Impromptu G25

[Upsilander]

While answering Valenman questions i collected samples and INADVERTENTLY created a calculator?

Let's try it (if you are really bored) ;)


Balochi_Pakistan,0.085367,0.063978,-0.093903,0.028424,-0.071398,0.029562,0.00893,0.006,-0.025156,-0.016037,-0.00065,-0.003447,0.006838,-0.007707,0.019137,0.027976,-0.012126,0.002534,0.008673,-0.025262,-0.000998,-0.017188,0.001725,-0.014098,0.016765
French_Bearn,0.122929,0.146236,0.055437,0.004522,0 .053856,-0.002231,-0.000235,-0.004384,0.029042,0.040456,-0.009419,0.01139,-0.019326,-0.009909,0.014794,0.002121,-0.009648,-0.000507,-0.00817,-0.008379,0.007487,0.007048,-0.009613,-0.011327,0.001197
Tajik_Afghanistan,0.095611,0.020311,-0.038089,0.031331,-0.052317,0.023706,0.00376,0.000923,-0.024747,-0.014943,-0.006983,-0.001349,0,-0.025735,0.010722,0.008353,-0.005346,0.011909,0.006913,-0.008629,-0.011979,0,-0.003204,-0.004097,0.010777
Spanish_Cataluna,0.112685,0.141159,0.051666,0.0080 75,0.046778,-0.004741,-0.001175,0.004615,0.017589,0.030069,-0.001949,0.009741,-0.01665,-0.015689,0.006922,0.011933,0.015255,-0.00114,0.001634,0.001126,0.010981,-0.005935,-0.009613,-0.001446,-0.00012
French_Seine-Maritime,0.134311,0.141159,0.043746,0.024871,0.045 239,0.017849,0.00658,-0.005307,-0.001841,0.001458,-0.005684,0.006594,-0.004757,-0.006881,0.019272,0,-0.011213,-0.001267,-0.001383,-0.003502,0.006239,0.008037,0.006286,0.009519,-0.007424
Norwegian,0.12862,0.137096,0.065996,0.049742,0.043 085,0.017012,0.009165,0.005077,-0.000205,-0.006196,-0.009419,0.003747,-0.010852,-0.006331,0.014929,-0.009016,-0.021383,0.011529,0.00905,0.001376,-0.001248,0,0.007641,0.024582,-0.001437
Danish,0.141141,0.125926,0.062979,0.056202,0.03785 3,0.008646,0.00611,0.013384,0.007158,0.000182,-0.020299,0.001499,-0.004906,-0.007294,0.010722,0.005701,-0.004303,0.006081,0,0.011005,-0.00262,0.007543,0.002095,0.013978,-0.007544
Estonian,0.130897,0.118817,0.090886,0.077843,0.040 931,0.033746,0.00846,0.017538,-0.001432,-0.032802,0.001786,-0.007643,0.013379,0.015001,0.000814,0.000796,0.002 217,-0.003041,0.005531,0.001251,0.003119,-0.005564,-0.005423,0.009037,0.002155
Latvian,0.143417,0.121864,0.087492,0.090117,0.0381 61,0.035419,0.008695,0.01223,-0.003477,-0.03426,-0.00406,-0.01109,0.017691,0.037571,-0.014522,-0.010209,-0.014212,0.002534,0.006285,0.004502,-0.003993,-0.005688,0.013064,-0.012893,0.002036
Palestinian_Beit_Sahour,0.0876435,0.146744,-0.0541165,-0.084949,-0.0156955,-0.023148,-0.005405,-0.0050765,0.01176,0.0102965,0.00341,-0.00577,0.010927,-0.0052295,-0.004886,0.0144525,0.009844,0.0019635,-0.0001255,-0.0011255,-0.0016845,0.003895,0.0035125,0.005362,0.0033525

RP/ADC at your convenience but post original result at least



https://i.postimg.cc/XYXP69BK/imrpo2.png

https://i.postimg.cc/Dz9dDX1z/impro1.png

[Dušan]

Target: Dušan_scaled
Distance: 3.2682% / 0.03268213
51.2 Latvian
22.8 Palestinian_Beit_Sahour
17.4 French_Bearn
8.6 Spanish_Cataluna

