Thessaly+Lithuanian_RA+Moldovan+Moldovan


Knez01_fromK13,0.12552655,0.13116285,0.04432470,0. 02515673,0.02932083,0.01025415,0.00680238,0.007301 55,-0.00161180,-0.00440953,-0.00096390,-0.00307803,0.00670888,0.01596588,-0.01154060,-0.00246875,0.00434253,-0.00066360,0.00397953,-0.00114480,-0.00511258,-0.00105368,0.00516258,-0.00155078,-0.00109075

[Impaler]

How about mine, mate? Eurogenes K15 has the most SNPs(184240).

puntDNAL K13:
1 French_Basque + Jordanian + Tadjik + Ukrainian @ 2.179775

Eurogenes K13:
1 Ashkenazi + Finnish + Iranian + Spanish_Valencia @ 4.440485

Eurogenes K15:
1 Estonian + Lebanese_Druze + Spanish_Cataluna + Turkmen @ 4.922306

MDLP World:
1 Vepsa + Sardinian + Italian-North + Brahui @ 1.195434

[knez01]

Greek_Thessaly+Lithuanian_RA+Moldovan+Moldovan


Knez01_fromK13,0.12552655,0.13116285,0.04432470,0. 02515673,0.02932083,0.01025415,0.00680238,0.007301 55,-0.00161180,-0.00440953,-0.00096390,-0.00307803,0.00670888,0.01596588,-0.01154060,-0.00246875,0.00434253,-0.00066360,0.00397953,-0.00114480,-0.00511258,-0.00105368,0.00516258,-0.00155078,-0.00109075

Thank you man

[Dr_Maul]

Can someone do mine
armenian_behar + azeri_harappa + brahui_hgdp + syrian_behar @ 1.785185

[Adamg]

Run any Gedmatch calculator in which you obtain good distances in "oracle 4 ", then take similar 4 populations samples from G25 pop averages datasheet, and calculate the mean.

So it´s not a perfect match, but these coordinates work relatively well.

I did not check this method with different oracle 4 K13 results, or with different calculators in which I obtain better distances, surely I could get better coordinates searching more, this is only to explain the method.

I hope this method helps someone, and remember that this does not replace authentic G25 coordinates made with your raw data directly.

:wink

Davidski:


Following a rigorous testing phase, the awesome Global 25 analysis is now available at the store for $12 USD. What's so awesome about this test, you might ask? See here and here.

Gixajo: I hacked it using old oracle from Gedmatch :))))))))))))))))))))))


Davidski: ........... eeeee........eeee.......eee....:mad:

[Rædwald]

Eurogenes K13


1 Danish + North_Swedish + Southeast_English + Spanish_Valencia @ 3.098357

Eurogenes K15


1 Norwegian + Norwegian + Norwegian + Spanish_Aragon @ 3.066442


Run me please!

[knez01]

I believe that I've found an even more accurate way to get your g25 results for free, instead of using gedmatch 4-oracle, because you get a much smaller distance, put your data into vahaduo original/updated k13, and for example you get this result:
35.6 Latvian
28.8 Bulgarian_Ruse
15.0 Sardinian
13.8 Pomak_Kavala
2.8 Laz
1.4 Saudi
0.8 Georgian
0.8 Karitiana
0.6 Bulgarian_Northwest
0.4 Macedonian_Southwest
Use the vahaduo g25 modern averages to get each component seperately by doing this x1*0.356+x2*0.288+x3*0.150+x3*0.138... = average of 1st component(1st component of your new g25)
x1,x2... - 1st component of every population
And I guess if you do this for every component separately your result should me more accurate than the one which you get from oracle-4.
It will take time but it will be much more realistic and accurate than the gixajo's version although based on the same concept.

[andre]

I believe that I've found an even more accurate way to get your g25 results for free, instead of using gedmatch 4-oracle, because you get a much smaller distance, put your data into vahaduo original/updated k13, and for example you get this result:
35.6 Latvian
28.8 Bulgarian_Ruse
15.0 Sardinian
13.8 Pomak_Kavala
2.8 Laz
1.4 Saudi
0.8 Georgian
0.8 Karitiana
0.6 Bulgarian_Northwest
0.4 Macedonian_Southwest
Use the vahaduo g25 modern averages to get each component seperately by doing this x1*0.356+x2*0.288+x3*0.150+x3*0.138... = average of 1st component(1st component of your new g25)
x1,x2... - 1st component of every population
And I guess if you do this for every component separately your result should me more accurate than the one which you get from oracle-4.
It will take time but it will be much more realistic and accurate than the gixajo's version although based on the same concept.

Could you try with mine? It would be interesting

Target: Andre
Distance: 1.0959% / 1.09592498 | ADC: 0.25x
57.0 Bulgarian_Pleven
21.6 Romania_Crisana
17.4 Hungarian_Csango
3.6 Saudi
0.4 Pomak_Central-Macedonia

[knez01]

Could you try with mine? It would be interesting

Target: Andre
Distance: 1.0959% / 1.09592498 | ADC: 0.25x
57.0 Bulgarian_Pleven
21.6 Romania_Crisana
17.4 Hungarian_Csango
3.6 Saudi
0.4 Pomak_Central-Macedonia

I will if I find the time, but it is really simple like I said in the post above, I am still doing mine lol

[gixajo]

How about mine, mate? Eurogenes K15 has the most SNPs(184240).

puntDNAL K13:
1 French_Basque + Jordanian + Tadjik + Ukrainian @ 2.179775

Eurogenes K13:
1 Ashkenazi + Finnish + Iranian + Spanish_Valencia @ 4.440485

Eurogenes K15:
1 Estonian + Lebanese_Druze + Spanish_Cataluna + Turkmen @ 4.922306

MDLP World:
1 Vepsa + Sardinian + Italian-North + Brahui @ 1.195434

Basque_French+Jordanian+Tajik+Ukrainian

Scaled.


Impaler_fromPuntdnalK13,0.10020295,0.10514093,0.01 156408,0.00421743,0.00941468,0.00331230,0.00182348 ,0.00268938,0.00363273,-0.00030880,-0.00299030,-0.00140601,0.00240818,-0.00036160,0.00308565,0.00430913,-0.00299103,0.00078335,0.00024523,-0.00168120,0.00013280,-0.00014728,-0.00041708,-0.00223765,0.00221698



Target: Impaler_fromPuntdnalK13
Distance: 0.1778% / 0.00177806
25.0 Basque_French
25.0 Jordanian
25.0 Tajik
25.0 Ukrainian

[gixajo]

I believe that I've found an even more accurate way to get your g25 results for free, instead of using gedmatch 4-oracle, because you get a much smaller distance, put your data into vahaduo original/updated k13, and for example you get this result:
35.6 Latvian
28.8 Bulgarian_Ruse
15.0 Sardinian
13.8 Pomak_Kavala
2.8 Laz
1.4 Saudi
0.8 Georgian
0.8 Karitiana
0.6 Bulgarian_Northwest
0.4 Macedonian_Southwest
Use the vahaduo g25 modern averages to get each component seperately by doing this x1*0.356+x2*0.288+x3*0.150+x3*0.138... = average of 1st component(1st component of your new g25)
x1,x2... - 1st component of every population
And I guess if you do this for every component separately your result should me more accurate than the one which you get from oracle-4.
It will take time but it will be much more realistic and accurate than the gixajo's version although based on the same concept.

The idea is good, but I should prevent you that you can find a great problem operating coordinates in that way.

I did already something similar, some weeks ago when I investigate how the coordinates work.

Yesterday we were talking preciselly about that method, and I exposed the problems whe fin doing this,which are basically related to the way in which we use a product to calculate an increase and its effect on negative figures, and the question of what exactly is the most distant or close coordinate.

If you know exactly how the coordinates work and you've solved that problem to operate them, I'd like to see how you do it.

Check it, if it works, it´s another way to do the same.:thumb001:

[andre]

1 East_Sicilian + Italian_Abruzzo + Russian_Smolensk + Russian_Smolensk @ 1.624632

Could you do it also for me?

Thank you!

[gixajo]

Eurogenes K13


1 Danish + North_Swedish + Southeast_English + Spanish_Valencia @ 3.098357

Eurogenes K15


1 Norwegian + Norwegian + Norwegian + Spanish_Aragon @ 3.066442


Run me please!

3XNorwegian+Spanish_Aragon
Scaled.


Rædwald_fromK15,0.13024610,0.13259003,0.06129903,0 .03999430,0.04069693,0.01574258,0.00301513,0.00545 780,0.01052023,0.00951870,-0.00333913,0.00533760,-0.01005188,-0.01005188,0.01899600,0.00635005,-0.00525503,0.00175663,-0.00004608,0.00081285,0.00509038,0.00419643,0.0029 1610,0.01303418,0.00076115


Target: Rædwald_fromK15
Distance: 0.1930% / 0.00193000
75.0 Norwegian
25.0 Spanish_Aragon

[andre]

3XNorwegian+Spanish_Aragon
Scaled.


