New Illustrative DNA Deep Modern UNscaled G25

[ScandinavianCelt]

You will need to get unscaled coords from your new coords with them by converting your scaled to unscaled here:

(click the arrows icon on top and paste scaled in there):

https://admixtr.streamlit.app/

Source, UNscaled:

<iframe src="https://pastebin.com/embed_iframe/BXkiekt4" style="border:none;width:50%"></iframe>


Target: SC_Brad_Official_New.Merged_UNscaled
Distance: 0.8226% / 0.00822636 | ADC: 2x RC
100.0 Norwegian

Target: SC_Brad_Official_New.Merged_UNscaled
Distance: 0.7263% / 0.00726274 | ADC: 1x RC
44.4 Norwegian
30.2 English_Kent
25.4 German

Target: SC_Brad_Official_New.Merged_UNscaled
Distance: 0.5478% / 0.00547751 | ADC: 0.5x RC
36.6 Norwegian
23.2 German
22.4 Irish
11.6 French_Bourgogne-Franche-Comte
4.0 Jarawa
2.2 Greenlander_West

Target: SC_Brad_Official_New.Merged_UNscaled
Distance: 0.4205% / 0.00420484 | ADC: 0.25x RC
40.6 Irish
27.6 Norwegian
7.0 Finnish_Southwest
7.0 French_Bourgogne-Franche-Comte
5.8 Ukrainian_Ternopil
4.6 Italian_Liguria
1.8 Greenlander_West
1.8 Zoroastrian_Yazd
1.2 Papuan_Baining
1.2 Sahrawi_Morocco
0.8 Mbuti_Congo
0.6 Jarawa

Target: SC_Brad_Official_New.Merged_UNscaled
Distance: 0.3824% / 0.00382430
38.0 Irish
16.8 Norwegian
15.4 Spanish_Aragon
13.8 Finnish_Southwest
6.2 Ukrainian_Ternopil
3.6 Kaitag_Dagestan
1.6 Greenlander_West
1.2 North_Kannadi
1.0 Swahili_Jomvu
0.8 Mbuti_Congo
0.6 Papuan_Baining
0.4 French_Bourgogne-Franche-Comte
0.4 Papuan
0.2 Ju_Hoansi_Namibia

-------------------

R5P

Target: SC_Brad_Official_New.Merged_UNscaled
Distance: 0.4991% / 0.00499096 | R5P
49.2 Irish
24.0 Finnish_Southwest
18.0 Spanish_Aragon
5.4 Kaitag_Dagestan
3.4 Jarawa

Target: SC_Brad_Official_New.Merged_UNscaled
Distance: 0.5602% / 0.00560228 | R3P
77.0 Irish
18.6 Ukrainian_Ternopil
4.4 Jarawa

----------------------------------------------------------------------

Distance to: SC_Brad_Official_New.Merged_UNscaled
0.00822636 Norwegian
0.00878756 Danish
0.00903610 Dutch
0.00935469 English_Kent
0.00943438 Welsh
0.00987584 Irish
0.00990978 Orcadian
0.00999221 German
0.01015859 Scottish
0.01033414 Icelander
0.01036634 White_American_Utah
0.01041523 English_Cornwall
0.01235977 Swedish
0.01280335 Austrian
0.01311514 French_Bourgogne-Franche-Comte
0.01316212 Breton
0.01441150 French_Hauts-de-France
0.01522144 French_Grand_Est
0.01523818 French
0.01534426 French_Normandy
0.02059505 Italian_Aosta_Valley
0.02075945 French_Provence
0.02176576 Hungarian
0.02184997 Czech
0.02372461 Italian_Friuli-Venezia_Giulia

[Athalafuns]

Target: RNB27
Distance: 1.2290% / 0.01229048 | ADC: 1x RC
65.6 Spanish_Castilla_y_Leon
34.4 French_Provence

Target: RNB27
Distance: 1.1985% / 0.01198467 | R3P
61.8 Spanish_Castilla_y_Leon
35.8 French_Provence
2.4 Greenlander_West

[Xavier727]

Merged data

Target:
Distance: 1.0929% / 0.01092917
64.4 Icelander
20.4 French_Nouvelle-Aquitaine
5.4 Swedish
3.4 Kubachi_Dagestan
3.4 Mari
1.6 Han_Hubei
0.8 Pamiri_Rushan
0.6 Mixe_Mexico

Target:
Distance: 1.0956% / 0.01095568 | ADC: 0.25x RC
63.6 Icelander
17.0 French_Nouvelle-Aquitaine
9.8 English_Cornwall
4.4 Pamiri_Rushan
3.0 Mari
1.6 Han_Hubei
0.6 Mixe_Mexico

Target:
Distance: 1.1364% / 0.01136436 | ADC: 0.5x RC
66.2 Welsh
26.6 Icelander
4.0 Altaian_Chelkan
3.2 Pamiri_Rushan

Target:
Distance: 1.1822% / 0.01182247 | ADC: 1x RC
61.4 Welsh
38.6 Icelander

Target:
Distance: 1.2160% / 0.01215967 | ADC: 2x RC
100.0 Welsh

Target:
Distance: 1.0982% / 0.01098154 | R5P
70.6 Icelander
19.8 French_Nouvelle-Aquitaine
4.0 Mari
3.8 Kubachi_Dagestan
1.8 Han_Hubei


23andme

Target:
Distance: 1.5895% / 0.01589513
44.2 English_Cornwall
40.6 Swedish
7.2 Spanish_Cantabria
3.6 Datog_Tanzania
1.6 Huichol_Mexico
1.6 Sherpa_Nepal
1.0 French_Nouvelle-Aquitaine
0.2 Ju_Hoansi_Namibia

Target:
Distance: 1.5895% / 0.01589536 | ADC: 0.25x RC
45.6 English_Cornwall
39.8 Swedish
7.8 Spanish_Cantabria
3.6 Datog_Tanzania
1.6 Huichol_Mexico
1.6 Sherpa_Nepal

Target:
Distance: 1.6213% / 0.01621333 | ADC: 0.5x RC
58.0 English_Cornwall
37.4 Swedish
4.6 Datog_Tanzania

Target:
Distance: 1.7065% / 0.01706465 | ADC: 1x RC
38.8 Dutch
38.6 Norwegian
22.6 Welsh

Target:
Distance: 1.7090% / 0.01709045 | ADC: 2x RC
59.2 Dutch
40.8 Norwegian

Target:
Distance: 1.5934% / 0.01593426 | R5P
43.6 English_Cornwall
41.8 Swedish
9.0 Spanish_Cantabria
4.0 Datog_Tanzania
1.6 Huichol_Mexico


I don’t think these new coordinates are quite as accurate tbh, do you think your new ones are any better?

[ScandinavianCelt]

Merged data

Target:
Distance: 1.0929% / 0.01092917
64.4 Icelander
20.4 French_Nouvelle-Aquitaine
5.4 Swedish
3.4 Kubachi_Dagestan
3.4 Mari
1.6 Han_Hubei
0.8 Pamiri_Rushan
0.6 Mixe_Mexico

Target:
Distance: 1.0956% / 0.01095568 | ADC: 0.25x RC
63.6 Icelander
17.0 French_Nouvelle-Aquitaine
9.8 English_Cornwall
4.4 Pamiri_Rushan
3.0 Mari
1.6 Han_Hubei
0.6 Mixe_Mexico

Target:
Distance: 1.1364% / 0.01136436 | ADC: 0.5x RC
66.2 Welsh
26.6 Icelander
4.0 Altaian_Chelkan
3.2 Pamiri_Rushan

Target:
Distance: 1.1822% / 0.01182247 | ADC: 1x RC
61.4 Welsh
38.6 Icelander

Target:
Distance: 1.2160% / 0.01215967 | ADC: 2x RC
100.0 Welsh

Target:
Distance: 1.0982% / 0.01098154 | R5P
70.6 Icelander
19.8 French_Nouvelle-Aquitaine
4.0 Mari
3.8 Kubachi_Dagestan
1.8 Han_Hubei


23andme

Target:
Distance: 1.5895% / 0.01589513
44.2 English_Cornwall
40.6 Swedish
7.2 Spanish_Cantabria
3.6 Datog_Tanzania
1.6 Huichol_Mexico
1.6 Sherpa_Nepal
1.0 French_Nouvelle-Aquitaine
0.2 Ju_Hoansi_Namibia

Target:
Distance: 1.5895% / 0.01589536 | ADC: 0.25x RC
45.6 English_Cornwall
39.8 Swedish
7.8 Spanish_Cantabria
3.6 Datog_Tanzania
1.6 Huichol_Mexico
1.6 Sherpa_Nepal

Target:
Distance: 1.6213% / 0.01621333 | ADC: 0.5x RC
58.0 English_Cornwall
37.4 Swedish
4.6 Datog_Tanzania

Target:
Distance: 1.7065% / 0.01706465 | ADC: 1x RC
38.8 Dutch
38.6 Norwegian
22.6 Welsh

Target:
Distance: 1.7090% / 0.01709045 | ADC: 2x RC
59.2 Dutch
40.8 Norwegian

Target:
Distance: 1.5934% / 0.01593426 | R5P
43.6 English_Cornwall
41.8 Swedish
9.0 Spanish_Cantabria
4.0 Datog_Tanzania
1.6 Huichol_Mexico


I don’t think these new coordinates are quite as accurate tbh, do you think your new ones are any better?

I think it's intended to cover a much larger span of centuries, but not sure how much more. The "deep modern" on DNAGenics is 0 AD til 1900 AD, so it might be comparable? I think it looks good but we can't expect it to be just most recent stuff.

[Xavier727]

I think it's intended to cover a much larger span of centuries, but not sure how much more. The "deep modern" on DNAGenics is 0 AD til 1900 AD, so it might be comparable? I think it looks good but we can't expect it to be just most recent stuff.

Cool, I’ll give that a try

[RyoHazuki]

Target: ryo
Distance: 1.0618% / 0.01061784
50.6 Irish
15.2 Russian_Smolensk
9.8 Spanish_Castilla_y_Leon
8.8 French_Nouvelle-Aquitaine
6.2 Greenlander_West
4.8 Italian_Aosta_Valley
1.8 English_Cornwall
1.8 Ju_Hoansi_Namibia
1.0 Somali

Target: ryo
Distance: 1.0691% / 0.01069110 | R5P
54.2 Irish
22.2 Spanish_Castilla_y_Leon
15.8 Russian_Smolensk
6.0 Greenlander_West
1.8 Ju_Hoansi_Namibia

Target: ryo
Distance: 1.0748% / 0.01074813 | ADC: 0.25x RC
33.4 English_Cornwall
20.4 Irish
11.6 Spanish_Castilla_y_Leon
11.4 Ukrainian_Lviv
8.8 French_Hauts-de-France
6.4 Greenlander_West
5.6 Finnish_Southwest
1.6 Ju_Hoansi_Namibia
0.8 Ethiopian_Afar

Target: ryo
Distance: 1.2210% / 0.01220995 | ADC: 0.5x RC
57.8 Dutch
17.4 German
11.2 Irish
7.0 Greenlander_West
6.6 Austrian

Target: ryo
Distance: 1.4400% / 0.01440008 | ADC: 1x RC
74.8 Dutch
25.2 German

Target: ryo
Distance: 1.4562% / 0.01456151 | ADC: 2x RC
100.0 Dutch

[Dušan]

Okay, better than update itself.


https://i.imgur.com/ugtOpNY.png

https://i.imgur.com/EQH1BM1.png

[ScandinavianCelt]

Okay, better than update itself.


https://i.imgur.com/ugtOpNY.png

https://i.imgur.com/EQH1BM1.png

Looks good!