[Dušan]

Target: Dušan_scaled
Distance: 3.2682% / 0.03268213
51.2 Latvian
22.8 Palestinian_Beit_Sahour
17.4 French_Bearn
8.6 Spanish_Cataluna

With Greek Cypriot instead Palestinian as East Med reference, I get better distance


Target: Dušan_scaled
Distance: 2.6320% / 0.02631992
50.6 Latvian
30.6 Cypriot
14.8 French_Bearn
4.0 Spanish_Cataluna

[Petalpusher]

Target: Petalpusher
Distance: 3.0428% / 0.03042809
39.4 French_Bearn
19.2 French_Seine-Maritime
14.4 Norwegian
10.2 Danish
9.4 Latvian
7.4 Spanish_Cataluna

If i put some North Italian instead of Cataluna, improves the distance:

Target: Petalpusher
Distance: 2.0854% / 0.02085403
38.8 French_Bearn
15.2 Norwegian
14.6 Italian_Bergamo
10.4 Danish
9.4 French_Seine-Maritime
8.2 Latvian
3.4 Estonian



Distance to: Petalpusher
0.04448306 French_Seine-Maritime
0.05682986 Danish
0.05706810 French_Bearn
0.05731472 Norwegian
0.05856269 Spanish_Cataluna
0.10025871 Estonian
0.11835914 Latvian
0.19531619 Palestinian_Beit_Sahour
0.21397925 Tajik_Afghanistan
0.23952120 Balochi_Pakistan

[cass]

Let's see what it looks like if you use the real Danish and Swedish averages in such a calculator. A good example of how the G25 works with built-in overrepresentation of WestMed anchors and the use of drifted samples.

Target: Danish
Distance: 1.4580% / 0.01458013
30.2 Norwegian
22.8 Danish
19.2 Estonian
15.4 French_Seine-Maritime
12.4 Spanish_Cataluna

Target: Swedish
Distance: 1.3160% / 0.01316047
35.2 Estonian
31.0 Danish
16.0 Norwegian
7.6 French_Seine-Maritime
6.4 Spanish_Cataluna
3.4 French_Bearn
0.4 Tajik_Afghanistan

Distance to: Danish
0.02995623 Norwegian
0.03067104 Danish:414
0.04301458 French_Seine-Maritime
0.06713485 Estonian
0.07610696 Spanish_Cataluna
0.08489738 French_Bearn
0.09428324 Latvian
0.19272025 Tajik_Afghanistan
0.20632258 Palestinian_Beit_Sahour
0.22458979 Balochi_Pakistan

Distance to: Swedish
0.03079885 Danish:414
0.03705650 Norwegian
0.05336262 Estonian
0.05433633 French_Seine-Maritime
0.08221886 Latvian
0.08539343 Spanish_Cataluna
0.09507608 French_Bearn
0.19144136 Tajik_Afghanistan
0.21475437 Palestinian_Beit_Sahour
0.22629404 Balochi_Pakistan

[Grace O'Malley]

Target: Grace_scaled
Distance: 2.7307% / 0.02730663 | ADC: 0.25x RC
46.8 Danish
28.6 French_Seine-Maritime
12.8 Estonian
6.2 French_Bearn
5.6 Norwegian

[Upsilander]

Let's see what it looks like if you use the real Danish and Swedish averages in such a calculator. A good example of how the G25 works with built-in overrepresentation of WestMed anchors and the use of drifted samples.

Target: Danish
Distance: 1.4580% / 0.01458013
30.2 Norwegian
22.8 Danish
19.2 Estonian
15.4 French_Seine-Maritime
12.4 Spanish_Cataluna

Target: Swedish
Distance: 1.3160% / 0.01316047
35.2 Estonian
31.0 Danish
16.0 Norwegian
7.6 French_Seine-Maritime
6.4 Spanish_Cataluna
3.4 French_Bearn
0.4 Tajik_Afghanistan

Distance to: Danish
0.02995623 Norwegian
0.03067104 Danish:414
0.04301458 French_Seine-Maritime
0.06713485 Estonian
0.07610696 Spanish_Cataluna
0.08489738 French_Bearn
0.09428324 Latvian
0.19272025 Tajik_Afghanistan
0.20632258 Palestinian_Beit_Sahour
0.22458979 Balochi_Pakistan