Rædwald_fromK15,0.13024610,0.13259003,0.06129903,0 .03999430,0.04069693,0.01574258,0.00301513,0.00545 780,0.01052023,0.00951870,-0.00333913,0.00533760,-0.01005188,-0.01005188,0.01899600,0.00635005,-0.00525503,0.00175663,-0.00004608,0.00081285,0.00509038,0.00419643,0.0029 1610,0.01303418,0.00076115


Target: Rædwald_fromK15
Distance: 0.1930% / 0.00193000
75.0 Norwegian
25.0 Spanish_Aragon

Target: Rædwald_fromK15
Distance: 1.2508% / 0.01250762 | ADC: 0.5x
57.6 Celtic_7
14.0 Celtic_1
12.6 Celtic_4
10.6 Germanic_2
5.2 Celtic_3

With my project. So Celtic.

[gixajo]

1 East_Sicilian + Italian_Abruzzo + Russian_Smolensk + Russian_Smolensk @ 1.624632

Could you do it also for me?

Thank you!

Sicilian_East,+Italian_Abruzzo,+Russian_Smolensk,+ Russian_Smolensk,


andre_fromGedmatch,0.12119793,0.13547410,0.0340707 3,0.01419463,0.02805270,0.00552555,0.00550713,0.00 579435,0.00289035,-0.00216585,0.00018903,-0.00252060,0.00550123,0.01430575,-0.00792193,-0.00590193,-0.00192273,-0.00063793,0.00198463,-0.00100135,-0.00090803,-0.00111418,0.00269993,-0.00220188,0.00002325

Target: andre_fromGedmatch
Distance: 0.0000% / 0.00000002
50.0 Russian_Smolensk
25.0 Italian_Abruzzo
25.0 Sicilian_East

In this case distances are so close because they coincided exactly practically number of decimal places I use with the coordinates of the original populations.

[andre]

Sicilian_East,+Italian_Abruzzo,+Russian_Smolensk,+ Russian_Smolensk,


andre_fromGedmatch,0.12119793,0.13547410,0.0340707 3,0.01419463,0.02805270,0.00552555,0.00550713,0.00 579435,0.00289035,-0.00216585,0.00018903,-0.00252060,0.00550123,0.01430575,-0.00792193,-0.00590193,-0.00192273,-0.00063793,0.00198463,-0.00100135,-0.00090803,-0.00111418,0.00269993,-0.00220188,0.00002325

Target: andre_fromGedmatch
Distance: 0.0000% / 0.00000002
50.0 Russian_Smolensk
25.0 Italian_Abruzzo
25.0 Sicilian_East

In this case distances are so close because they coincided exactly practically number of decimal places I use with the coordinates of the original populations.

I can't run it, i think that it's a problem.

[gixajo]

1 East_Sicilian + Italian_Abruzzo + Russian_Smolensk + Russian_Smolensk @ 1.624632

use only in Scaled models/calculators


andre_fromGedmatch,0.12119793,0.13547410,0.0340707 3,0.01419463,0.02805270,0.00552555,0.00550713,0.00 579435,0.00289035,-0.00216585,0.00018903,-0.00252060,0.00550123,0.01430575,-0.00792193,-0.00590193,-0.00192273,-0.00063793,0.00198463,-0.00100135,-0.00090803,-0.00111418,0.00269993,-0.00220188,0.00002325

They work fine,I´ve checked it again, try them here for example:

http://g25vahaduo.genetics.ovh/LivingDNA%20G25%20Model.htm

[andre]

use only in Scaled models/calculators


andre_fromGedmatch,0.12119793,0.13547410,0.0340707 3,0.01419463,0.02805270,0.00552555,0.00550713,0.00 579435,0.00289035,-0.00216585,0.00018903,-0.00252060,0.00550123,0.01430575,-0.00792193,-0.00590193,-0.00192273,-0.00063793,0.00198463,-0.00100135,-0.00090803,-0.00111418,0.00269993,-0.00220188,0.00002325

They work fine,I´ve checked it again, try them here for example:

http://g25vahaduo.genetics.ovh/LivingDNA%20G25%20Model.htm

Thank you.

[gixajo]

The main problem is that all those coordinates get excessively close distances.

We would have to "mess them up" a bit to make them look more "real".

It´s the consequence of being made with refrence samples from the datasheet.

Maybe if we make them using individual samples and not population averages, distances are more distant.

[gixajo]

As a point of interest, comparation among different coordinates made with this method(K13,K15 and a mean between both, ) and real G25 coordinates (gixajo_scaled).

i used this model:

http://g25vahaduo.genetics.ovh/ULTIMATE%20ANCIENT%20COMPONENTS.htm

https://i.imgur.com/5rSMWR6.png

[andre]

Target: Andrei_scaled
Distance: 3.6921% / 0.03692103
53.0 Early_European_Farmer
35.0 Steppe_Pastoralist
9.2 Scandinavian_Hunter-Gatherer
2.2 Eastern_Hunter-Gatherer
0.4 Northeastern_Asia_Neolithic
0.2 Iran_Neolithic

Target: andre_fromGedmatch
Distance: 2.6485% / 0.02648511
45.6 Early_European_Farmer
39.0 Steppe_Pastoralist
12.0 Scandinavian_Hunter-Gatherer
2.4 Early_Levantine_Farmer
0.8 Ancient_Dravidian
0.2 Iran_Neolithic

Coordinates with k15 looks so good.

[Dr_Maul]

As a point of interest, comparation among different coordinates made with this method(K13,K15 and a mean between both, ) and real G25 coordinates (gixajo_scaled).

i used this model:

http://g25vahaduo.genetics.ovh/ULTIMATE%20ANCIENT%20COMPONENTS.htm

https://i.imgur.com/5rSMWR6.png

Can you do this one pls

armenian_behar + azeri_harappa + brahui_hgdp + syrian_behar @ 1.785185

[gixajo]

Can you do this one pls

armenian_behar + azeri_harappa + brahui_hgdp + syrian_behar @ 1.785185

Scaled coordinates.


Dr.Maul_fromGedmatch,0.08211920,0.10041215,-0.06489645,-0.03265753,-0.03926538,-0.00262753,0.00284245,-0.00245103,-0.02041375,-0.00910790,-0.00038038,-0.00238108,0.00346588,-0.00219833,0.00245728,0.00945233,-0.00398295,0.00147435,0.00308208,-0.00832658,0.00025083,-0.00335428,-0.00166988,-0.00556565,0.00296932

I post this to check that the statistical mean is well done.:)

Target: Dr.Maul_fromGedmatch
Distance: 0.0000% / 0.00000002
25.0 Armenian
25.0 Azeri
25.0 Brahui
25.0 Syrian

[Dr_Maul]

Scaled coordinates.


Dr.Maul_fromGedmatch,0.08211920,0.10041215,-0.06489645,-0.03265753,-0.03926538,-0.00262753,0.00284245,-0.00245103,-0.02041375,-0.00910790,-0.00038038,-0.00238108,0.00346588,-0.00219833,0.00245728,0.00945233,-0.00398295,0.00147435,0.00308208,-0.00832658,0.00025083,-0.00335428,-0.00166988,-0.00556565,0.00296932

I post this to check that the statistical mean is well done.:)

Target: Dr.Maul_fromGedmatch
Distance: 0.0000% / 0.00000002
25.0 Armenian
25.0 Azeri
25.0 Brahui
25.0 Syrian

Thanks!

[gixajo]

I take this opportunity to say once again that the coordinates made with raw data from a saliva test are the ones that would really be more precise, all of these do not have the same value.
They are only an approximation, and it depends on each person and the references that are available, will vary quite a bit with respect to the real results, to each individual.

So if you really want to have precise values ​​that are as true as possible to what you are, you should obtain the original G25 coordinates made from your raw data.

[Kyp]

Distance to: Father_kyp
0.03787813 Turkish_South
0.04099013 Turkish_North
0.04352974 Turkish_Southwest
0.04771539 Turkish_Northwest
0.04957151 Turkish_Balikesir
0.05055253 Turkish_Aydin
0.05274196 Azeri
0.05338515 Turkish_Central
0.05753605 Turkish_Adana
0.05974592 Azeri_Dagestan
0.05974936 Iranian_Fars
0.06006751 Iranian_Seyyed
0.06008404 Parsi_Pakistan
0.06019050 Azeri_Turkey
0.06178191 Parsi_India
0.06355053 Tajik
0.06443997 Turkish_Kayseri
0.06460376 Turkish_Istanbul
0.06515703 Kumyk
0.06611164 Kabardin
0.06660276 Roma_Balkans
0.06672449 Tajik_Yagnobi
0.06751731 Abazin
0.06814414 Karachay
0.06934473 Talysh_Azerbaijan


seems like I made a mistake

Target: Father_kyp
Distance: 1.1696% / 0.01169588
35.2 Turkish_Trabzon
25.4 Uzbek
23.4 Pashtun
16.0 Druze

[gixajo]

Distance to: Father_kyp
0.03787813 Turkish_South
0.04099013 Turkish_North
0.04352974 Turkish_Southwest
0.04771539 Turkish_Northwest
0.04957151 Turkish_Balikesir
0.05055253 Turkish_Aydin
0.05274196 Azeri
0.05338515 Turkish_Central
0.05753605 Turkish_Adana
0.05974592 Azeri_Dagestan
0.05974936 Iranian_Fars
0.06006751 Iranian_Seyyed
0.06008404 Parsi_Pakistan
0.06019050 Azeri_Turkey
0.06178191 Parsi_India
0.06355053 Tajik
0.06443997 Turkish_Kayseri
0.06460376 Turkish_Istanbul
0.06515703 Kumyk
0.06611164 Kabardin
0.06660276 Roma_Balkans
0.06672449 Tajik_Yagnobi
0.06751731 Abazin
0.06814414 Karachay
0.06934473 Talysh_Azerbaijan


seems like I made a mistake

Target: Father_kyp
Distance: 1.1696% / 0.01169588
35.2 Turkish_Trabzon
25.4 Uzbek
23.4 Pashtun
16.0 Druze

Coordinates I gave you were those of your father?