[Solitude]

Target: illustrativeunscaled
Distance: 1.2451% / 0.01245067 | ADC: 0.25x RC
60.8 Puerto_Rican
19.2 Ngoni_Malawi
13.0 Spanish_Andalusia
5.4 Danish
1.6 Gurung_Nepal

without puerto rican and andalusian

Target: illustrativeunscaled
Distance: 1.5141% / 0.01514121 | ADC: 0.25x RC
59.8 Spanish_Galicia
23.0 Ngoni_Malawi
9.2 Yukpa_Venezuela
5.4 Danish
2.2 Gambia
0.4 Shor_Mountain

G25

Target: NightmareCity_unscaled
Distance: 1.4553% / 0.01455308 | ADC: 0.25x RC
61.2 Spain_Portugal:Portuguese
14.0 Nigerian:Igbo
9.8 Southern_East_African:Luhya
9.4 Native_American:Karitiana
5.2 French_German:Dutch
0.4 Melanesian:Australian

[Lux Tenebras]

Distance: 0.8840% / 0.00883993 | ADC: 0.25x RC
38.6 Greek_Thessaly
21.8 Greek_Western_Greece
13.6 Slovakian
13.0 Ukrainian_Kirovohrad
11.4 Moldovan
1.6 Mari

Distance: 1.0273% / 0.01027311 | ADC: 1x RC
62.6 Serb
37.4 Greek_Thessaly

[BoredBalkanMan]

135139

Target: me :)
Distance: 0.6976% / 0.00697644
34.4 Latvian
17.0 Serb_Bosnia
16.8 Greek_Izmir
14.8 Albanian
13.2 Greek_Eastern_Macedonia_and_Thrace
2.6 Samaritan
0.8 Swahili_Siyu
0.2 Aymara_Peru
0.2 Biaka

Target:
Distance: 0.7291% / 0.00729078 | ADC: 0.25x RC
43.4 Serb_Bosnia
19.8 Latvian
19.6 Greek_Eastern_Macedonia_and_Thrace
8.0 Samaritan
7.4 Ukrainian_Zhytomyr
1.2 Serb_Croatia
0.6 Persian_Qom

Target:
Distance: 0.7973% / 0.00797321 | ADC: 0.5x RC
66.6 Serb_Bosnia
17.8 Ukrainian_Zhytomyr
8.6 Russian_Belgorod
7.0 Yemeni_Shabwah

Target:
Distance: 0.9640% / 0.00964006 | ADC: 1x RC (2x RC is the same as this one)
40.4 Serb_Bosnia
34.2 Bosniak
25.4 Croat

[Gallop]

Target: Gallopaire
Distance: 1.0668% / 0.01066769 | ADC: 0.5x RC
44.8 Spanish_Castilla_y_Leon
42.4 Spanish_Valencia
8.8 Mari
4.0 Italian_Aosta_Valley

Target: Gallopaire
Distance: 1.2311% / 0.01231139 | ADC: 1x RC
52.6 Spanish_Extremadura
24.4 Spanish_Valencia
23.0 Spanish_Castilla_y_Leon

-----------------------------------

Target: Papá
Distance: 0.9891% / 0.00989109 | ADC: 0.5x RC
50.2 Spanish_Extremadura
35.0 Spanish_Galicia
8.0 Ukrainian_Ternopil
6.8 Chuvash

Target: Papá
Distance: 1.1300% / 0.01130050 | ADC: 1x RC
49.6 Spanish_Extremadura
27.6 Spanish_Galicia
22.8 French_Grand_Est

------------------------------

Target: pepe
Distance: 1.2057% / 0.01205660 | ADC: 0.5x RC
63.6 Spanish_Galicia
15.6 Spanish_Extremadura
11.8 Greek
7.0 Mari
2.0 Ukrainian_Ternopil

Target: pepe
Distance: 1.4125% / 0.01412521 | ADC: 1x RC
74.2 Spanish_Galicia
25.8 Spanish_Extremadura



Soy un niño Mari llegado desde Marimlandia

[ScandinavianCelt]

Target: Gallopaire
Distance: 1.0668% / 0.01066769 | ADC: 0.5x RC
44.8 Spanish_Castilla_y_Leon
42.4 Spanish_Valencia
8.8 Mari
4.0 Italian_Aosta_Valley

Target: Gallopaire
Distance: 1.2311% / 0.01231139 | ADC: 1x RC
52.6 Spanish_Extremadura
24.4 Spanish_Valencia
23.0 Spanish_Castilla_y_Leon

-----------------------------------

Target: Papá
Distance: 0.9891% / 0.00989109 | ADC: 0.5x RC
50.2 Spanish_Extremadura
35.0 Spanish_Galicia
8.0 Ukrainian_Ternopil
6.8 Chuvash

Target: Papá
Distance: 1.1300% / 0.01130050 | ADC: 1x RC
49.6 Spanish_Extremadura
27.6 Spanish_Galicia
22.8 French_Grand_Est

------------------------------

Target: pepe
Distance: 1.2057% / 0.01205660 | ADC: 0.5x RC
63.6 Spanish_Galicia
15.6 Spanish_Extremadura
11.8 Greek
7.0 Mari
2.0 Ukrainian_Ternopil

Target: pepe
Distance: 1.4125% / 0.01412521 | ADC: 1x RC
74.2 Spanish_Galicia
25.8 Spanish_Extremadura



Soy un niño Mari llegado desde Marimlandia

That's very interesting that you would get that do you know how you get that I mean is it coming through some sort of visigoth? Maybe it came with the Yamnaya

[ScandinavianCelt]

135139

Target: me :)
Distance: 0.6976% / 0.00697644
34.4 Latvian
17.0 Serb_Bosnia
16.8 Greek_Izmir
14.8 Albanian
13.2 Greek_Eastern_Macedonia_and_Thrace
2.6 Samaritan
0.8 Swahili_Siyu
0.2 Aymara_Peru
0.2 Biaka

Target:
Distance: 0.7291% / 0.00729078 | ADC: 0.25x RC
43.4 Serb_Bosnia
19.8 Latvian
19.6 Greek_Eastern_Macedonia_and_Thrace
8.0 Samaritan
7.4 Ukrainian_Zhytomyr
1.2 Serb_Croatia
0.6 Persian_Qom

Target:
Distance: 0.7973% / 0.00797321 | ADC: 0.5x RC
66.6 Serb_Bosnia
17.8 Ukrainian_Zhytomyr
8.6 Russian_Belgorod
7.0 Yemeni_Shabwah

Target:
Distance: 0.9640% / 0.00964006 | ADC: 1x RC (2x RC is the same as this one)
40.4 Serb_Bosnia
34.2 Bosniak
25.4 Croat

So what's the difference if you have more Serbian from Montenegro like the other guy on the forum here has and you don't really have any does that mean you're more Northern Serbian that's all or more Western probably I don't know it doesn't look like you're very Western to me so what's the difference? I mean why do some serbs get half montenegrin Serb and you don't?

[ScandinavianCelt]

Target: RNB27
Distance: 1.2290% / 0.01229048 | ADC: 1x RC
65.6 Spanish_Castilla_y_Leon
34.4 French_Provence

Target: RNB27
Distance: 1.1985% / 0.01198467 | R3P
61.8 Spanish_Castilla_y_Leon
35.8 French_Provence
2.4 Greenlander_West

It seems that I share more DNA with you then the other guys from Spain but I don't really know I think maybe the southerners connect to me further in time but for me to get on the unscaled test like 18% from Aragon I have to ask you who amongst the Spanish would have the most from Aragon?

[Gallop]

That's very interesting that you would get that do you know how you get that I mean is it coming through some sort of visigoth? Maybe it came with the Yamnaya

In some other calculator I had already got it, so I have no idea how it can be, I will see if any other complete Spaniard gets it.

[Fabricius]

You will need to get unscaled coords from your new coords with them by converting your scaled to unscaled here:

(click the arrows icon on top and paste scaled in there):

https://admixtr.streamlit.app/


Thank you!

[Fabricius]

Oh my...

Target: Fabricius_g25_unscaled
Distance: 2.1570% / 0.02156956 | R4P | ADC: 1x
64.2 Tatar_Siberian_Baraba
33.8 Puerto_Rican
2.0 Kikuyu_Kenya

Target: Fabricius_g25_unscaled
Distance: 2.2749% / 0.02274852 | R3P | ADC: 1x
36.0 Bashkir_Ishimbaysky
34.0 Tatar_Siberian_Baraba
30.0 Puerto_Rican

Target: Fabricius_g25_unscaled
Distance: 2.7133% / 0.02713346 | ADC: 2x
52.6 Bashkir_Ilishevsky
38.6 Crimean_Tatar_Steppe
8.8 Nogai_Astrakhan

[ScandinavianCelt]

Oh my...

Target: Fabricius_g25_unscaled
Distance: 2.1570% / 0.02156956 | R4P | ADC: 1x
64.2 Tatar_Siberian_Baraba
33.8 Puerto_Rican
2.0 Kikuyu_Kenya

Target: Fabricius_g25_unscaled
Distance: 2.2749% / 0.02274852 | R3P | ADC: 1x
36.0 Bashkir_Ishimbaysky
34.0 Tatar_Siberian_Baraba
30.0 Puerto_Rican

Target: Fabricius_g25_unscaled
Distance: 2.7133% / 0.02713346 | ADC: 2x
52.6 Bashkir_Ilishevsky
38.6 Crimean_Tatar_Steppe
8.8 Nogai_Astrakhan

Yeah you need their updated coordinates to work with that source you can't use your unscaled other coordinates they're not going to work you're going to get weird results that don't make a lot of sense because the plot is different

[ScandinavianCelt]

In some other calculator I had already got it, so I have no idea how it can be, I will see if any other complete Spaniard gets it.

I wonder if it came from some ancient Basque explorers or potentially with the Visigoths because if they were coming from the East they would have some uralic

[ScandinavianCelt]

In some other calculator I had already got it, so I have no idea how it can be, I will see if any other complete Spaniard gets it.

You know what you can do is put that sample as the Target and then put yourself as source with all the other pieces and then run the distances however many you need to to find your closest pieces going in that direction potentially maybe the one closest to you is how you got it

[Grace O'Malley]

These new coordinates are completely inaccurate for me. Despite Bretons and Irish being Insular Celts they aren't exactly interchangeable populations. I now do not get Irish at all which is not the case with my original G25 coordinates.