Distance to: Swedish
0.03079885 Danish:414
0.03705650 Norwegian
0.05336262 Estonian
0.05433633 French_Seine-Maritime
0.08221886 Latvian
0.08539343 Spanish_Cataluna
0.09507608 French_Bearn
0.19144136 Tajik_Afghanistan
0.21475437 Palestinian_Beit_Sahour
0.22629404 Balochi_Pakistan

Using the "valentine's average collection", it actually gives me more of it with the average, so used all individuals samples and used the ones that created more separation

With the averages

Target: Upsilander_Scaled
Distance: 2.2493% / 0.02249271
43.2 Danish
20.0 French_Bearn
17.8 Latvian
11.8 French_Seine-Maritime
7.2 Spanish_Cataluna

Without

Target: Upsilander_Scaled
Distance: 2.3181% / 0.02318077
23.4 French_Bearn
21.2 French_Seine-Maritime
17.0 Danish
16.0 Estonian
10.6 Latvian
6.4 Spanish_Cataluna
5.4 Norwegian

But you can try both, same with Cataluna


Danish,0.13112418,0.13513707,0.066324435,0.0522766 ,0.041437471,0.019368141,0.0051036941,0.0074196,0. 0033758588,-0.0026262824,-0.0053511647,0.0034098588,-0.0084526588,-0.0068843294,0.018785318,0.0059150706,-0.0067217412,0.0019898235,0.0033982706,0.004321152 9,0.0055064235,0.0023610235,0.00073516471,0.013840 247,0.00044803529
Norwegian,0.13180044,0.12968906,0.067948176,0.0548 15,0.040704324,0.019784735,0.0042922353,0.00595888 24,0.0061958529,-0.0029425,-0.0047667353,0.0042889412,-0.0094224412,-0.0096295588,0.020162441,0.0055805,-0.0079840588,0.0034354412,0.0034492647,0.004682323 5,0.0056077059,0.0036114118,0.00018114706,0.013286 618,-0.00023594118
Spanish_Catalonia_(Catalan),0.114582,0.14623633,0. 045883333,0.0023686667,0.047188333,-2.8912058e-19,-0.0020366667,0.0023843333,0.022361333,0.030494333,-0.0018946667,0.0085923333,-0.016006,-0.010642667,0.0088673333,0.001591,-0.000652,-0.001647,-0.001131,-0.00095866667,0.0061973333,-0.005729,-0.0039026667,-0.001928,0.00095766667


Target: Danish
Distance: 0.6330% / 0.00633021
80.8 Norwegian
10.2 French_Seine-Maritime
5.8 Estonian
3.2 Spanish_Cataluna

[Balboa]

Target: Balboa
Distance: 4.5455% / 0.04545458
57.4 French_Bearn
42.6 Palestinian_Beit_Sahour

[Flashball]

Target: Father(PicardieNorthernFrance)
Distance: 2.0034% / 0.02003449
53.6 Norwegian
40.8 French_Bearn
4.6 Balochi_Pakistan
1.0 French_Seine-Maritime



Distance to: Father(PicardieNorthernFrance)
0.03732027 French_Seine-Maritime
0.04517142 Norwegian
0.05705596 Danish:414
0.05840771 French_Bearn
0.06355190 Spanish_Cataluna
0.10400554 Estonian
0.12300405 Latvian
0.18745442 Palestinian_Beit_Sahour
0.19035207 Tajik_Afghanistan
0.21883648 Balochi_Pakistan

[cass]

Using the "valentine's average collection", it actually gives me more of it with the average, so used all individuals samples and used the ones that created more separation

With the averages

Target: Upsilander_Scaled
Distance: 2.2493% / 0.02249271
43.2 Danish
20.0 French_Bearn
17.8 Latvian
11.8 French_Seine-Maritime
7.2 Spanish_Cataluna

Without

Target: Upsilander_Scaled
Distance: 2.3181% / 0.02318077
23.4 French_Bearn
21.2 French_Seine-Maritime
17.0 Danish
16.0 Estonian
10.6 Latvian
6.4 Spanish_Cataluna
5.4 Norwegian