Which calculator is this?

in modern averages:

Distance to: Dr.Maul_fromGedmatch
0.01707511 Iranian_Lor
0.01791326 Ezid
0.01811956 Iranian_Seyyed
0.01832340 Iranian_Fars
0.02347025 Iranian_Zoroastrian
0.02567436 Talysh_Azerbaijan
0.02619436 Kurdish
0.02627182 Azeri
0.03163362 Azeri_Turkey
0.03956886 Iranian_Mazandarani
0.04238187 Azeri_Dagestan
0.04252653 Turkish_Adana
0.04606349 Turkish_Kayseri
0.04873142 Mountain_Jew_Chechnya
0.04988846 Georgian_Jew
0.05072924 Turkish_Central
0.05102649 Assyrian
0.05127547 Iranian_Jew
0.05835984 Syrian
0.05876266 Armenian
0.05896246 Parsi_Pakistan
0.06166714 Parsi_India
0.06292750 Turkish_Istanbul
0.06603731 Iranian_Bandari
0.06768140 Iraqi_Jew

[Kyp]

Coordinates I gave you were those of your father?

Which calculator is this?

in modern averages:

Distance to: Dr.Maul_fromGedmatch
0.01707511 Iranian_Lor
0.01791326 Ezid
0.01811956 Iranian_Seyyed
0.01832340 Iranian_Fars
0.02347025 Iranian_Zoroastrian
0.02567436 Talysh_Azerbaijan
0.02619436 Kurdish
0.02627182 Azeri
0.03163362 Azeri_Turkey
0.03956886 Iranian_Mazandarani
0.04238187 Azeri_Dagestan
0.04252653 Turkish_Adana
0.04606349 Turkish_Kayseri
0.04873142 Mountain_Jew_Chechnya
0.04988846 Georgian_Jew
0.05072924 Turkish_Central
0.05102649 Assyrian
0.05127547 Iranian_Jew
0.05835984 Syrian
0.05876266 Armenian
0.05896246 Parsi_Pakistan
0.06166714 Parsi_India
0.06292750 Turkish_Istanbul
0.06603731 Iranian_Bandari
0.06768140 Iraqi_Jew

You didn't gave me coordinates. I'm not Dr.Maul :D

I've made it myself for my father's results. It's g25.

[Dr_Maul]

Coordinates I gave you were those of your father?

Which calculator is this?

in modern averages:

Distance to: Dr.Maul_fromGedmatch
0.01707511 Iranian_Lor
0.01791326 Ezid
0.01811956 Iranian_Seyyed
0.01832340 Iranian_Fars
0.02347025 Iranian_Zoroastrian
0.02567436 Talysh_Azerbaijan
0.02619436 Kurdish
0.02627182 Azeri
0.03163362 Azeri_Turkey
0.03956886 Iranian_Mazandarani
0.04238187 Azeri_Dagestan
0.04252653 Turkish_Adana
0.04606349 Turkish_Kayseri
0.04873142 Mountain_Jew_Chechnya
0.04988846 Georgian_Jew
0.05072924 Turkish_Central
0.05102649 Assyrian
0.05127547 Iranian_Jew
0.05835984 Syrian
0.05876266 Armenian
0.05896246 Parsi_Pakistan
0.06166714 Parsi_India
0.06292750 Turkish_Istanbul
0.06603731 Iranian_Bandari
0.06768140 Iraqi_Jew

Those are my coordinates lol

[Elias.99]

Waiting until 1st July but would be fun if someone could help me out with this.

1 Kurdish + Lebanese_Muslim + Mozabite_Berber + Mozabite_Berber @ 2.893268

[RyoHazuki]

I'm doing mine right now, but it's interesting! For North_Dutch + Spanish_Murcia + West_Scottish + West_Scottish from Eurogenes, I'll translate it to Dutch + Spanish_Murcia + Shetlandic + Shetlandic for G25.

[RyoHazuki]

My coordinates won't work, Vahaduo says non numerical value in target.



Ryo_K13/G25,0.126161325,0.1352467,0.0551695,0.0340395,0.04 169355,0.0133478,0.002502425,0.0035297,0.01010725, 0.006069025,0.004439325,0.0053712,−0.0110439,−0.01 1219075,0.016194075,0.002283725,−0.0061688,0.00124 86,0.00253925,−0.000276275,0.004029625,0.000255806 3,0.0030401,0.012484325,0.001708075

[RyoHazuki]

I've scanned the whole coordinates and don't find any non-numerical data?

[gixajo]

My coordinates won't work, Vahaduo says non numerical value in target.



Ryo_K13/G25,0.126161325,0.1352467,0.0551695,0.0340395,0.04 169355,0.0133478,0.002502425,0.0035297,0.01010725, 0.006069025,0.004439325,0.0053712,−0.0110439,−0.01 1219075,0.016194075,0.002283725,−0.0061688,0.00124 86,0.00253925,−0.000276275,0.004029625,0.000255806 3,0.0030401,0.012484325,0.001708075


Here you have good ones, i prefer redo it before find an error in which you made.


RyoHazuki_fromGedmatch,0.12616133,0.13524670,0.055 16950,0.03403950,0.04169355,0.01334780,0.00250243, 0.00352970,0.00898120,0.00606903,-0.00443933,0.00537120,-0.01104390,-0.01121908,0.01619408,0.00228373,-0.00616880,0.00124860,0.00253925,-0.00027628,0.00402963,0.00132225,0.00304010,0.0124 8433,0.00170808

Target: RyoHazuki_fromGedmatch
Distance: 0.0000% / 0.00000002
50.0 Shetlandic
25.0 Dutch
25.0 Spanish_Murcia

[gixajo]

i have compared yours and mines, I found 2 different coordinates.

[RyoHazuki]

Here you have good ones, i prefer redo it before find an error in which you made.


RyoHazuki_fromGedmatch,0.12616133,0.13524670,0.055 16950,0.03403950,0.04169355,0.01334780,0.00250243, 0.00352970,0.00898120,0.00606903,-0.00443933,0.00537120,-0.01104390,-0.01121908,0.01619408,0.00228373,-0.00616880,0.00124860,0.00253925,-0.00027628,0.00402963,0.00132225,0.00304010,0.0124 8433,0.00170808

Target: RyoHazuki_fromGedmatch
Distance: 0.0000% / 0.00000002
50.0 Shetlandic
25.0 Dutch
25.0 Spanish_Murcia

Thank you so much.

[gixajo]

Waiting until 1st July but would be fun if someone could help me out with this.

1 Kurdish + Lebanese_Muslim + Mozabite_Berber + Mozabite_Berber @ 2.893268

Sorry, i didn´t see you till now.

Scaled coordinates.


Elias.99_fromGedmatch,0.01047908,0.13018438,-0.02832950,-0.06205145,-0.00161953,-0.02378980,-0.01155330,0.00328358,0.02340485,0.01268818,0.0044 7650,-0.00425593,0.01438428,-0.00801835,0.00684703,-0.00366435,-0.00149413,-0.01040260,-0.02134435,0.00200613,-0.00759393,-0.01999358,0.01162658,-0.00235753,0.00335768

And checking results with used samples names.

Target: Elias.99_fromGedmatch
Distance: 0.0000% / 0.00000002
50.0 Mozabite
25.0 Kurdish
25.0 Lebanese_Muslim

[gixajo]

Thank you so much.

You´re welcome.

[RyoHazuki]

i have compared yours and mines, I found 2 different coordinates.