Target: Grace
Distance: 0.8708% / 0.00870836
68.0 Breton
12.4 Orcadian
7.8 French_Bourgogne-Franche-Comte
6.4 Mari
3.8 Lak_Dagestan
1.0 Moroccan_Berber_Ifrane
0.6 Karitiana_Brazil


Target: Grace
Distance: 0.8767% / 0.00876666 | ADC: 0.25x RC
70.0 Breton
10.6 French_Bourgogne-Franche-Comte
8.2 Orcadian
6.2 Mari
3.6 Lak_Dagestan
1.4 Altaian_Chelkan


Target: Grace
Distance: 0.8991% / 0.00899066 | ADC: 0.5x RC
67.2 Breton
22.4 Orcadian
6.2 Mari
4.2 Pamiri_Rushan

Target: Grace
Distance: 0.8985% / 0.00898495 | R3P
88.6 Breton
6.4 Mari
5.0 Lak_Dagestan

Not accurate for someone who is 100% Irish.

[Fabricius]

Yeah you need their updated coordinates to work with that source you can't use your unscaled other coordinates they're not going to work you're going to get weird results that don't make a lot of sense because the plot is different

Oh, now I understand!
Ok

[ScandinavianCelt]

These new coordinates are completely inaccurate for me. Despite Bretons and Irish being Insular Celts they aren't exactly interchangeable populations. I now do not get Irish at all which is not the case with my original G25 coordinates.

Target: Grace
Distance: 0.8708% / 0.00870836
68.0 Breton
12.4 Orcadian
7.8 French_Bourgogne-Franche-Comte
6.4 Mari
3.8 Lak_Dagestan
1.0 Moroccan_Berber_Ifrane
0.6 Karitiana_Brazil


Target: Grace
Distance: 0.8767% / 0.00876666 | ADC: 0.25x RC
70.0 Breton
10.6 French_Bourgogne-Franche-Comte
8.2 Orcadian
6.2 Mari
3.6 Lak_Dagestan
1.4 Altaian_Chelkan


Target: Grace
Distance: 0.8991% / 0.00899066 | ADC: 0.5x RC
67.2 Breton
22.4 Orcadian
6.2 Mari
4.2 Pamiri_Rushan

Target: Grace
Distance: 0.8985% / 0.00898495 | R3P
88.6 Breton
6.4 Mari
5.0 Lak_Dagestan

Not accurate for someone who is 100% Irish.

Target: Breton
Distance: 0.5502% / 0.00550197
38.8 Scottish
28.2 Icelander
15.6 Basque_Spain
12.4 Irish
3.2 Mari
0.6 Russian_Leshukonsky
0.4 Biaka
0.4 Kurmi_Uttar_Pradesh
0.2 Karitiana_Brazil
0.2 Mbuti_Congo

Target: Breton
Distance: 0.6498% / 0.00649839 | ADC: 2x RC
100.0 Scottish


Write to them and ask why.


Try these NEW InsularAve vs ScandinavianAve and show me your distances please and no ADC and 2x:

Insular4_NewAverage_UNscaled,-0.017314,-0.007629,0.011375,-0.006913,0.004964,-0.018532,0.001341,0.003017,0.003587,-0.003671,0.002527,-0.000432,0.004956,0.000186,-0.009067,0.00358,0.003624,-0.009058,-0.003809,-0.001278,0.004877,0.003347,-0.002192,0.006099,0.000291
Scandinavian4_NewAverage_UNscaled,-0.016873,-0.007807,0.012187,-0.005649,0.007682,-0.021515,0.001199,0.000742,0.0021,-0.002552,-0.000046,-0.000763,0.003837,-0.000582,-0.005268,0.001198,0.002352,-0.006881,-0.002524,-0.001187,0.003698,0.003591,-0.001384,0.004619,-0.001531
Breton,-0.017316,-0.007517,0.011508,-0.005853,0.00539,-0.01957,0.00063,0.002736,0.004778,-0.002992,0.00281,0.000137,0.006038,-0.000156,-0.008967,0.004071,0.003546,-0.009135,-0.006436,-0.000032,0.006788,-0.000148,0.001251,0.008238,-0.001


Mine:

Target: SC_Brad_Official_New.Merged_UNscaled
Distance: 0.8421% / 0.00842072
53.4 Scandinavian4_NewAverage_UNscaled
46.6 Insular4_NewAverage_UNscaled

Target: SC_Brad_Official_New.Merged_UNscaled
Distance: 0.8421% / 0.00842072 | ADC: 2x RC
53.4 Scandinavian4_NewAverage_UNscaled
46.6 Insular4_NewAverage_UNscaled

Distance to: SC_Brad_Official_New.Merged_UNscaled
0.00930295 Scandinavian4_NewAverage_UNscaled
0.00955496 Insular4_NewAverage_UNscaled
0.01316212 Breton

I'm not picking up any Breton on a 3-way with those averages.


Language

Breton and Irish are both Celtic languages, along with Cornish, Manx, Scottish Gaelic, and Welsh. Breton is the only Celtic language spoken on the European mainland, and the only insular Celtic language spoken outside of the British Isles.

History
Breton was introduced to the Brittany region of France by migrating Britons in the 5th and 6th centuries.

So, perhaps these coords are a "deep modern" back to at least then.

[Eurafricanid]

Target: Eurafricanid-ILLUSTRATIVE
Distance: 0.7608% / 0.00760833 | R5P
34.8 Yao_Malawi
26.2 Spanish_Aragon
25.0 Maltese
11.2 Swahili_Jomvu
2.8 Huichol_Mexico

[Grace O'Malley]

Target: Breton
Distance: 0.5502% / 0.00550197
38.8 Scottish
28.2 Icelander
15.6 Basque_Spain
12.4 Irish
3.2 Mari
0.6 Russian_Leshukonsky
0.4 Biaka
0.4 Kurmi_Uttar_Pradesh
0.2 Karitiana_Brazil
0.2 Mbuti_Congo

Target: Breton
Distance: 0.6498% / 0.00649839 | ADC: 2x RC
100.0 Scottish


Write to them and ask why.


Try these NEW InsularAve vs ScandinavianAve and show me your distances please and no ADC and 2x:

Insular4_NewAverage_UNscaled,-0.017314,-0.007629,0.011375,-0.006913,0.004964,-0.018532,0.001341,0.003017,0.003587,-0.003671,0.002527,-0.000432,0.004956,0.000186,-0.009067,0.00358,0.003624,-0.009058,-0.003809,-0.001278,0.004877,0.003347,-0.002192,0.006099,0.000291
Scandinavian4_NewAverage_UNscaled,-0.016873,-0.007807,0.012187,-0.005649,0.007682,-0.021515,0.001199,0.000742,0.0021,-0.002552,-0.000046,-0.000763,0.003837,-0.000582,-0.005268,0.001198,0.002352,-0.006881,-0.002524,-0.001187,0.003698,0.003591,-0.001384,0.004619,-0.001531
Breton,-0.017316,-0.007517,0.011508,-0.005853,0.00539,-0.01957,0.00063,0.002736,0.004778,-0.002992,0.00281,0.000137,0.006038,-0.000156,-0.008967,0.004071,0.003546,-0.009135,-0.006436,-0.000032,0.006788,-0.000148,0.001251,0.008238,-0.001


Mine:

Target: SC_Brad_Official_New.Merged_UNscaled
Distance: 0.8421% / 0.00842072
53.4 Scandinavian4_NewAverage_UNscaled
46.6 Insular4_NewAverage_UNscaled

Target: SC_Brad_Official_New.Merged_UNscaled
Distance: 0.8421% / 0.00842072 | ADC: 2x RC
53.4 Scandinavian4_NewAverage_UNscaled
46.6 Insular4_NewAverage_UNscaled

Distance to: SC_Brad_Official_New.Merged_UNscaled
0.00930295 Scandinavian4_NewAverage_UNscaled
0.00955496 Insular4_NewAverage_UNscaled
0.01316212 Breton

I'm not picking up any Breton on a 3-way with those averages.


Language

Breton and Irish are both Celtic languages, along with Cornish, Manx, Scottish Gaelic, and Welsh. Breton is the only Celtic language spoken on the European mainland, and the only insular Celtic language spoken outside of the British Isles.

History
Breton was introduced to the Brittany region of France by migrating Britons in the 5th and 6th centuries.

So, perhaps these coords are a "deep modern" back to at least then.

I understand the history however I'm an Irish Gael and I'm not close to Bretons on any other platform. It plainly isn't correct. Not sure why my coordinates would be so off when it is the same upload as the previous ones which were more in line with my G25 from David and I was Irish on those. Why should I be so different than the Irish average with these new coordinates?

Target: Grace
Distance: 1.0640% / 0.01064043
85.4 Breton
10.6 Scandinavian4_NewAverage_UNscaled
4.0 Insular4_NewAverage_UNscaled

Distance to: Grace
0.01072879 Breton
0.01223487 Insular4_NewAverage_UNscaled
0.01446467 Scandinavian4_NewAverage_UNscaled

Bretons aren't the same as Irish and I'm not an outlier for Irish on any other platform.

[ScandinavianCelt]

I understand the history however I'm an Irish Gael and I'm not close to Bretons on any other platform. It plainly isn't correct. Not sure why my coordinates would be so off when it is the same upload as the previous ones which were more in line with my G25 from David and I was Irish on those. Why should I be so different than the Irish average with these new coordinates?

Target: Grace
Distance: 1.0640% / 0.01064043
85.4 Breton
10.6 Scandinavian4_NewAverage_UNscaled
4.0 Insular4_NewAverage_UNscaled

Distance to: Grace
0.01072879 Breton
0.01223487 Insular4_NewAverage_UNscaled
0.01446467 Scandinavian4_NewAverage_UNscaled

Bretons aren't the same as Irish and I'm not an outlier for Irish on any other platform.

I would email them and ask.

[Saba]

Target: Saba
Distance: 2.7513% / 0.02751293 | ADC: 0.5x RC
61.6 Lur_Lorestan
28.0 Azerbaijani_Tabriz
8.8 Bandari_Iran
1.6 Ju_Hoansi_Namibia


The update on the website sucks. But the coordinates are really good actually. This actually adds up to being very similar to my paper trail without me needing to manipulate the source population. I’m interested to see what new populations they add

[ScandinavianCelt]

I understand the history however I'm an Irish Gael and I'm not close to Bretons on any other platform. It plainly isn't correct. Not sure why my coordinates would be so off when it is the same upload as the previous ones which were more in line with my G25 from David and I was Irish on those. Why should I be so different than the Irish average with these new coordinates?

Target: Grace
Distance: 1.0640% / 0.01064043
85.4 Breton
10.6 Scandinavian4_NewAverage_UNscaled
4.0 Insular4_NewAverage_UNscaled

Distance to: Grace
0.01072879 Breton
0.01223487 Insular4_NewAverage_UNscaled
0.01446467 Scandinavian4_NewAverage_UNscaled

Bretons aren't the same as Irish and I'm not an outlier for Irish on any other platform.



Honestly I think it can just be time period related, potentially. I mean look at my results I'm getting Norwegian at 2X and primarily Irish at no distance yet the modern commercial test give me Swedish and French because that's the most recent so I could also say this is terrible because I'm not picking up Norwegian and Irish very much on commercial tests but when you do a deep modern test it's looking at at least five times probably the time period of the commercial tests. If you run a test with the previous version of official scaled coordinates against all the modern Irish and Brittany samples do you show any Brittany at all?

[Grace O'Malley]

Welcome to the plastic Paddie club :p

You can't be a Plastic Paddy if you are actually Irish. :) Personally I don't like the term and find it condescending. I have a different attitude to the topic and some Irish are a bit insufferable. I push back with some people on the topic. Not all Irish are the same either.

[Grace O'Malley]

Honestly I think it can just be time period related, potentially. I mean look at my results I'm getting Norwegian at 2X and primarily Irish at no distance yet the modern commercial test give me Swedish and French because that's the most recent so I could also say this is terrible because I'm not picking up Norwegian and Irish very much on commercial tests but when you do a deep modern test it's looking at at least five times probably the time period of the commercial tests. If you run a test with the previous version of official scaled coordinates against all the modern Irish and Brittany samples do you show any Brittany at all?

I don't agree. The Irish did not come from Brittany. Irish have been there as long as any population. This is also based on modern populations. Why is these new coordinates so off for me? You're right I should put in an enquiry.

I've put in a query and asked them to look at it.

[Gallop]

You know what you can do is put that sample as the Target and then put yourself as source with all the other pieces and then run the distances however many you need to to find your closest pieces going in that direction potentially maybe the one closest to you is how you got it


I see that my father and brother are in one group and I am in another, maybe it is a Caucasian or Indo-European result. Maybe the solution lies in some of the places between my father's and brother's situation and mine. Between my father's and brother's position and my own with the transition between the two, the British Isles and France are the most repeated and consistent for my geographical origin, but also Italy and Greece so it could be something related to the Roman Empire.


Distance to: Mari
0.02262658 Chuvash
0.02400084 Udmurt
0.02880630 Tatar_Siberian_Zabolotniye
0.03039896 Besermyan
0.03114806 Bashkir_Karaidelsky
0.03283339 Bashkir_Arkhangelsky
0.03373404 Komi
0.03378857 Mansi
0.03420074 Saami
0.03532079 Bashkir_Baymaksky
0.03588028 Bashkir
0.03627373 Bashkir_Yanaulsky
0.03634167 Bashkir_Kugarchinsky
0.03660920 Bashkir_Davlekanovsky
0.03690856 Bashkir_Ishimbaysky
0.03834626 Bashkir_Ilishevsky
0.03844448 Tatar_Siberian
0.03968034 Khanty
0.04052125 Saami_Kola
0.04069193 Tatar_Kazan
0.04088948 Russian_Leshukonsky
0.04544844 Tatar_Siberian_Baraba
0.04589017 Tatar_Kryashen
0.04678611 Russian_Pinezhsky
0.04697034 Tatar_Siberian_Tom
0.04739024 Finnish_East
0.04770787 Shor_Khakassia
0.04867563 Tatar_Mishar
0.04878495 Altaian_Chelkan
0.04920890 Altaian_Tubalar
0.04966144 Shor_Mountain
0.05000697 Vepsian
0.05009015 Russian_Vologda
0.05055450 Karelian
0.05159971 Mordvin
0.05163453 Mordvin_Erzya
0.05174889 Russian_Krasnoborsky
0.05176987 Finnish_Southeast
0.05248638 Finnish
0.05256197 Mordvin_Moksha
0.05258557 Russian_Kostroma
0.05260966 Finnish_Central
0.05306739 Ingrian
0.05316103 Selkup
0.05337173 Khakas
0.05390182 Finnish_North
0.05426909 Teleut
0.05687631 Finnish_Southwest
0.05812778 Pamiri_Shugnan
0.05841107 Nogai_Astrakhan
0.05864016 Ket
0.05881288 Crimean_Tatar_Steppe
0.05890707 Ukrainian_Ternopil
0.05898710 Russian_Kursk
0.05902303 Pamiri_Rushan
0.05909902 Russian_Ryazan
0.05925824 Russian_Tver
0.05931914 Nogai_Stavropol
0.05957993 Ukrainian_Kirovohrad
0.05958624 Russian_Kaluga
0.05972396 Uzbek_Khorezm
0.05972491 Turkmen_Afghanistan
0.05974513 Estonian
0.05982686 Slovakian
0.05995887 Uzbek
0.06008395 Russian_Yaroslavl
0.06015892 Uzbek_Tashkent
0.06017093 Tajik
0.06027122 Ukrainian_Dnipro
0.06038038 Ukrainian_Donetsk
0.06046834 Turkmen_Uzbekistan
0.06049201 Ukrainian_Sumy
0.06054222 Russian_Voronezh
0.06054453 Yaghnobi
0.06084135 Altaian_Kizhi
0.06092760 Karakalpak
0.06097542 Ukrainian_Rivne
0.06115718 Tajik_Hisor
0.06137827 Khakas_Kachin
0.06156793 Tajik_Kulob
0.06159117 Uyghur
0.06161611 Polish
0.06162524 Russian_Oryol
0.06164407 Altaian
0.06178310 Russian_Belgorod
0.06193454 Ukrainian_Chernihiv
0.06211925 Russian_Pskov
0.06214471 Ukrainian_Zakarpattia
0.06221815 Czech
0.06224576 Swedish
0.06246940 Hungarian
0.06259312 Ukrainian_Poltava
0.06269908 Turkmen_Turkmenistan
0.06273403 Pamiri_Ishkashim
0.06278585 Moldovan
0.06292236 Belarusian
0.06297176 Ukrainian_Zhytomyr
0.06327862 Norwegian
0.06338106 Yukaghir_Forest
0.06343319 Lithuanian_South_Aukstaitija
0.06360302 Tajik_Ayni
0.06360540 Kazakh
0.06361584 Hazara_Afghanistan
0.06362285 Bosniak
0.06365253 Russian_Smolensk
0.06408214 Lithuanian_West_Aukstaitija
0.06438956 German
0.06439315 Danish
0.06450391 Croat
0.06453064 Turkmen_Iran
0.06453577 Icelander
0.06454814 Tajik_Afghanistan
0.06466036 Hazara_Pakistan
0.06475231 Ukrainian_Lviv
0.06476221 Kyrgyz_Tajikistan
0.06488819 Nenets_Tundra
0.06500039 Lithuanian_South_Zemaitija
0.06500940 Turkish_Northern_Bulgaria
0.06504934 Lithuanian_East_Aukstaitija
0.06506953 Lithuanian_North_Zemaitija
0.06540079 Slovenian
0.06541976 Turkish_Southern_Bulgaria
0.06555885 Nenets_Forest
0.06556676 Kyrgyz_China
0.06571022 Tuvan
0.06573907 Romanian
0.06575619 Serb
0.06588876 Nenets
0.06590126 Uzbek_Afghanistan
0.06592413 Lithuanian_West_Zemaitija
0.06601382 Orcadian
0.06602899 Tlingit
0.06607765 Serb_Bosnia
0.06609651 Kyrgyz
0.06618726 Austrian
0.06620585 Nogai_Karachay-Cherkessia
0.06622377 Breton
0.06631200 Dutch
0.06639896 Serb_Croatia
0.06644650 Serb_Montenegro
0.06673736 North_Macedonian
0.06692728 Pomak_Bulgaria
0.06695446 Montenegrin
0.06703571 Welsh
0.06705325 Bulgarian
0.06714368 Ror_Haryana
0.06727411 Scottish
0.06729074 Pashtun_Afghanistan
0.06731239 English_Kent
0.06788879 FATHER
0.06790263 French_Grand_Est
0.06790613 BROTHER
0.06802187 Irish
0.06804223 Latvian
0.06819496 English_Cornwall
0.06850908 Gagauz
0.06868542 White_American_Utah
0.06874054 French_Normandy
0.06876414 Enets
0.06934216 Burusho_Pakistan
0.06946144 French_Bourgogne-Franche-Comte
0.06951835 Greek_Macedonia
0.06958730 Tabasaran_Dagestan
0.06968546 Nuristani_Afghanistan
0.06970516 French_Provence
0.06974741 Turkish_Denizli
0.06975544 Avar_Dagestan
0.06989872 Persian_Khorasan
0.06997752 French_Hauts-de-France
0.07005247 Pashtun
0.07010796 French
0.07025980 Italian_Friuli-Venezia_Giulia
0.07027171 Kalash_Pakistan
0.07041906 Kaitag_Dagestan
0.07047071 GALLOP-Ancestry
0.07047167 Lezgin_Dagestan
0.07051440 Turkish_Antalya
0.07085403 Greek_Eastern_Macedonia_and_Thrace
0.07094301 Pashtun_Pakistan
0.07103074 Italian_Aosta_Valley
0.07111098 Turkish_Balikesir
0.07168539 GALLOP-ftdna
0.07173787 Greek_Central_Macedonia
0.07182975 Bahun_Nepal
0.07183006 Italian_Veneto
0.07186057 Zoroastrian_Yazd
0.07196113 Greek_Northeast
0.07199223 Greek
0.07228463 Zoroastrian_Shiraz
0.07229484 Puerto_Rican
0.07237934 Dargin_Dagestan
0.07242504 Tuvan_Tozhu
0.07247731 Turkish_Ankara
0.07250770 Albanian_Kosovo
0.07253254 Greek_Thessaly
0.07270969 Kumyk_Dagestan
0.07284630 Turkish_Aydin
0.07297256 Kamboj_Rajasthan
0.07298359 Spanish_Extremadura
0.07300814 Kubachi_Dagestan
0.07318480 Persian_Yazd
0.07319751 Italian_Piedmont
0.07323582 Spanish_Galicia
0.07325538 Turkish_Giresun
0.07336554 Lak_Dagestan
0.07349276 Roma_Balkans
0.07354511 Greek_Peloponnese
0.07357395 Makrani_Pakistan
0.07359029 Balochi_Pakistan
0.07365940 Azerbaijani_Tehran
0.07377148 Zoroastrian_Tehran
0.07378590 Persian_Fars
0.07380777 Bandari_Iran
0.07381038 Italian_Trentino-Alto_Adige
0.07384004 Kabardian
0.07384632 Azerbaijani_Dagestan
0.07390477 Italian_North
0.07393576 Turkish_Adana
0.07396524 Kalmyk
0.07404863 Albanian
0.07423258 Italian_Southern_Tuscany
0.07429152 Brahui_Pakistan
0.07432246 Spanish_Balearic_Islands
0.07435852 Mongol_Mongolia
0.07439451 Greek_Western_Greece
0.07448621 Parsi_Pakistan
0.07455119 Greek_Athens
0.07463678 GujaratiA
0.07467079 Chechen
0.07484269 Spanish_Cantabria
0.07488191 Balochi_Iran
0.07489511 Azerbaijani
0.07490819 Kurdish_Syria
0.07492284 Portuguese
0.07494617 Circassian
0.07507206 Spanish_Catalonia
0.07515234 Italian_Emilia-Romagna
0.07515977 Abazin
0.07518291 Turkish_Konya
0.07529374 Italian_Lombardy
0.07542694 Turkish_Sivas
0.07564288 Spanish_Murcia
0.07568521 Persian_Semnan
0.07573805 Parsi_India
0.07575638 Rajput_India
0.07589799 Italian_Liguria
0.07595049 Azerbaijani_Tabriz
0.07598928 Ingush
0.07603770 Azerbaijani_Ardabil
0.07608701 Persian_Tehran
0.07609720 Azerbaijani_Aghjabadi
0.07612720 Persian_Isfahan
0.07616559 Italian_Abruzzo
0.07617712 Greek_Izmir
0.07618742 Ashkenazi_Jew_East
0.07618818 Italian_Tuscany
0.07620133 SaudiC
0.07626286 Italian_Marche
0.07626754 Ashkenazi_Jew
0.07633735 Turkish_Kayseri
0.07653206 Spanish_Valencia
0.07656370 Spanish_Castilla_la_Mancha
0.07660256 Karachay
0.07668032 Brahmin_Uttarakhand
0.07668152 Turkish_Malatya
0.07669411 Spanish_Andalusia
0.07672128 Italian_Lazio
0.07680951 Yazidi_Armenia
0.07682870 Sindhi_Pakistan
0.07684967 Italian_Umbria
0.07689995 Italian_Molise
0.07692074 Khamnegan
0.07696836 Bukharan_Jew
0.07698038 Kurdish_Iran
0.07707140 Sicilian
0.07708506 Maltese
0.07710352 Spanish_Castilla_y_Leon
0.07714105 Greek_Cyclades
0.07714559 Azerbaijani_Zanjan
0.07717220 Kurdish_Turkey
0.07726249 Dongxiang_Gansu
0.07736804 Colombian
0.07742157 Kurdish_Iraq
0.07743430 Italian_Basilicata
0.07748333 Dungan_Uzbekistan
0.07752234 Italian_Apulia
0.07763063 Persian_Qom
0.07764569 Greek_Crete
0.07774688 Buryat
0.07778456 Lur_Lorestan
0.07793004 Balkar
0.07801786 Spanish_Aragon
0.07802635 French_Occitania
0.07809854 Talysh_Azerbaijan
0.07819111 Italian_South
0.07832322 Salar_Qinghai
0.07836716 Iraqi_Arab
0.07838274 Adygei
0.07838749 Tharu_Nepal
0.07857926 Kurdish_Adygea