It's actually quite similar to what I really get

Individual


Target: RyoHazuki_fromGedmatch
Distance: 0.4969% / 0.00496923 | ADC: 0.5x
27.8 Afrikaner
24.2 Welsh
14.0 Belgian
12.4 French_Occitanie
12.2 French_Brittany
8.0 Irish
1.4 English_Cornwall


Top 4


Distance to: Ryo_scaled
0.03018375 English
0.03171045 Scottish
0.03328919 Welsh
0.03438256 RyoHazuki_fromGedmatch
0.03474354 French_Brittany
0.03498638 Irish
0.03537730 Afrikaner
0.03590789 Danish
0.03816967 Belgian
0.03889071 German
0.03975137 French_Nord
0.04142096 French_Alsace
0.04271912 French_Seine-Maritime
0.04335415 Swiss_German
0.04360312 French_Paris
0.04424640 Swedish
0.04443804 Norwegian
0.04492454 French_Pas-de-Calais
0.04620065 German_East
0.04896195 Austrian
0.05087806 French_Occitanie
0.05472363 French_Auvergne
0.05558481 Czech
0.05560534 Hungarian
0.05893281 Slovenian


With Shetland, Netherlands, and Murcia removed


Target: RyoHazuki_fromGedmatch
Distance: 0.7117% / 0.00711693 | ADC: 0.5x
48.4 Belgian
16.6 French_Brittany
16.2 Afrikaner
15.2 Welsh
3.6 Danish

Distance to: RyoHazuki_fromGedmatch
0.01214104 Belgian
0.01266847 French_Brittany
0.01568214 Welsh
0.01664778 Afrikaner
0.01690248 French_Nord
0.01825763 German
0.01832764 English
0.02022381 French_Pas-de-Calais
0.02036080 French_Alsace
0.02050083 Scottish
0.02113260 French_Paris
0.02310586 Swiss_German
0.02332762 Irish
0.02378691 French_Seine-Maritime
0.02701705 Danish
0.02970616 Austrian
0.03033207 Norwegian
0.03240701 French_Occitanie
0.03548896 French_Auvergne
0.03681811 Swedish
0.03810292 Swiss_French
0.03860941 German_East
0.03983036 Hungarian
0.04286320 French_Provence

[gixajo]

Wow is this for real? I wanted to buy G25 coordinates but now I might as well just do this. Yeah can someone do this for me? (pleeeaaase)

And what would be better? Can you help me to choose one? For example:

Eurogenes K13: 1 Bulgarian + Bulgarian + Serbian + Ukrainian_Belgorod @ 2.184501
PuntDNAL K13: 1 French + Norwegian + Orcadian + Turkish_Aydin @ 2.122946
Dodecad K12b: 1 Belorussian_Behar + Belorussian_Behar + Kumyks_Yunusbayev + Sardinian_HGDP @ 2.121763
Harappaworld: 1 belorussian_behar + lithuanian_behar + north-ossetian_yunusbayev + sardinian_hgdp @ 1.425610
Gedrosia K12: 1 BA_Sintashta + Sardinian + Turks_Istanbul + Turks_Istanbul @ 2.760295
PuntDNAL K12 Modern: 1 Balkar + Russian + Sardinian + Scottish_West @ 1.105825
MDLP K23b: 1 Kosovar_ + Kosovar_ + Mordovian_ + South_German_ @ 1.737589

Here you have, delete the first coordinates I give you, I see that I made something wrong because i used a different method to check them.


Chris596_fromGedmatch,0.12674963,0.13287928,0.0391 6805,0.02052578,0.02919458,0.00565800,0.00590428,0 .00585000,-0.00056930,-0.00112003,-0.00234868,-0.00163760,0.00596498,0.01274340,-0.01318445,-0.00276008,0.00628353,0.00075653,0.00338993,-0.00265770,-0.00539213,-0.00159925,0.00442698,-0.00202065,-0.00107093

tomorrow if i have some time to do it, I will check first coordinates I mgave, because they could be wrong too.

[gixajo]

It's actually quite similar to what I really get

Individual


Target: RyoHazuki_fromGedmatch
Distance: 0.4969% / 0.00496923 | ADC: 0.5x
27.8 Afrikaner
24.2 Welsh
14.0 Belgian
12.4 French_Occitanie
12.2 French_Brittany
8.0 Irish
1.4 English_Cornwall


Top 4


Distance to: Ryo_scaled
0.03018375 English
0.03171045 Scottish
0.03328919 Welsh
0.03438256 RyoHazuki_fromGedmatch
0.03474354 French_Brittany
0.03498638 Irish
0.03537730 Afrikaner
0.03590789 Danish
0.03816967 Belgian
0.03889071 German
0.03975137 French_Nord
0.04142096 French_Alsace
0.04271912 French_Seine-Maritime
0.04335415 Swiss_German
0.04360312 French_Paris
0.04424640 Swedish
0.04443804 Norwegian
0.04492454 French_Pas-de-Calais
0.04620065 German_East
0.04896195 Austrian
0.05087806 French_Occitanie
0.05472363 French_Auvergne
0.05558481 Czech
0.05560534 Hungarian
0.05893281 Slovenian


With Shetland, Netherlands, and Murcia removed


Target: RyoHazuki_fromGedmatch
Distance: 0.7117% / 0.00711693 | ADC: 0.5x
48.4 Belgian
16.6 French_Brittany
16.2 Afrikaner
15.2 Welsh
3.6 Danish

Distance to: RyoHazuki_fromGedmatch
0.01214104 Belgian
0.01266847 French_Brittany
0.01568214 Welsh
0.01664778 Afrikaner
0.01690248 French_Nord
0.01825763 German
0.01832764 English
0.02022381 French_Pas-de-Calais
0.02036080 French_Alsace
0.02050083 Scottish
0.02113260 French_Paris
0.02310586 Swiss_German
0.02332762 Irish
0.02378691 French_Seine-Maritime
0.02701705 Danish
0.02970616 Austrian
0.03033207 Norwegian
0.03240701 French_Occitanie
0.03548896 French_Auvergne
0.03681811 Swedish
0.03810292 Swiss_French
0.03860941 German_East
0.03983036 Hungarian
0.04286320 French_Provence


You can try it with other or the same calculator oracle results in Gedmatch to see what of them get closer distances, i have only try with my K13 and K15, my k13 get my first distance, , but not with k15.

[Luso]

Not sure how to do this but here is my k13 population:

1 Portuguese + Portuguese + Spanish_Castilla_Y_Leon + Spanish_Castilla_Y_Leon @ 2.888674

THANK YOU GIXAJO :)

[Mingle]

Greek_Thessaly+Lithuanian_RA+Moldovan+Moldovan


Knez01_fromK13,0.12552655,0.13116285,0.04432470,0. 02515673,0.02932083,0.01025415,0.00680238,0.007301 55,-0.00161180,-0.00440953,-0.00096390,-0.00307803,0.00670888,0.01596588,-0.01154060,-0.00246875,0.00434253,-0.00066360,0.00397953,-0.00114480,-0.00511258,-0.00105368,0.00516258,-0.00155078,-0.00109075

The Moldovan on G25 is different to the one on K13. The K13 one is more northern/Slavic-shifted.

[andre]

Bro, could you try it with these?

ashkenazy-jew_behar + hungarian_behar + mordovian_yunusbayev + tuscan_hgdp @ 1.568903

[gixajo]

Not sure how to do this but here is my k13 population:

1 Portuguese + Portuguese + Spanish_Castilla_Y_Leon + Spanish_Castilla_Y_Leon @ 2.888674

THANK YOU GIXAJO :)

Scaled.


Luso_fromGedmatch,0.10696320,0.14423905,0.03824240 ,-0.00329245,0.04296985,-0.00109505,-0.00273225,0.00368740,0.02701345,0.02947965,-0.00153085,0.00763220,-0.01241415,-0.01164105,0.01240840,-0.00346940,-0.00395565,-0.00130910,-0.00514350,-0.00126895,0.00071445,-0.00173935,0.00130810,-0.00185145,-0.00142965

Target: Luso_fromGedmatch
Distance: 0.0000% / 0.00000000
50.0 Portuguese
50.0 Spanish_Castilla_Y_Leon

[gixajo]

Bro, could you try it with these?

ashkenazy-jew_behar + hungarian_behar + mordovian_yunusbayev + tuscan_hgdp @ 1.568903

Choose which Ashkenazi sample fits better with your origins, there is not any Ashkenazy average, I could do it but probably there are a lot of differences among them and mean would be too strange for any individual.



Ashkenazi_Belarussia,0.1019155,0.1339716,-0.0073393,-0.0395799,0.0107712,-0.0144595,-0.0010123,-0.0010294,0.0057267,0.0146208,0.0024485,-0.0003688,0.00231,-0.001461,-0.002944,0.0027944,0.0018154,-0.0003409,0.0014889,-0.0012602,-0.0038586,-0.0007705,0.0027399,0.0015665,-0.0002949
Ashkenazi_Germany,0.0973188,0.1423773,-0.014406,-0.0499358,0.010925,-0.0187694,-0.001974,-0.0017538,0.0098579,0.0188432,0.0039622,-0.0011239,0.0025123,-0.0026699,-0.0050489,0.0030892,0.0022035,-0.0016977,-0.0007794,-0.0011255,-0.0033441,-0.0026957,0.0008751,0.0013857,0.0008143
Ashkenazi_Lithuania,0.0998539,0.1327575,-0.0092224,-0.040375,0.0094843,-0.0141475,-0.0005555,-0.001175,0.0060613,0.0137009,0.0015499,-0.0018529,0.0025678,0.0006257,-0.0044417,0.0034595,0.0016001,0.0001612,0.0004455,-0.0031721,-0.0032555,-0.0033497,0.0029245,0.0024428,-0.001056
Ashkenazi_Poland,0.1001169,0.1368425,-0.0073382,-0.0429994,0.0097966,-0.0154087,-0.0008812,-0.0008942,0.0081981,0.0142751,0.0011639,-0.0005932,0.0028802,0.0001662,-0.0041451,-0.001674,-0.0037648,3.18e-05,-0.0008065,-0.0040645,-0.0026776,-0.0022721,0.0016895,0.002169,0.0015267
Ashkenazi_Russia,0.1011888,0.131511,-0.0064488,-0.0382755,0.0103711,-0.014335,-0.0019505,-0.0001847,0.0065447,0.0140506,0.0011205,0.0002997, 0.0021408,0.0003303,-0.0050352,-0.0002651,-0.0012125,-0.0005701,-0.0021367,-0.0031266,-0.0035687,-0.0029553,0.0006286,0.0045788,-0.0012214
Ashkenazi_Ukraine,0.0994244,0.1351162,-0.005506,-0.0401166,0.0120483,-0.0142652,-0.0010928,0.0001154,0.007772,0.0129388,0.0008038,0 .0001125,0.0024156,0.0005229,-0.0028297,-0.0018297,-0.0043223,-1.9e-05,0.0012758,-0.0046772,-0.0031258,-0.0025904,0.0007702,0.0021028,0.0010059

[andre]

Choose which Ashkenazi sample fits better with your origins, there is not any Ashkenazy average, I could do it but probably there are a lot of differences among them and mean would be too strange for any individual.