[Feiichy]

Target: Feiichy
Distance: 0.0078% / 0.00777057 | ADC: 0.5x RC

61.4 Serb_Bosnia
20.9 Ukrainian_Zhytomyr
14.4 Slovakian
3.3 Sherpa_Nepal

https://static.jutarnji.hr/images/slike/2023/12/20/k_31622529_640.jpg

Distance to: Feiichy

0.00933941 Croat
0.01022979 Serb_Bosnia
0.01054765 Slovenian
0.01075730 Bosniak
0.01131893 Ukrainian_Zakarpattia
0.01141199 Moldovan
0.01198347 Slovakian
0.01206028 Hungarian
0.01329777 Czech
0.01346291 Serb
0.01347074 Serb_Croatia
0.01509508 Montenegrin
0.01558961 Ukrainian_Lviv
0.01629959 Romanian
0.01640357 Polish
0.01669684 North_Macedonian
0.01677783 Serb_Montenegro
0.01759986 Ukrainian_Ternopil
0.01807782 Ukrainian_Poltava
0.01820098 Pomak_Bulgaria
0.01839261 Ukrainian_Zhytomyr
0.01859936 Ukrainian_Sumy
0.01884875 Bulgarian
0.01909714 Ukrainian_Rivne
0.01933114 Ukrainian_Dnipro

[Demirkazık]

Target: Demir
Distance: 0.8622% / 0.00862203
45.0 Greek_Central_Anatolia
11.2 Latvian
10.8 Georgian_Guria
8.8 Mazandarani
6.8 Nivkh
6.6 BedouinB_Negev
3.8 Tibetan_Lhasa
2.6 Ket
2.2 Nenets
1.2 Biaka
1.0 Mbuti_Congo

Target: Demir
Distance: 1.0864% / 0.01086440 | R3P
65.8 Armenian_Yerevan
21.6 Tatar_Siberian_Tom
12.6 Yukaghir_Forest

Target: Demir
Distance: 1.0332% / 0.01033183 | R4P
65.4 Armenian_Yerevan
15.8 Tatar_Siberian_Tom
11.0 Yukaghir_Forest
7.8 Russian_Yaroslavl

Target: Demir
Distance: 0.9932% / 0.00993164 | R5P
48.4 Armenian_Yerevan
19.8 Greek_Central_Anatolia
16.6 Tatar_Siberian_Tom
9.8 Yukaghir_Forest
5.4 Latvian

1 0.012 66% Armenian_Yerevan + 34% Tatar_Siberian_Tom
2 0.013 64% Greek_Trabzon + 36% Bashkir_Ilishevsky
3 0.013 61% Greek_Central_Anatolia + 39% Uzbek_Tashkent
4 0.013 57% Armenian + 43% Crimean_Tatar_Steppe
5 0.014 70% Greek_Central_Anatolia + 30% Bashkir_Arkhangelsky
6 0.014 59% Greek_Central_Anatolia + 41% Uzbek_Khorezm
7 0.014 95% Turkish_Antalya + 5% Tatar_Siberian_Tom
8 0.015 50% Greek_Izmir + 50% Turkmen_Iran
9 0.015 52% Turkmen_Turkmenistan + 48% Greek_Kos
10 0.016 53% Turkmen_Uzbekistan + 47% Greek_Cyprus

[Lux Tenebras]

Target: Feiichy
Distance: 0.0078% / 0.00777057 | ADC: 0.5x RC

61.4 Serb_Bosnia
20.9 Ukrainian_Zhytomyr
14.4 Slovakian
3.3 Sherpa_Nepal

https://static.jutarnji.hr/images/slike/2023/12/20/k_31622529_640.jpg
:1127:

[EasternLusitanian]

Target: mv1
Distance: 0.0147% / 0.01474686 | ADC: 1x RC
72.1 Spanish_Extremadura
27.9 Corsican

Target: mv1
Distance: 0.0130% / 0.01297363 | R3P
48.8 French_Nouvelle-Aquitaine
37.5 Corsican
13.7 Moroccan_South

Distance to: mv1
0.01540193 Spanish_Extremadura
0.01632577 Spanish_Murcia
0.01641352 Spanish_Andalusia
0.01643888 Portuguese
0.01654885 Spanish_Balearic_Islands
0.01668877 Spanish_Castilla_la_Mancha
0.01677587 Spanish_Galicia
0.01686212 Spanish_Catalonia
0.01719240 Spanish_Cantabria
0.01727289 Spanish_Valencia
0.01734146 Spanish_Castilla_y_Leon
0.01804517 Spanish_Canary_Islands
0.01822230 Italian_Lombardy
0.01840360 Spanish_Aragon
0.01867495 Italian_Emilia-Romagna
0.01869195 Corsican
0.01938356 Italian_Piedmont
0.01963614 Italian_North
0.02012050 French_Nouvelle-Aquitaine
0.02036040 Italian_Veneto
0.02042165 French_Occitania
0.02092125 Italian_Tuscany
0.02096365 Italian_Aosta_Valley
0.02101198 Italian_Trentino-Alto_Adige
0.02109975 French_Provence

The distances seem better than with previous coords, the results not so much...

[BoredBalkanMan]

Good question. I don't really know, we have no family trees. The only thing that's familiar to me is that my ancestors from my dad's side all came to Serbia from around the Dalmatian region around the 1800's. Mother's side is all Serbs from local areas.

[Vitez]

Target: vitez
Distance: 0.0080% / 0.00797389 | ADC: 0.5x RC
48.8 Bosniak
15.8 Slovenian
15.7 Serb_Bosnia
12.5 Ukrainian_Lviv
7.2 Ukrainian_Kirovohrad

Target: vitez
Distance: 0.0082% / 0.00819287 | ADC: 1x RC
56.4 Bosniak
43.6 Slovenian

Distance to: vitez
0.00906345 Bosniak
0.00940850 Croat
0.00960594 Slovenian
0.00982144 Serb_Bosnia
0.01081609 Hungarian
0.01134610 Moldovan
0.01150413 Ukrainian_Zakarpattia
0.01214702 Serb
0.01227594 Serb_Croatia
0.01356671 Montenegrin
0.01378845 Slovakian
0.01425194 Ukrainian_Lviv
0.01449276 North_Macedonian
0.01460100 Czech
0.01462772 Romanian
0.01629593 Serb_Montenegro
0.01650649 Pomak_Bulgaria
0.01715323 Bulgarian
0.01720481 Ukrainian_Ternopil
0.01757155 Polish
0.01831563 Ukrainian_Kirovohrad
0.01839069 Ukrainian_Poltava
0.01850631 Greek_Eastern_Macedonia_and_Thrace
0.01861453 Gagauz
0.01893007 Turkish_Northern_Bulgaria

[hazmatnik]

Hahahahah, not sure where they found this Ethiopian

Target: nikola
Distance: 1.1708% / 0.01170815 | ADC: 0.5x RC
71.4 Serb_Bosnia
24.4 Greek_Macedonia
4.2 Ethiopian_Oromo

Target: nikola
Distance: 1.2328% / 0.01232794 | ADC: 1x RC
69.0 Serb_Bosnia
31.0 Greek_Macedonia

[Thracian]

Worthless. Did not even bother myself run nmonte after seeing closest pops.

Distance to: Thracian
0.01253962 Greek_Central_Macedonia
0.01298041 Turkish_Southern_Bulgaria
0.01404611 Greek_Northeast
0.01412329 Gagauz
0.01452240 Greek_Peloponnese
0.01506409 Bulgarian
0.01508770 Turkish_Northern_Bulgaria
0.01515731 Albanian_Kosovo
0.01526630 Greek_Izmir
0.01578267 Greek_Athens
0.01597232 Greek
0.01606010 Albanian
0.01616216 Pomak_Bulgaria
0.01642238 Greek_Thessaly
0.01661641 Greek_Macedonia
0.01719040 North_Macedonian
0.01746585 Romanian
0.01752057 Ashkenazi_Jew_East
0.01764960 Greek_Eastern_Macedonia_and_Thrace
0.01780726 Italian_Abruzzo
0.01794810 Italian_Apulia
0.01797684 Ashkenazi_Jew
0.01824026 Italian_Marche
0.01836707 Italian_Molise
0.01842958 Turkish_Antalya

[ScandinavianCelt]

Worthless. Did not even bother myself run nmonte after seeing closest pops.