Ashkenazi_Belarussia,0.1019155,0.1339716,-0.0073393,-0.0395799,0.0107712,-0.0144595,-0.0010123,-0.0010294,0.0057267,0.0146208,0.0024485,-0.0003688,0.00231,-0.001461,-0.002944,0.0027944,0.0018154,-0.0003409,0.0014889,-0.0012602,-0.0038586,-0.0007705,0.0027399,0.0015665,-0.0002949
Ashkenazi_Germany,0.0973188,0.1423773,-0.014406,-0.0499358,0.010925,-0.0187694,-0.001974,-0.0017538,0.0098579,0.0188432,0.0039622,-0.0011239,0.0025123,-0.0026699,-0.0050489,0.0030892,0.0022035,-0.0016977,-0.0007794,-0.0011255,-0.0033441,-0.0026957,0.0008751,0.0013857,0.0008143
Ashkenazi_Lithuania,0.0998539,0.1327575,-0.0092224,-0.040375,0.0094843,-0.0141475,-0.0005555,-0.001175,0.0060613,0.0137009,0.0015499,-0.0018529,0.0025678,0.0006257,-0.0044417,0.0034595,0.0016001,0.0001612,0.0004455,-0.0031721,-0.0032555,-0.0033497,0.0029245,0.0024428,-0.001056
Ashkenazi_Poland,0.1001169,0.1368425,-0.0073382,-0.0429994,0.0097966,-0.0154087,-0.0008812,-0.0008942,0.0081981,0.0142751,0.0011639,-0.0005932,0.0028802,0.0001662,-0.0041451,-0.001674,-0.0037648,3.18e-05,-0.0008065,-0.0040645,-0.0026776,-0.0022721,0.0016895,0.002169,0.0015267
Ashkenazi_Russia,0.1011888,0.131511,-0.0064488,-0.0382755,0.0103711,-0.014335,-0.0019505,-0.0001847,0.0065447,0.0140506,0.0011205,0.0002997, 0.0021408,0.0003303,-0.0050352,-0.0002651,-0.0012125,-0.0005701,-0.0021367,-0.0031266,-0.0035687,-0.0029553,0.0006286,0.0045788,-0.0012214
Ashkenazi_Ukraine,0.0994244,0.1351162,-0.005506,-0.0401166,0.0120483,-0.0142652,-0.0010928,0.0001154,0.007772,0.0129388,0.0008038,0 .0001125,0.0024156,0.0005229,-0.0028297,-0.0018297,-0.0043223,-1.9e-05,0.0012758,-0.0046772,-0.0031258,-0.0025904,0.0007702,0.0021028,0.0010059

Germany please.

[andre]

Scaled.


Luso_fromGedmatch,0.10696320,0.14423905,0.03824240 ,-0.00329245,0.04296985,-0.00109505,-0.00273225,0.00368740,0.02701345,0.02947965,-0.00153085,0.00763220,-0.01241415,-0.01164105,0.01240840,-0.00346940,-0.00395565,-0.00130910,-0.00514350,-0.00126895,0.00071445,-0.00173935,0.00130810,-0.00185145,-0.00142965

Target: Luso_fromGedmatch
Distance: 0.0000% / 0.00000000
50.0 Portuguese
50.0 Spanish_Castilla_Y_Leon

Target: Luso_fromGedmatch
Distance: 1.6848% / 0.01684758 | ADC: 0.5x
40.6 Celtic_2
26.2 Celtic_6
21.2 Celtic_5
8.6 North_African_1
3.4 Greco-Roman_2

[andre]

Waiting until 1st July but would be fun if someone could help me out with this.

1 Kurdish + Lebanese_Muslim + Mozabite_Berber + Mozabite_Berber @ 2.893268

Target: Elias.99_fromGedmatch
Distance: 1.8407% / 0.01840748 | ADC: 0.5x
49.6 North_African_1
20.8 Iranic_1
14.8 Levantine_2
14.8 Old_Arabic&Egyptian_2

[gixajo]

Germany please.

Scaled, as always.


Andre_FromGedmatch_2,0.11739858,0.12567708,0.03190 933,0.00777598,0.02404913,0.00120988,0.00343825,0. 00428308,0.00356455,0.00247845,0.00073595,-0.00194318,0.00320548,0.00385553,-0.00591418,0.00062483,0.00235960,-0.00066525,0.00153430,-0.00142553,-0.00261570,-0.00043518,0.00204595,0.00083783,0.00039185

Target: Andre_FromGedmatch_2
Distance: 0.0080% / 0.00008015
25.4 Hungarian
25.2 Ashkenazi_Germany
24.8 Mordovian
24.6 Italian_Tuscany

I don´t see any fail in means, so probably the distance is less close due to homogeneization of all samples used to 8 decimals, still very accurate and close, so they are ok.

[andre]

Scaled, as always.


Andre_FromGedmatch_2,0.11739858,0.12567708,0.03190 933,0.00777598,0.02404913,0.00120988,0.00343825,0. 00428308,0.00356455,0.00247845,0.00073595,-0.00194318,0.00320548,0.00385553,-0.00591418,0.00062483,0.00235960,-0.00066525,0.00153430,-0.00142553,-0.00261570,-0.00043518,0.00204595,0.00083783,0.00039185

Target: Andre_FromGedmatch_2
Distance: 0.0080% / 0.00008015
25.4 Hungarian
25.2 Ashkenazi_Germany
24.8 Mordovian
24.6 Italian_Tuscany

I don´t see any fail in means, so probably the distance is less close due to homogeneization of all samples used to 8 decimals, still very accurate and close, so they are ok.

Target: Andrei_scaled
Distance: 3.3830% / 0.03382977 | ADC: 0.25x
54.4 Mediterranean
45.6 Slavic

Target: andre_fromGedmatch
Distance: 1.5673% / 0.01567285 | ADC: 0.25x
49.8 Mediterranean
49.6 Slavic
0.6 Kipchak

Target: Andre_FromGedmatch_2
Distance: 1.0073% / 0.01007335 | ADC: 0.25x
55.8 Mediterranean
37.6 Slavic
4.8 Kipchak
1.8 Germanic

[gixajo]

Target: Andrei_scaled
Distance: 3.3830% / 0.03382977 | ADC: 0.25x
54.4 Mediterranean
45.6 Slavic

Target: andre_fromGedmatch
Distance: 1.5673% / 0.01567285 | ADC: 0.25x
49.8 Mediterranean
49.6 Slavic
0.6 Kipchak

Target: Andre_FromGedmatch_2
Distance: 1.0073% / 0.01007335 | ADC: 0.25x
55.8 Mediterranean
37.6 Slavic
4.8 Kipchak
1.8 Germanic

Are those results relatively consistent for you?

You can't ask for much more precision either, the differences between one and the other coordinates are understandable.

The best thing would be to try many oracles from different calculators, and find the one that is closest to reality.

So what I wanted from the beginning was to show the method, and that each one make their own coordinates, trying many different calculators and oracles, until finding the most suitable one.

But I suppose that the way in which these coordinates are presented to us, make them difficult to operate, or at least uncomfortable, and people do not want to waste their time finding out,
even less if there is someone who does them for them..;)

[Luso]

Target: Andrei_scaled
Distance: 3.3830% / 0.03382977 | ADC: 0.25x
54.4 Mediterranean
45.6 Slavic

Target: andre_fromGedmatch
Distance: 1.5673% / 0.01567285 | ADC: 0.25x
49.8 Mediterranean
49.6 Slavic
0.6 Kipchak

Target: Andre_FromGedmatch_2
Distance: 1.0073% / 0.01007335 | ADC: 0.25x
55.8 Mediterranean
37.6 Slavic
4.8 Kipchak
1.8 Germanic

which calculator are you using on vahaduo?

[andre]

which calculator are you using on vahaduo?

Created by me (ITA_Rome_Late_Antiquity+Avar_Szolad+KAZ_Kipchak+D EU_Ma)

[Dlav]

How do you do it the mean? I have 4 populations ready

[gixajo]

If all of you who have "alternative" coordinates and after that you get the official ones from Davidsky, could post your 10 first distances with both coordinates, running modern averages scaled calculator, please.

I am curious to know how they approached reality.

In any case, the method is supposed to consist of trying several different calculators and oracles, and here practically all of you have coordinates based on a single oracle of a single calculator.

Possibly if each one of you were making coordinates with this method and compared them with the real ones, some of the oracles would give a better match than the ones you have.

Or maybe we just happened to find the right mix of populations the first time.

In any case, what is inimitable from the real ones would be the distances, since the alternative coordinates, being made with means over references from the original datasheet, will always be excessively small.

Thanks to all, this has been very entertaining for me.:thumb001:

[gixajo]

Better than post both distance lists, please post yourselves how many populations and how many population order were hit comparing both lists , only among the first 10 population distances.

Thanks again.

[Luso]

If all of you who have "alternative" coordinates and after that you get the official ones from Davidsky, could post your 10 first distances with both coordinates, running modern averages scaled calculator, please.

I am curious to know how they approached reality.

In any case, the method is supposed to consist of trying several different calculators and oracles, and here practically all of you have coordinates based on a single oracle of a single calculator.

Possibly if each one of you were making coordinates with this method and compared them with the real ones, some of the oracles would give a better match than the ones you have.

Or maybe we just happened to find the right mix of populations the first time.

In any case, what is inimitable from the real ones would be the distances, since the alternative coordinates, being made with means over references from the original datasheet, will always be excessively small.

Thanks to all, this has been very entertaining for me.:thumb001:

For some reason... the G25 Modern avg code freezes my computer. Could you just send the code to me here? I'll show you the comparison.

[gixajo]

For some reason... the G25 Modern avg code freezes my computer. Could you just send the code to me here? I'll show you the comparison.

I don´t know what you men with"send the code " to you?

Post here all the sources? Post here a link to that calculator?

[Luso]

I don´t know what you men with"send the code " to you?

Post here all the sources? Post here a link to that calculator?

This one freezes: http://g25vahaduo.genetics.ovh/G25modern-scaled-averages.htm

[gixajo]

This one freezes: http://g25vahaduo.genetics.ovh/G25modern-scaled-averages.htm

I understand that, but I don´t understand what do you want me to do, run it with your coordinates in my PC?

[Luso]

I don´t know what you men with"send the code " to you?

Post here all the sources? Post here a link to that calculator?

NVM I GOT IT!

Okay so.... Official G25 with Modern Calculator:

Target: Josef_scaled
Distance: 1.5970% / 0.01597034
40.4 Spanish_Asturias
18.8 Italian_Liguria
16.0 Basque_French
6.0 German_East
5.6 Sardinian
5.4 Berber_Tunisia_Chen
2.4 Mari
2.2 Spanish_Castilla_Y_Leon
2.0 Ethiopian_Agaw
0.8 Biaka
0.4 Gupta

Distance to: Josef_scaled
0.02534072 Spanish_Castilla_Y_Leon
0.02715626 Spanish_Andalucia
0.02868336 Portuguese
0.02927137 Spanish_Galicia
0.02962993 Spanish_Asturias
0.03067866 Spanish_Extremadura
0.03143928 Spanish_Murcia
0.03222368 Spanish_Castilla_La_Mancha
0.03346217 Spanish_Canarias
0.03369607 Spanish_Eivissa
0.03401931 Spanish_Menorca
0.03465368 Spanish_Alacant
0.03518269 Spanish_Valencia
0.03582007 Spanish_Cataluna
0.03722806 Spanish_Terres_de_l'Ebre
0.03726135 Spanish_Aragon
0.03748683 Spanish_Baleares
0.03849595 Spanish_Mallorca
0.03862101 Spanish_Barcelones
0.03877322 Spanish_Camp_de_Tarragona
0.03913698 Spanish_Lleida
0.03927272 Spanish_Pirineu
0.03990329 Spanish_Cantabria
0.03996741 Spanish_Peri-Barcelona
0.04139247 Spanish_Girona



Gedmatch alternative G25:

Target: Luso_fromGedmatch
Distance: 0.1057% / 0.00105659
43.2 Spanish_Castilla_Y_Leon
18.6 Portuguese
8.2 Basque_Spanish
5.8 Spanish_Aragon
3.6 Berber_Tunisia_Chen
3.0 Sardinian
3.0 Shetlandic
2.4 Swiss_German
2.2 Spanish_Menorca
2.2 Welsh
2.0 French_Seine-Maritime
1.4 French_Paris
1.4 Italian_Trentino-Alto-Adige
1.2 Moroccan_North
0.6 Greek_Central_Anatolia
0.4 Italian_Molise
0.2 Georgian_Imer
0.2 Kol
0.2 Tunisian_Jew
0.2 Yemenite_Mahra

Distance to: Luso_fromGedmatch
0.00659819 Portuguese
0.00659819 Spanish_Castilla_Y_Leon
0.00880114 Spanish_Galicia
0.01005931 Spanish_Andalucia
0.01470553 Spanish_Extremadura
0.01521205 Spanish_Castilla_La_Mancha
0.01580834 Spanish_Eivissa
0.01598394 Spanish_Alacant
0.01638481 Spanish_Murcia
0.01651842 Spanish_Valencia
0.01824651 Spanish_Aragon
0.01885407 Spanish_Cataluna
0.01889667 Spanish_Menorca
0.01967974 Spanish_Camp_de_Tarragona
0.01996912 Spanish_Baleares
0.02087294 Spanish_Mallorca
0.02095968 Spanish_Peri-Barcelona
0.02105147 Spanish_Pirineu
0.02134808 Spanish_Terres_de_l'Ebre
0.02207196 Spanish_Lleida
0.02241703 Spanish_Girona
0.02313001 Spanish_Penedes
0.02371341 Spanish_Barcelones
0.02400675 Spanish_Castello
0.02417981 Spanish_Cantabria

[gixajo]

What a surprise,you are... Portuguese!!!

:D

[Defcon2]

Better than post both distance lists, please post yourselves how many populations and how many population order were hit comparing both lists , only among the first 10 population distances.

Thanks again.

Ola soi nuebo

Distance to: K13
0.01354015 Spanish_Canarias
0.03093675 Portuguese
0.03164336 Spanish_Extremadura
0.03220810 Spanish_Andalucia
0.03364169 Spanish_Castilla_Y_Leon
0.03423069 Spanish_Galicia
0.03565839 Spanish_Murcia
0.04038734 Spanish_Alacant
0.04085434 Spanish_Castilla_La_Mancha
0.04189686 Spanish_Asturias
0.04281337 Spanish_Eivissa
0.04308554 Spanish_Valencia
0.04371216 Spanish_Menorca
0.04385688 Spanish_Cataluna
0.04588789 Spanish_Aragon
0.04632615 Spanish_Baleares
0.04783552 Spanish_Camp_de_Tarragona
0.04784415 Spanish_Navarra
0.04813912 Spanish_Pirineu
0.04839532 Spanish_Mallorca
0.04883639 Spanish_Terres_de_l'Ebre
0.04884707 Spanish_Castello
0.04895861 Spanish_Cantabria
0.04932377 Spanish_Peri-Barcelona
0.05031497 Spanish_Barcelones

Target: K13
Distance: 0.8463% / 0.00846336 | ADC: 0.25x
78.0 Spanish_Canarias
14.2 Basque_French
3.8 Spanish_Asturias
2.4 Moroccan_South
1.4 Sardinian
0.2 Eritrean

Distance to: Juan_scaled
0.02910453 Spanish_Castilla_Y_Leon
0.03060658 Spanish_Andalucia
0.03207120 Spanish_Murcia
0.03254586 Portuguese
0.03321372 Spanish_Extremadura
0.03357197 Spanish_Galicia
0.03396093 Spanish_Asturias
0.03519913 Spanish_Castilla_La_Mancha
0.03564540 Spanish_Valencia
0.03572431 Spanish_Aragon
0.03575547 Spanish_Alacant
0.03579724 Spanish_Menorca
0.03689213 Spanish_Eivissa
0.03726761 Spanish_Baleares
0.03763331 Spanish_Cataluna
0.03866352 Spanish_Cantabria
0.03918715 Spanish_Terres_de_l'Ebre
0.03940735 Spanish_Pirineu
0.04021304 Spanish_Barcelones
0.04023849 Spanish_Mallorca
0.04029485 Spanish_Canarias
0.04040945 Spanish_Peri-Barcelona
0.04043393 Spanish_Lleida
0.04043567 Spanish_Navarra
0.04049958 Spanish_Camp_de_Tarragona

Target: Juan_scaled
Distance: 2.0368% / 0.02036820 | ADC: 0.25x
39.8 Spanish_Castilla_Y_Leon
39.4 Spanish_Asturias
8.6 Sardinian
7.8 Italian_Lombardy
3.0 Gupta
1.0 Baka
0.2 Cameroon_Bangwa
0.2 Italian_Bergamo

[gixajo]

Ola soi nuebo




I swear I'm not responsible for that coordinate nightmare!!!:eek:

[Beowulf]

te podria pedir el mio? North_Italian + Portuguese + Spanish_Galicia + Spanish_Valencia @ 3.033611


y el k15: French_Basque + French_Basque + Libyan_Jewish + Southwest_French @ 4.537610

[J.S.]