Distance to: Thracian
0.01253962 Greek_Central_Macedonia
0.01298041 Turkish_Southern_Bulgaria
0.01404611 Greek_Northeast
0.01412329 Gagauz
0.01452240 Greek_Peloponnese
0.01506409 Bulgarian
0.01508770 Turkish_Northern_Bulgaria
0.01515731 Albanian_Kosovo
0.01526630 Greek_Izmir
0.01578267 Greek_Athens
0.01597232 Greek
0.01606010 Albanian
0.01616216 Pomak_Bulgaria
0.01642238 Greek_Thessaly
0.01661641 Greek_Macedonia
0.01719040 North_Macedonian
0.01746585 Romanian
0.01752057 Ashkenazi_Jew_East
0.01764960 Greek_Eastern_Macedonia_and_Thrace
0.01780726 Italian_Abruzzo
0.01794810 Italian_Apulia
0.01797684 Ashkenazi_Jew
0.01824026 Italian_Marche
0.01836707 Italian_Molise
0.01842958 Turkish_Antalya

did you use the unscaled version of your newest updated coords from Illdna?

[Beowulf]

Target: Beowulf
Distance: 0.0123% / 0.01228155 | ADC: 0.25x RC
32.4 Spanish_Castilla_la_Mancha
31.1 Spanish_Cantabria
14.2 Swedish
6.2 Moroccan_Berber_Ifrane
6.0 Greek_Western_Greece
3.7 Rai_Nepal
3.0 Ukrainian_Kirovohrad
2.6 Kyrgyz_Tajikistan
0.8 Ukrainian_Donetsk

[djipon]

Target: djipon_ancestrydna
Distance: 1.0042% / 0.01004179 | ADC: 0.5x RC
50.6 Bulgarian
38.4 Greek_Athens
11.0 Mari

[tk'es]

Target: tk'es
Distance: 1.3903% / 0.01390287 | ADC: 0.25x RC
45.0 Georgian_Mtiuleti
22.6 Lak_Dagestan
14.0 Chechen
5.6 Greenlander_West
4.0 Somali_Kenya
3.8 Ossetian
2.6 Han_Hubei
1.0 Kyrgyz_Tajikistan
0.8 French_Bourgogne-Franche-Comte
0.6 Mbuti_Congo



Target: tk'es
Distance: 1.4831% / 0.01483147 | ADC: 0.5x RC
53.6 Chechen
29.0 Georgian_Mtiuleti
9.8 Ossetian
7.6 Greenlander_West



Target: tk'es
Distance: 1.6964% / 0.01696369 | ADC: 1x RC
73.4 Ossetian
26.6 Kaitag_Dagestan



Target: tk'es
Distance: 1.7765% / 0.01776491 | ADC: 2x RC
100.0 Ossetian



Distance to: tk'es
0.01776491 Ossetian
0.01835511 Ingush
0.01912893 Chechen
0.01938725 Karachay
0.02064627 Georgian_Mtiuleti
0.02095808 Kumyk_Dagestan
0.02155906 Balkar
0.02171366 Georgian_Tusheti
0.02177950 Kabardian
0.02199344 Adygei
0.02238973 Kaitag_Dagestan
0.02255022 Circassian
0.02302093 Abazin
0.02349593 Kubachi_Dagestan
0.02367287 Avar_Dagestan
0.02457043 Georgian_Khevsureti
0.02462369 Dargin_Dagestan
0.02506279 Tabasaran_Dagestan
0.02518668 Lak_Dagestan
0.02528621 Lezgin_Dagestan
0.02558399 Abkhazian
0.02569000 Georgian_Kartli
0.02638564 Azerbaijani_Dagestan
0.02642850 Georgian_Svaneti
0.02666171 Georgian

[ScandinavianCelt]

Target: Feiichy
Distance: 0.0078% / 0.00777057 | ADC: 0.5x RC

61.4 Serb_Bosnia
20.9 Ukrainian_Zhytomyr
14.4 Slovakian
3.3 Sherpa_Nepal

https://static.jutarnji.hr/images/slike/2023/12/20/k_31622529_640.jpg

Distance to: Feiichy

0.00933941 Croat
0.01022979 Serb_Bosnia
0.01054765 Slovenian
0.01075730 Bosniak
0.01131893 Ukrainian_Zakarpattia
0.01141199 Moldovan
0.01198347 Slovakian
0.01206028 Hungarian
0.01329777 Czech
0.01346291 Serb
0.01347074 Serb_Croatia
0.01509508 Montenegrin
0.01558961 Ukrainian_Lviv
0.01629959 Romanian
0.01640357 Polish
0.01669684 North_Macedonian
0.01677783 Serb_Montenegro
0.01759986 Ukrainian_Ternopil
0.01807782 Ukrainian_Poltava
0.01820098 Pomak_Bulgaria
0.01839261 Ukrainian_Zhytomyr
0.01859936 Ukrainian_Sumy
0.01884875 Bulgarian
0.01909714 Ukrainian_Rivne
0.01933114 Ukrainian_Dnipro

hi feiichy (name sounds Japanese when I try to pronounce it), can you possibly make a Deep Modern UNscaled Phenotype calc with the new samples requiring our new coords unscaled for us to try? Maybe same groupings as your other model? Would be fun. I'm looking at results of mine at no ADC here and think top 5 prob make up my phenotype(s). cheers

[ScandinavianCelt]

I don't agree. The Irish did not come from Brittany. Irish have been there as long as any population. This is also based on modern populations. Why is these new coordinates so off for me? You're right I should put in an enquiry.

I've put in a query and asked them to look at it.

Target: Breton
Distance: 0.8528% / 0.00852776 | R3P
50.0 Scottish
40.4 Icelander
9.6 Basque_Spain

Target: Breton
Distance: 0.8336% / 0.00833605
44.4 Icelander
36.0 Scottish
11.4 Basque_Spain
6.6 Irish
0.8 Norwegian
0.4 GujaratiA
0.2 French_Normandy
0.2 Mbuti_Congo

Target: Breton
Distance: 0.9352% / 0.00935180 | ADC: 2x RC
100.0 Scottish





Target: Irish
Distance: 0.5323% / 0.00532269 | R3P
79.0 Orcadian
16.2 Norwegian
4.8 Basque_Spain

Target: Irish
Distance: 0.4978% / 0.00497777
27.2 Icelander
24.4 White_American_Utah
22.8 Orcadian
13.8 Scottish
7.8 Breton
3.4 Basque_Spain
0.6 Greenlander_West

Target: Irish
Distance: 0.5767% / 0.00576697 | ADC: 2x RC
100.0 Orcadian

Grace-- which R3P do you see your real genetics closest to?

[vasiliki23]

Something is seriously wrong with my updated coordinates LOL

Target: Vasiliki_unscaled_updated
Distance: 0.9374% / 0.00937448
19.4 Rai_Nepal
16.0 Sardinian
14.8 Igorot_Philippines
12.0 Yakut
10.2 Hawaiian
6.6 Greek_Trabzon
5.0 Lahu_Yunnan
4.2 Nivkh
3.0 Albanian
2.4 Han_Shanghai
2.2 Greek_Eastern_Macedonia_and_Thrace
2.2 Surui_Brazil
2.0 Serb_Croatia

Target: Vasiliki_unscaled_updated
Distance: 2.2826% / 0.02282605 | ADC: 2x RC
51.2 Crimean_Tatar_Steppe
48.8 Mon_Thailand

[Vessna]

Distance to: Vessna
0.01387252 Lithuanian_South_Aukstaitija
0.01415612 Belarusian
0.01422305 Lithuanian_West_Aukstaitija
0.01449428 Russian_Belgorod
0.01513607 Lithuanian_East_Aukstaitija
0.01514436 Ukrainian_Chernihiv
0.01520082 Russian_Pskov
0.01526000 Lithuanian_North_Zemaitija
0.01561515 Lithuanian_West_Zemaitija
0.01565069 Lithuanian_South_Zemaitija
0.01575485 Russian_Oryol
0.01583943 Russian_Ryazan
0.01592456 Ukrainian_Poltava
0.01605330 Ukrainian_Rivne
0.01628320 Russian_Kaluga
0.01661030 Russian_Smolensk
0.01686357 Ukrainian_Zhytomyr
0.01693307 Russian_Kursk
0.01738450 Latvian
0.01759468 Ukrainian_Sumy
0.01761223 Russian_Voronezh
0.01768530 Russian_Yaroslavl
0.01830966 Ukrainian_Dnipro
0.01856777 Polish
0.01861495 Estonian


Target: Vessna
Distance: 1.3117% / 0.01311750 | ADC: 2x RC
57.8 Lithuanian_South_Aukstaitija
42.2 Russian_Belgorod

Target: Vessna
Distance: 1.2851% / 0.01285063 | ADC: 1x RC
52.4 Lithuanian_West_Aukstaitija
47.6 Russian_Belgorod

Target: Vessna
Distance: 1.2584% / 0.01258371 | ADC: 0.5x RC
54.6 Russian_Belgorod
45.4 Lithuanian_North_Zemaitija

Target: Vessna
Distance: 1.2206% / 0.01220634 | ADC: 0.25x RC
52.6 Russian_Belgorod
41.0 Latvian
3.4 Sherpa_Nepal
2.0 Ukrainian_Poltava
1.0 Lithuanian_North_Zemaitija

Target: Vessna
Distance: 1.2149% / 0.01214949
51.6 Russian_Belgorod
43.2 Latvian
2.6 Tibetan_Lhasa
1.2 Ukrainian_Poltava
0.8 Kusunda_Nepal
0.4 Mbuti_Congo
0.2 Khomani_San_South_Africa

[Geba]

More eastern than I am, but still okay. :thumb001:


Target: Geba
Distance: 1.1468% / 0.01146772
28.4 Ukrainian_Chernihiv
26.2 Russian_Belgorod
20.2 Ukrainian_Zhytomyr
11.4 Latvian
5.8 Yemeni_Al_Jawf
3.2 Greek_Central_Anatolia
2.4 Tatar_Siberian_Tom
1.2 Papuan_Korowai
1.0 Biaka
0.2 Yakut


Target: Geba
Distance: 1.2053% / 0.01205329 | ADC: 0.5x RC
60.2 Ukrainian_Chernihiv
16.4 Russian_Belgorod
15.8 Ukrainian_Poltava
7.6 Yemeni_Shabwah

Target: Geba
Distance: 1.3279% / 0.01327857 | ADC: 2x RC
51.6 Ukrainian_Chernihiv
48.4 Ukrainian_Poltava

[ScandinavianCelt]

Something is seriously wrong with my updated coordinates LOL

Target: Vasiliki_unscaled_updated
Distance: 0.9374% / 0.00937448
19.4 Rai_Nepal
16.0 Sardinian
14.8 Igorot_Philippines
12.0 Yakut
10.2 Hawaiian
6.6 Greek_Trabzon
5.0 Lahu_Yunnan
4.2 Nivkh
3.0 Albanian
2.4 Han_Shanghai
2.2 Greek_Eastern_Macedonia_and_Thrace
2.2 Surui_Brazil
2.0 Serb_Croatia

Target: Vasiliki_unscaled_updated
Distance: 2.2826% / 0.02282605 | ADC: 2x RC
51.2 Crimean_Tatar_Steppe
48.8 Mon_Thailand


It's very strange if you're not coming from those areas I wonder if you tried your original unscaled official coordinates against the deep modern source I wonder if it would be more accurate or not?