These would be your scaled coordinates:


Schwop_fromK13,0.13174588,0.12088580,0.07458703,0. 06142590,0.03868860,0.02191873,0.00748860,0.010548 30,0.00357365,-0.01182523,-0.00211280,-0.00181365,0.00321303,0.00473933,0.00664963,0.0005 2630,-0.00721523,0.00128703,0.00316880,0.00245710,0.0036 7430,0.00067810,0.00272143,0.00596593,0.00062950

Made with more similar population samples I found in average pop, sorry, not North_Swedish or SouthWest_Finnish.

Belarusian+Swedish+English_Cornwall+Finnish

Can you help me amigo? i might be French but not so bright.
1 French + French_Basque + Southeast_English + Spanish_Valencia @ 3.350345 with MH kit

If you are willing to, here is the K13 of my 23andMe kit i have already the G25 coordinates in order to compare the accuracy of your method.
1 French_Basque + North_Swedish + Spanish_Aragon + Spanish_Castilla_Y_Leon @ 3.062119

In advance thanks, bro, for your kindness.

[Beowulf]

te podria pedir el mio? North_Italian + Portuguese + Spanish_Galicia + Spanish_Valencia @ 3.033611


y el k15: French_Basque + French_Basque + Libyan_Jewish + Southwest_French @ 4.537610

[Dušan]

I hope this method helps someone, and remember that this does not replace authentic G25 coordinates made with your raw data directly.



Can you make for me?

K13
1 Erzya + Moldavian + Sardinian + Ukrainian_Belgorod @ 3.963264

K15
1 Croatian + Greek + Moldavian + Russian_Smolensk @ 3.228230

[rothaer]

(...)

An extremely smart and simple approach, respect!


As a point of interest, comparation among different coordinates made with this method(K13,K15 and a mean between both, ) and real G25 coordinates (gixajo_scaled).

i used this model:

http://g25vahaduo.genetics.ovh/ULTIMATE%20ANCIENT%20COMPONENTS.htm

https://i.imgur.com/5rSMWR6.png

I don't know whether I maybe missed it, but did you also show the distance between your real G25 coords and the various simulated ones? (You can simply put the simulated ones in the source and the real one in the target.) What you show here is something else.

And another question. Afaik MDLP K23b is the GEDmatch calculator with the plentiest components among those with an oracle. I would expect that one to cause the best fitting model as it checks 23 components. Thoughts?

[Kyp]

As far as I know the website Genoplot (https://genoplot.com/) allows you to generate G25 coordinates from your gedmatch result automatically.

For people who want to average g25 coordinates quickly this could be a useful tool:

https://dnplay.github.io/g25play.html

[gixajo]

An extremely smart and simple approach, respect!



I don't know whether I maybe missed it, but did you also show the distance between your real G25 coords and the various simulated ones? (You can simply put the simulated ones in the source and the real one in the target.) What you show here is something else.

Yes, I did it and in my case my simulated coordinates were the first in my distance list fo whole G25 datasheet (of that times, in the present one maybe something has changed).

Distance list were I show what I say is in the spoiler of the initial post.

I open a thread when people I gave this type of simulated coordinates posted their distance list of the simulated coordinates and the real coordinates distance list , of the modern averages pop whole datasheet.

In some cases it was similar, in other cases some populations changed the position in that list.


And another question. Afaik MDLP K23b is the GEDmatch calculator with the plentiest components among those with an oracle. I would expect that one to cause the best fitting model as it checks 23 components. Thoughts?

I advised that each person can make their simulated coordinates using the Gedmatch calculator that seemed most accurate based on their known ancestry. It can be done with any Gedmatch calculator, even mixing different calculators.

I offered this as a temporary solution for people who wanted to have some G25 coordinates to use in models that we published when Davidski stopped making G25 coordinates for a few months.

The only problem that these simulated coordinates offer is that since they are made with means of datasheet references, in any model/calculator in which some of the references used to elaborate them are in the sources, the distances will be extremely close.

Anyway, more realistic distances can be made, using a multiplier factor that alters each individual coordinate enough, so that the distances increase when that type of reference is used in the sources.

Also alterning averages with individual references, etc...

Finally, these coordinates do not replace or intend to replace the real ones, they are just alternative coordinates, which can emulate the results of the real ones, but obviously they are not.

[gixajo]

As far as I know the website Genoplot (https://genoplot.com/) allows you to generate G25 coordinates from your gedmatch result automatically.

For people who want to average g25 coordinates quickly this could be a useful tool:

]

These ones work better than mine in most cases, although it would not be bad if they are inspired by my method, at least they told me.

After all, I offered the method for free to everyone, and I made "alternative" coordinates for free to everyone who asked me for them (about 40 people).

:)

[rothaer]

Yes, I did it and in my case my simulated coordinates were the first in my distance list fo whole G25 datasheet (of that times, in the present one maybe something has changed).

Distance list were I show what I say is in the spoiler of the initial post.

Thanks.


Also alterning averages with individual references, etc...

Wow, yes, of course! Interesting as I do have G25 coords for a number of family members, while for others not.


Finally, these coordinates do not replace or intend to replace the real ones, they are just alternative coordinates, which can emulate the results of the real ones, but obviously they are not.

Absolutely agreed. I actually disliked simulated G25 coords to show up, because I'm afraid that they will mingle into other data, eventually lose their label and contaminate spreadsheets. Yes, what you say here should be emphasized.

[gixajo]

Can you help me amigo? i might be French but not so bright.
1 French + French_Basque + Southeast_English + Spanish_Valencia @ 3.350345 with MH kit

If you are willing to, here is the K13 of my 23andMe kit i have already the G25 coordinates in order to compare the accuracy of your method.
1 French_Basque + North_Swedish + Spanish_Aragon + Spanish_Castilla_Y_Leon @ 3.062119

In advance thanks, bro, for your kindness.

Tell me how they work with your real ones, they are slighty different between them.

23 and Me kit:


JS_scaled:K13_23andMe_sim,0.1254662,0.1449606,0.05 14051,0.0173761,0.0424227,0.0064151,0.0011299,0.00 7022,0.0188764,0.0223407,-0.0025628,0.0074965,-0.0120505,-0.0133897,0.0125587,0.0016798,-0.0055312,0.000947,0.0015754,-0.0021672,0.0028104,0.0023488,-0.0025851,0.0046738,-0.0010855

My Heritage kit:


JS_scaled:K13_MH_sim,0.1263061,0.143994,0.0511094, 0.0106383,0.0476505,0.0079919,-0.0014507,0.0034041,0.0180317,0.0265947,-0.0042307,0.0086082,-0.0144778,-0.0109794,0.009933,0.0025109,-0.0028836,-0.0001354,-0.0012047,-0.002732,0.0030459,0.0017536,-0.0032539,0.0019304,0.001349

[gixajo]

Thanks.



Wow, yes, of course! Interesting as I do have G25 coords for a number of family members, while for others not.



Absolutely agreed. I actually disliked simulated G25 coords to show up, because I'm afraid that they will mingle into other data, eventually lose their label and contaminate spreadsheets. Yes, what you say here should be emphasized.

With some method of "blurring" and "refining", simulated coordinates can pass quite well as real, but best option is always ask for real ones to its creator.

It is fair that the one who made an effort receives the merit, and in this case also the money.

[rothaer]

(...)

Btw. do you know what kind of raw data is most suitable for making real G25 coords?

Davidski is not very informative about that. He once rejected merged data from me for calculation and told that whatever commercial data is fine. Also, he told another individual that I know that GSA chip data are fine as well and are not less suitable. For everyone that has worked with GEDmatch calculators and noted the differences not just in results but also in evaluated SNPs this must appear doubtful. When I lately got the G25 coords from Peterska, one time from GSA chip data and one time from OmniExpress chip data and saw the difference, I felt confirmed in that Davidski was talking bs in that context. He just didn't care for a customer to get as applicable coords as possible. Also, it seems absurd to provide such coords with 7 decimal places while the deviation often is 2 already in the third decimal place when you compare the results from GSA chip data with these from OmniExpress chip data.

[gixajo]

I couldn't tell you with what raw data we would get the most accurate coordinates of G25. We could thing that the more SNPs you have, the better, but since the original creator of those coordinates never has given precise information about how those coordinates are made technically, I can't tell anything about that subject.

I can make "educated guesses", conjectures, surmises, but I couldn't speak on solid ground.

I don't know if giving little information about how they are done is intended to prevent anyone from stealing the idea, or to hide possible criticism about the effectiveness of coordinates.

I have never gone beyond emulating G25 coordinates relying on Gedmatch, the attempts I have made trying to assign SNPs have given me quite absurd results.

Maybe someone else can clear your doubts, sorry.