Are you sure you copied the correct coordinates also?

[alexmegas777]

Distance to: alexmegas
0.01463713 Italian_Friuli-Venezia_Giulia
0.01615526 Romanian
0.01623342 North_Macedonian
0.01661045 Pomak_Bulgaria
0.01690360 Bulgarian
0.01698402 Italian_Veneto
0.01718577 Albanian_Kosovo
0.01746332 Serb_Montenegro
0.01754853 Italian_North
0.01757949 Italian_Trentino-Alto_Adige
0.01767855 Greek_Macedonia
0.01778392 Gagauz
0.01789465 Serb
0.01790171 Albanian
0.01791527 Italian_Aosta_Valley
0.01807826 Montenegrin
0.01814181 Greek_Central_Macedonia
0.01827325 Italian_Piedmont
0.01919004 French_Grand_Est
0.01952279 Greek_Northeast
0.01972313 Serb_Bosnia
0.01996983 Italian_Liguria
0.02033156 Italian_Lombardy
0.02040774 Italian_Emilia-Romagna
0.02044813 Italian_Tuscany


Target: alexmegas
Distance: 1.0501% / 0.01050073 | ADC: 0.25x RC
30.4 Serb_Montenegro
18.0 Italian_Aosta_Valley
17.4 Greek_Macedonia
11.6 Sardinian
9.4 French_Hauts-de-France
5.4 Serb_Bosnia
2.8 Nivkh
2.6 Japanese
1.4 Mbuti_Congo
1.0 Yukpa_Venezuela

Target: alexmegas
Distance: 1.1438% / 0.01143809 | ADC: 0.5x RC
37.6 Italian_Aosta_Valley
24.0 Serb_Montenegro
22.0 Greek_Macedonia
11.4 Italian_Friuli-Venezia_Giulia
5.0 Nivkh

Target: alexmegas
Distance: 1.1117% / 0.01111656 | R5P
37.4 Serb_Montenegro
25.2 French_Hauts-de-France
20.2 Greek_Macedonia
11.8 Sardinian
5.4 Nivkh

[Fabricius]

https://admixtr.streamlit.app/


Man, this site you recommended is very good!
It has very interesting tools, not only the one to convert to unscaled but also the possibility to generate "ghost" coordinates (hypothetical sample).

I like to make averages to avoid overlaps and prevent one population from hiding another that should appear, but the fear is that the average will be equal. Hesitation is greater when they are different ethnicities and not just different populations, even with the certainty that the ethnicities in question came together with a single individual. The option of generating ghost populations allows the weight to be unevenly distributed. This was important so that, with the help of ChatGPT (because I couldn't just double the percentage in each generation), using information from my MyHeritage test and DNAgenics' generation estimation tool, I arrived at the hypothetical sample of my most recent 100% euro (non-Iberian) ancestor. I managed in a calculator with 12 samples to reach a scaled result without noise (1%).

[Solitude]

Man, this site you recommended is very good!
It has very interesting tools, not only the one to convert to unscaled but also the possibility to generate "ghost" coordinates (hypothetical sample).

I like to make averages to avoid overlaps and prevent one population from hiding another that should appear, but the fear is that the average will be equal. Hesitation is greater when they are different ethnicities and not just different populations, even with the certainty that the ethnicities in question came together with a single individual. The option of generating ghost populations allows the weight to be unevenly distributed. This was important so that, with the help of ChatGPT (because I couldn't just double the percentage in each generation), using information from my MyHeritage test and DNAgenics' generation estimation tool, I arrived at the hypothetical sample of my most recent 100% euro (non-Iberian) ancestor. I managed in a calculator with 12 samples to reach a scaled result without noise (1%).

Sera que existe algum forma de isolar cada etinicidade , acho que tem alguns usuarios aqui no forum que conseguem, seria muito interessante se nos tivessemos uma coordenada para cada etinicidade para testar nas calcs , não faço a minima ideia de como fazer isso mas imagino que seja possivel.

[Fistora]

Im much more southern shifted on unscaled:
Target: Fistora
Distance: 1.8101% / 0.01810052
50.6 Russian_Kursk
22.4 Ukrainian_Kirovohrad
7.0 Montenegrin
6.8 Sardinian
5.2 Slovakian
4.0 French_Nouvelle-Aquitaine
2.2 Swahili_Ndau
1.8 Han_Shandong

Target: Fistora
Distance: 1.8781% / 0.01878149 | ADC: 0.5x RC
76.4 Slovakian
23.6 Ukrainian_Kirovohrad

I dont know if it does make sense in my case. Can someone explain the difference between scaled and unscaled?

Distance to: oskr
0.01907111 Slovakian
0.02114823 Ukrainian_Zakarpattia
0.02134670 Polish
0.02160418 Ukrainian_Kirovohrad
0.02245877 Croat
0.02254793 Moldovan
0.02260329 Slovenian
0.02278796 Russian_Kursk
0.02311087 Ukrainian_Ternopil
0.02317373 Ukrainian_Lviv
0.02320224 Ukrainian_Rivne
0.02321996 Hungarian
0.02337839 Czech
0.02371362 Bosniak
0.02394965 Ukrainian_Poltava
0.02409098 Serb_Croatia
0.02427471 Ukrainian_Chernihiv
0.02437301 Serb_Bosnia
0.02439520 Ukrainian_Sumy
0.02447131 Ukrainian_Zhytomyr
0.02488459 Ukrainian_Dnipro
0.02520453 Russian_Ryazan
0.02524021 Montenegrin
0.02547017 Finnish_Southeast
0.02590195 Russian_Oryol

[MandM]

Something is seriously wrong with my updated coordinates LOL

Target: Vasiliki_unscaled_updated
Distance: 0.9374% / 0.00937448
19.4 Rai_Nepal
16.0 Sardinian
14.8 Igorot_Philippines
12.0 Yakut
10.2 Hawaiian
6.6 Greek_Trabzon
5.0 Lahu_Yunnan
4.2 Nivkh
3.0 Albanian
2.4 Han_Shanghai
2.2 Greek_Eastern_Macedonia_and_Thrace
2.2 Surui_Brazil
2.0 Serb_Croatia

Target: Vasiliki_unscaled_updated
Distance: 2.2826% / 0.02282605 | ADC: 2x RC
51.2 Crimean_Tatar_Steppe
48.8 Mon_Thailand

you are probably using your old coords on the new sheet or old sheet on new coords

[Fabricius]

Sera que existe algum forma de isolar cada etinicidade , acho que tem alguns usuarios aqui no forum que conseguem, seria muito interessante se nos tivessemos uma coordenada para cada etinicidade para testar nas calcs , não faço a minima ideia de como fazer isso mas imagino que seja possivel.

Você quer dizer isolar os componentes de uma etnicidade? Quero dizer, fazer o contrário da coordenada ghost?

Acredito que seja válido criar um modelo com populações modernas próximas geograficamente ou com alguma relação histórica, mas de outra etnia. Do resultado (sem ADC) nós poderíamos substituir aquela população ou subestimá-la, mantendo o sample dela com as outras próximas.
Continuando a comparação com as coordenadas "fantasmas", nós poderíamos simplificar o % por 1/10. Se >5%, arredondamos para cima e incluímos um sample daquela população, <5% ignoramos o valor acima das dezenas.

Soa arbitrário ou não-científico?
Eu acho que funciona para ter um resultado específico.

Por exemplo:
Alguém tira x% "French_Brittany" e acha suspeito, na verdade ele esperava tirar "holandês" e talvez fora puxado mais ao sul por ter algo de basco ou ibérico, ou mesmo italiano ou [francês]ocitano.

Ele cria um modelo (por volta de 20 referências) com o seguinte resultado:

Target: French_Brittany
Distance: 0.6299% / 0.00629932
65.2 English
15.2 French_Pas-de-Calais
7.0 Basque_Spanish
6.0 French_Seine-Maritime
5.2 Dutch
1.4 French_Paris

O novo modelo terá:
(Poderá ter mais de 10 samples! Pois estamos arredondando os resultados.)

7 samples “English” (65,2%)
2 samples “French” (22,6%)
1 sample “Basque” (7%)
1 sample “Dutch” (5,2%)

Dependendo das hipóteses, o cara pode apagar os samples “English”, se não espera ter x% de inglês.


**********************************


Do you mean isolating the components of an ethnicity? I mean, do the opposite of the ghost coordinate?

I believe it is valid to create a model with modern populations that are geographically close or with some historical relationship, but of another ethnicity. From the result (without ADC) we could substitute that population or underestimate it, keeping its sample with the others nearby.
Continuing the comparison with the "ghost" coordinates, we could simplify the % by 1/10. If >5%, we round up and include a sample of that population, <5% we ignore the value above the tens.

Does it sound arbitrary or unscientific?
I think it works to have a specific outcome.

E.G.:
Someone takes x% "French_Brittany" and thinks it's suspicious, in fact he expected to take "Dutch" and maybe he was pulled further south because he had something Basque or Iberian, or even Italian or [French]Ocitan.

He creates a model (around 20 samples) with the following result:

Target: French_Brittany
Distance: 0.6299% / 0.00629932
65.2 English
15.2 French_Pas-de-Calais
7.0 Basque_Spanish
6.0 French_Seine-Maritime
5.2 Dutch
1.4 French_Paris

The new model will have:
(You can have more than 10 samples! Because we're rounding up the results.)

7 samples "English" (65.2%)
2 "French" samples (22.6%)
1 sample "Basque" (7%)
1 sample "Dutch" (5.2%)

Depending on the hypotheses, the guy can delete the "English" samples, if he doesn't expect to have x% English.

[Fabricius]

Im much more southern shifted on unscaled:
Target: Fistora
Distance: 1.8101% / 0.01810052
50.6 Russian_Kursk
22.4 Ukrainian_Kirovohrad
7.0 Montenegrin
6.8 Sardinian
5.2 Slovakian
4.0 French_Nouvelle-Aquitaine
2.2 Swahili_Ndau
1.8 Han_Shandong

Target: Fistora
Distance: 1.8781% / 0.01878149 | ADC: 0.5x RC
76.4 Slovakian
23.6 Ukrainian_Kirovohrad

I dont know if it does make sense in my case. Can someone explain the difference between scaled and unscaled?

From your two lowest results (without ADC), it may be that you are not using the new coordinates of Illustrative DNA.