[Khinerai]

My k13
What are my coordinates
Using 3 populations approximation:
1 50% Dai +25% Malay +25% Vietnamese @ 2.133790


Using 4 populations approximation:
++++++++++++++++++++++++++++++++++
1 Dai + Dai + Malay + Vietnamese @ 2.133790
2 Dai + Dai + Dai + Malay @ 2.451613
3 Dai + Malay + Vietnamese + Vietnamese @ 2.614715
4 Cambodian + Cambodian + Dai + Dai @ 2.644325
5 Dai + Dai + Lahu + Malay @ 2.803251
6 Cambodian + Dai + Dai + Vietnamese @ 3.007446
7 Cambodian + Dai + Dai + Malay @ 3.093906
8 Cambodian + Dai + Vietnamese + Vietnamese @ 3.136917
9 Cambodian + Dai + Dai + Lahu @ 3.289280
10 Cambodian + Cambodian + Dai + Vietnamese @ 3.430150
11 Cambodian + Dai + Dai + Dai @ 3.455288
12 Malay + Vietnamese + Vietnamese + Vietnamese @ 3.575135
13 Cambodian + Vietnamese + Vietnamese + Vietnamese @ 3.786680
14 Dai + Lahu + Malay + Vietnamese @ 3.794009
15 Dai + Dai + Malay + Malay @ 3.827342
16 Cambodian + Dai + Malay + Vietnamese @ 3.967831
17 Cambodian + Dai + Lahu + Vietnamese @ 3.989950
18 Dai + Dai + Malay + She @ 4.021276
19 Dai + Dai + Malay + Miaozu @ 4.032020
20 Cambodian + Cambodian + Vietnamese + Vietnamese @ 4.481103

[Beowulf]

My k13
What are my coordinates
Using 3 populations approximation:
1 50% Dai +25% Malay +25% Vietnamese @ 2.133790


Using 4 populations approximation:
++++++++++++++++++++++++++++++++++
1 Dai + Dai + Malay + Vietnamese @ 2.133790
2 Dai + Dai + Dai + Malay @ 2.451613
3 Dai + Malay + Vietnamese + Vietnamese @ 2.614715
4 Cambodian + Cambodian + Dai + Dai @ 2.644325
5 Dai + Dai + Lahu + Malay @ 2.803251
6 Cambodian + Dai + Dai + Vietnamese @ 3.007446
7 Cambodian + Dai + Dai + Malay @ 3.093906
8 Cambodian + Dai + Vietnamese + Vietnamese @ 3.136917
9 Cambodian + Dai + Dai + Lahu @ 3.289280
10 Cambodian + Cambodian + Dai + Vietnamese @ 3.430150
11 Cambodian + Dai + Dai + Dai @ 3.455288
12 Malay + Vietnamese + Vietnamese + Vietnamese @ 3.575135
13 Cambodian + Vietnamese + Vietnamese + Vietnamese @ 3.786680
14 Dai + Lahu + Malay + Vietnamese @ 3.794009
15 Dai + Dai + Malay + Malay @ 3.827342
16 Cambodian + Dai + Malay + Vietnamese @ 3.967831
17 Cambodian + Dai + Lahu + Vietnamese @ 3.989950
18 Dai + Dai + Malay + She @ 4.021276
19 Dai + Dai + Malay + Miaozu @ 4.032020
20 Cambodian + Cambodian + Vietnamese + Vietnamese @ 4.481103

Khinerai,0.0154017,-0.4245231,-0.0510127,-0.0519142,0.1191818,0.058778,-0.0008504,-0.0078257,-0.0164016,-0.012916,0.0205717,0.0023632,-0.0014978,-0.0041054,0.0020639,0.0025556,0.0018067,-0.0003073,-0.002529,-0.0073458,0.0059223,0.0048874,0.0082028,0.0008058, 0.0045713

[Beowulf]

Actually is similar to the real one's:

Target: Beowulf_Gedmatch_method
Distance: 0.0313% / 0.03125482
52.0 TUR_Barcin_N
34.9 Yamnaya_RUS_Samara
11.0 WHG
2.1 MAR_Taforalt




Distance to: Beowulf_Gedmatch_method
0.02069696 France:French_Auvergne:C_5_2
0.02226635 France:French_Auvergne:C_21
0.02395790 Iberian_Penninsula:Spanish_Castilla_Y_Leon:HG01506
0.02442212 France:French_Nord:N_55
0.02463135 Iberian_Penninsula:Spanish_Galicia:GAL3
0.02465764 France:French_Auvergne:C_82
0.02479879 France:French_Auvergne:C_3
0.02488118 France:French_Auvergne:C_30
0.02492303 France:French_Nord:N_60_2
0.02506443 Italy:Italian_Veneto:Alp100
0.02521979 Italy:Italian_Veneto:ALP250
0.02602031 France:French_Auvergne:C_13
0.02613555 France:French_Auvergne:C_19
0.02616987 France:French_Auvergne:C_51
0.02634437 France:French_Auvergne:C_16
0.02639140 France:French_Auvergne:C_35
0.02640802 Iberian_Penninsula:Spanish_Galicia:GAL16
0.02640997 Iberian_Penninsula:Spanish_Barcelones:SER015
0.02650806 Iberian_Penninsula:Spanish_Galicia:GAL74
0.02695110 Iberian_Penninsula:Portuguese:Portugal2
0.02701256 France:French_Auvergne:C_37
0.02703450 Iberian_Penninsula:Spanish_Castilla_Y_Leon:HG01501
0.02748012 Iberian_Penninsula:Portuguese:EBC_Portugal3
0.02752408 Iberian_Penninsula:Spanish_Barcelones:VID014
0.02753163 Iberian_Penninsula:Spanish_Barcelones:COD147



Target: Beowulf_Gedmatch_method
Distance: 0.0531% / 0.00053126 | ADC: 0.25x RC
46.8 Iberian_Penninsula
35.2 France
9.0 Germanic_People_of_CentralEurope
4.6 Balkan
4.4 Italy

[Khinerai]

Khinerai,0.0154017,-0.4245231,-0.0510127,-0.0519142,0.1191818,0.058778,-0.0008504,-0.0078257,-0.0164016,-0.012916,0.0205717,0.0023632,-0.0014978,-0.0041054,0.0020639,0.0025556,0.0018067,-0.0003073,-0.002529,-0.0073458,0.0059223,0.0048874,0.0082028,0.0008058, 0.0045713

Is the first one Dai?

[Beowulf]

Is the first one Dai?

Yes i used the one with the better distances:

1 Dai + Dai + Malay + Vietnamese @ 2.133790 this one

[Eurafricanid]

Distance to: Eurafricanid-EU_Gedmatch-Method_K13_Sim
0.01817227 Spanish_Menorca
0.01861622 Spanish_Castilla_La_Mancha
0.01921790 Spanish_Andalucia
0.01952522 Spanish_Eivissa
0.01970897 Spanish_Murcia
0.02069411 Spanish_Valencia
0.02146603 Spanish_Terres_de_l'Ebre
0.02196118 Spanish_Alacant
0.02252281 Spanish_Baleares
0.02283145 Portuguese
0.02349020 Spanish_Extremadura
0.02353330 Spanish_Cantabria
0.02370644 Spanish_Aragon
0.02387245 Spanish_Pirineu
0.02397956 French_Corsica
0.02428850 Spanish_Peri-Barcelona
0.02432815 Spanish_Galicia
0.02477605 Spanish_La_Rioja
0.02487613 Spanish_Mallorca
0.02511801 Spanish_Castello
0.02583563 Spanish_Lleida
0.02585010 Italian_Bergamo
0.02605485 Spanish_Camp_de_Tarragona
0.02661270 Italian_Lombardy
0.02701176 Spanish_Cataluna


Distance to: Eurafricanid-EU
0.01882838 Spanish_Menorca
0.02030984 Spanish_Eivissa
0.02220080 Spanish_Castilla_La_Mancha
0.02236428 Spanish_Baleares
0.02250190 Spanish_Mallorca
0.02267983 Spanish_Camp_de_Tarragona
0.02340466 Spanish_Terres_de_l'Ebre
0.02386008 Spanish_Peri-Barcelona
0.02402412 Spanish_Valencia
0.02404019 Spanish_Alacant
0.02500269 Spanish_Lleida
0.02519692 Spanish_Andalucia
0.02520435 Spanish_Murcia
0.02532113 Spanish_Catalunya_Central
0.02536405 Italian_Trentino_Alto_Adige
0.02541944 Spanish_Penedes
0.02546727 Italian_Veneto
0.02568090 Spanish_Girona
0.02570855 Spanish_Castello
0.02661283 Italian_Bergamo
0.02679319 Spanish_Extremadura
0.02685691 Spanish_Pirineu
0.02705952 Spanish_Cantabria
0.02779732 French_Provence
0.02780547 Italian_Piedmont

The distances are almost spot on! :eek:


But the ancestral components aren't as close, although pretty good, especially the WHG.

Target: Eurafricanid-EU_Gedmatch-Method_K13_Sim
Distance: 0.0272% / 0.02715180
60.7 Anatolian_Neolithic_Farmer
26.2 Yamnaya_Pastoralist
10.4 Western_Hunter-Gatherer
2.7 North_African_Hunter-Gatherer


Target: Eurafricanid-EU
Distance: 0.0275% / 0.02746042
55.9 Anatolian_Neolithic_Farmer
30.0 Yamnaya_Pastoralist
10.8 Western_Hunter-Gatherer
3.3 Levantine_Neolithic_Farmer

[gixajo]

Was I the first to offer coordinates emulated from the G25?

I don't remember anyone doing anything like that until quite some time later.

As far as I know was Genoplot the first commercial site that started offering something similar related with G25 simulated coordinates...?

Someone knows it?