******

The unscaled coordinates, are the raw one, your normal coordinates.
Apparently they are unstable and point more easily to ethnicities with something similar.
Apparently, it's good to use them with more probable models, or you can reduce the populations automatically in Vahaduo, or even increase the distance artificially in Vahaduo as well.
Some say that they are ideal for models with very old samples.

The scaled coordinates reduce unlikely or improbable occurrences. From what I understand, grosso modo, it is already an artificial increase in distances.
Your main ethnic group loses strength, but in compensation the very exotic populations disappear.
They say that scaled coordinates are better for modern populations.

See the example of my signature result. I needed to artificially increase the distance of the unscaled to get to 1%.


If I said nonsense, let someone correct me.
I want to help our friend with what I believe I understood well.

[Fabricius]

Sera que existe algum forma de isolar cada etinicidade , acho que tem alguns usuarios aqui no forum que conseguem, seria muito interessante se nos tivessemos uma coordenada para cada etinicidade para testar nas calcs , não faço a minima ideia de como fazer isso mas imagino que seja possivel.

Ei, Solitude, eu dei bobeira!
A própria ferramenta do site que o ScandinavianCelt indicou tem como gerar um fantasma excluindo etnias!
https://admixtr.streamlit.app/

Acredito que basta colocar suas coordenadas, o sample que você quer excluir e clicar em "subtract", antes de fazer o ghost.

Acho que isso foi feito para desfazer composições, mas deve funcionar para separar etnias que temos alguma porcentagem.

Nós podemos testar.


***************************


Edit:

Hey, Solitude, I messed around (I was foolish)!

The site's own tool that ScandinavianCelt indicated has a way to generate a ghost excluding ethnicities!

https://admixtr.streamlit.app/

I believe that you just need to put your coordinates, the sample you want to delete and click on "subtract", before ghosting.

I think this was done to undo compositions, but it should work to separate ethnicities that we have some percentage of.

We can test it.

[Solitude]

Você quer dizer isolar os componentes de uma etnicidade? Quero dizer, fazer o contrário da coordenada ghost?

Acredito que seja válido criar um modelo com populações modernas próximas geograficamente ou com alguma relação histórica, mas de outra etnia. Do resultado (sem ADC) nós poderíamos substituir aquela população ou subestimá-la, mantendo o sample dela com as outras próximas.
Continuando a comparação com as coordenadas "fantasmas", nós poderíamos simplificar o % por 1/10. Se >5%, arredondamos para cima e incluímos um sample daquela população, <5% ignoramos o valor acima das dezenas.

Soa arbitrário ou não-científico?
Eu acho que funciona para ter um resultado específico.

Por exemplo:
Alguém tira x% "French_Brittany" e acha suspeito, na verdade ele esperava tirar "holandês" e talvez fora puxado mais ao sul por ter algo de basco ou ibérico, ou mesmo italiano ou [francês]ocitano.

Ele cria um modelo (por volta de 20 referências) com o seguinte resultado:

Target: French_Brittany
Distance: 0.6299% / 0.00629932
65.2 English
15.2 French_Pas-de-Calais
7.0 Basque_Spanish
6.0 French_Seine-Maritime
5.2 Dutch
1.4 French_Paris

O novo modelo terá:
(Poderá ter mais de 10 samples! Pois estamos arredondando os resultados.)

7 samples “English” (65,2%)
2 samples “French” (22,6%)
1 sample “Basque” (7%)
1 sample “Dutch” (5,2%)

Dependendo das hipóteses, o cara pode apagar os samples “English”, se não espera ter x% de inglês.


**********************************


Do you mean isolating the components of an ethnicity? I mean, do the opposite of the ghost coordinate?

I believe it is valid to create a model with modern populations that are geographically close or with some historical relationship, but of another ethnicity. From the result (without ADC) we could substitute that population or underestimate it, keeping its sample with the others nearby.
Continuing the comparison with the "ghost" coordinates, we could simplify the % by 1/10. If >5%, we round up and include a sample of that population, <5% we ignore the value above the tens.

Does it sound arbitrary or unscientific?
I think it works to have a specific outcome.

E.G.:
Someone takes x% "French_Brittany" and thinks it's suspicious, in fact he expected to take "Dutch" and maybe he was pulled further south because he had something Basque or Iberian, or even Italian or [French]Ocitan.

He creates a model (around 20 samples) with the following result:

Target: French_Brittany
Distance: 0.6299% / 0.00629932
65.2 English
15.2 French_Pas-de-Calais
7.0 Basque_Spanish
6.0 French_Seine-Maritime
5.2 Dutch
1.4 French_Paris

The new model will have:
(You can have more than 10 samples! Because we're rounding up the results.)

7 samples "English" (65.2%)
2 "French" samples (22.6%)
1 sample "Basque" (7%)
1 sample "Dutch" (5.2%)

Depending on the hypotheses, the guy can delete the "English" samples, if he doesn't expect to have x% English.

"Por exemplo:
Alguém tira x% "French_Brittany" e acha suspeito, na verdade ele esperava tirar "holandês" e talvez fora puxado mais ao sul por ter algo de basco ou ibérico, ou mesmo italiano ou [francês]ocitano"

Exatamente isso aqui é o problema , as vezes um sample acaba por destorcer outro sample , criando esses overlaps , acontece muito com ibericos com frança e norte da italia , aquitania mesmo é um sample que ibericos puxam até mais de 10% mesmo as vezes sem não ter nenhuma ancestralidade francesa , acho que a unica forma de criar um ghost sample se baseando nos resultados e tentando isolar as etnias seria tentar chegar a um resultado final , em que voce nota que dali não passa , o meu por exemplo é um west iberia , ssa , amerindio e um shift pequeno para o norte e outras menores etinicidades que depende da coordenada utilizada no momento , agora tentando fragmentar esses componentes seria a parte mais complexa pois dependendo da coordenada algumas eu posso por exemplo puxar mais portugal outras vão me colocar na galicia , até agora só não notei diferença no ssa que tende sempre a puxar mais west africa e east , amerindio também não muda tanto , o mais complexo seria o europeu , o pequeno shift dependendo da coordenada pode aparecer dutch_north , norwegian , southeast_english e em outra coordenada pode puxar mais south_dutch, flemish , portanto é complexo criar uma coordenada para cada etinicidade sem ter nenhuma informação da arvore genealogica , o que da para fazermos é estudar as proprias coordenadas depois tirar algumas conclusões e tentar criar essas novas coordenadas

[Solitude]

Ei, Solitude, eu dei bobeira!
A própria ferramenta do site que o ScandinavianCelt indicou tem como gerar um fantasma excluindo etnias!
https://admixtr.streamlit.app/

Acredito que basta colocar suas coordenadas, o sample que você quer excluir e clicar em "subtract", antes de fazer o ghost.

Acho que isso foi feito para desfazer composições, mas deve funcionar para separar etnias que temos alguma porcentagem.

Nós podemos testar.


***************************


Edit:

Hey, Solitude, I messed around (I was foolish)!

The site's own tool that ScandinavianCelt indicated has a way to generate a ghost excluding ethnicities!

https://admixtr.streamlit.app/

I believe that you just need to put your coordinates, the sample you want to delete and click on "subtract", before ghosting.

I think this was done to undo compositions, but it should work to separate ethnicities that we have some percentage of.

We can test it.

Interessante vou testar depois

[Solitude]

Ei, Solitude, eu dei bobeira!
A própria ferramenta do site que o ScandinavianCelt indicou tem como gerar um fantasma excluindo etnias!
https://admixtr.streamlit.app/

Acredito que basta colocar suas coordenadas, o sample que você quer excluir e clicar em "subtract", antes de fazer o ghost.

Acho que isso foi feito para desfazer composições, mas deve funcionar para separar etnias que temos alguma porcentagem.

Nós podemos testar.


***************************


Edit:

Hey, Solitude, I messed around (I was foolish)!

The site's own tool that ScandinavianCelt indicated has a way to generate a ghost excluding ethnicities!

https://admixtr.streamlit.app/

I believe that you just need to put your coordinates, the sample you want to delete and click on "subtract", before ghosting.

I think this was done to undo compositions, but it should work to separate ethnicities that we have some percentage of.

We can test it.

voce consegiu fazer com alguma coords?

[Mopi The Dire Wolf]

Yours G25 simulated coordinates are :

Mopster_simulated_g25_scaled,0.123501,0.139964,0.0 46249,0.013403,0.036658,0.004048,0.002405,0.002983 ,0.011155,0.018568,-0.001314,0.006825,-0.013643,-0.014423,0.005942,-0.000915,-0.001546,0.000437,0.000489,-0.002653,0.000139,0.003585,-0.000528,0.00502,-0.001364

Yours results on Davidski G25 Standard model :

TUR_Barcin_N: 50.29 %
Yamnaya_RUS_Samara: 39.19 %
WHG: 10.24 %
MAR_Taforalt: 0.29 %

[Rafael Passoni]

Target: me
Distance: 1.2904% / 0.01290381
48.6 Sardinian
17.6 Greek_Eastern_Macedonia_and_Thrace
10.8 Georgian_Guria
8.2 French_Normandy
6.4 Montenegrin
2.4 Greek_Western_Greece
2.2 Gagauz
1.4 Nivkh
0.8 Dinka_South_Sudan
0.8 Papuan_Korowai
0.4 Mbuti_Congo
0.4 Yakut

Distance to: me
0.01609778 Italian_Tuscany
0.01622410 Corsican
0.01643764 Italian_Marche
0.01724132 Italian_North
0.01735640 Italian_Umbria
0.01807241 Italian_Lombardy
0.01828447 Italian_Lazio
0.01835938 Italian_Piedmont
0.01838149 Italian_Trentino-Alto_Adige
0.01873736 Italian_Emilia-Romagna
0.01892340 Italian_Southern_Tuscany
0.01909291 Italian_Veneto
0.01952664 Italian_Abruzzo
0.01980977 Italian_Molise
0.02016842 Italian_South
0.02025339 Sicilian
0.02036773 Albanian
0.02051678 Italian_Basilicata
0.02053453 Italian_Apulia
0.02057547 Italian_Campania
0.02063712 Italian_Liguria
0.02070648 Italian_Friuli-Venezia_Giulia
0.02070774 Italian_Calabria
0.02134347 Greek_Northeast
0.02186748 Albanian_Kosovo

[Beowulf]

Yours G25 simulated coordinates are :

Mopster_simulated_g25_scaled,0.123501,0.139964,0.0 46249,0.013403,0.036658,0.004048,0.002405,0.002983 ,0.011155,0.018568,-0.001314,0.006825,-0.013643,-0.014423,0.005942,-0.000915,-0.001546,0.000437,0.000489,-0.002653,0.000139,0.003585,-0.000528,0.00502,-0.001364

Yours results on Davidski G25 Standard model :

TUR_Barcin_N: 50.29 %
Yamnaya_RUS_Samara: 39.19 %
WHG: 10.24 %
MAR_Taforalt: 0.29 %

Your coordinates are very similar to my mother's ones