But you can try both, same with Cataluna


Danish,0.13112418,0.13513707,0.066324435,0.0522766 ,0.041437471,0.019368141,0.0051036941,0.0074196,0. 0033758588,-0.0026262824,-0.0053511647,0.0034098588,-0.0084526588,-0.0068843294,0.018785318,0.0059150706,-0.0067217412,0.0019898235,0.0033982706,0.004321152 9,0.0055064235,0.0023610235,0.00073516471,0.013840 247,0.00044803529
Norwegian,0.13180044,0.12968906,0.067948176,0.0548 15,0.040704324,0.019784735,0.0042922353,0.00595888 24,0.0061958529,-0.0029425,-0.0047667353,0.0042889412,-0.0094224412,-0.0096295588,0.020162441,0.0055805,-0.0079840588,0.0034354412,0.0034492647,0.004682323 5,0.0056077059,0.0036114118,0.00018114706,0.013286 618,-0.00023594118
Spanish_Catalonia_(Catalan),0.114582,0.14623633,0. 045883333,0.0023686667,0.047188333,-2.8912058e-19,-0.0020366667,0.0023843333,0.022361333,0.030494333,-0.0018946667,0.0085923333,-0.016006,-0.010642667,0.0088673333,0.001591,-0.000652,-0.001647,-0.001131,-0.00095866667,0.0061973333,-0.005729,-0.0039026667,-0.001928,0.00095766667


Target: Danish
Distance: 0.6330% / 0.00633021
80.8 Norwegian
10.2 French_Seine-Maritime
5.8 Estonian
3.2 Spanish_Cataluna

In my opinion, if you expect results limited to 3-5 extreme populations, there are better tools than G25, e.g. EgyK3-K9. They accurately set reference points on a given population.

[Gallop]

Target: Gallop_scaled
Distance: 2.5444% / 0.02544443
52.4 French_Bearn
29.4 Spanish_Cataluna
9.4 Palestinian_Beit_Sahour
7.8 Norwegian
1.0 Tajik_Afghanistan

Target: Father_scaled
Distance: 2.7381% / 0.02738078
42.6 Spanish_Cataluna
42.4 French_Bearn
10.6 Palestinian_Beit_Sahour
4.4 Latvian

Target: brother_scaled
Distance: 2.8314% / 0.02831405
51.0 French_Bearn
34.8 Spanish_Cataluna
12.6 Palestinian_Beit_Sahour
1.6 Latvian

[Gallop]

Andalusia x Catalonia

Target: Gallop_scaled
Distance: 2.6035% / 0.02603505
71.8 French_Bearn
10.4 Palestinian_Beit_Sahour
8.0 Norwegian
5.6 Spanish_Andalucia
4.2 Danish

Target: Father_scaled
Distance: 3.0038% / 0.03003800
73.0 French_Bearn
13.2 Palestinian_Beit_Sahour
9.6 Estonian
4.2 Spanish_Andalucia

Target: brother_scaled
Distance: 3.0327% / 0.03032726
76.4 French_Bearn
14.8 Palestinian_Beit_Sahour
5.6 Estonian
3.2 Spanish_Andalucia


:cool:

[Athalafuns]

Target: RNB27
Distance: 2.0874% / 0.02087362
38.4 Spanish_Cataluna
32.4 French_Bearn
16.2 Norwegian
11.8 Palestinian_Beit_Sahour
1.2 Balochi_Pakistan

Distance to: RNB27
0.03330850 Spanish_Cataluna
0.04306325 French_Bearn
0.06011094 French_Seine-Maritime
0.08288353 Danish:414
0.08362747 Norwegian
0.12972577 Estonian
0.15007519 Latvian
0.15238917 Palestinian_Beit_Sahour
0.19094974 Tajik_Afghanistan
0.21427516 Balochi_Pakistan

-------

With alternative samples:

Target: RNB27
Distance: 1.8667% / 0.01866670
81.8 Spanish_Catalonia_(Catalan)
9.0 Norwegian
6.0 Palestinian_Beit_Sahour
2.2 Tajik_Afghanistan
1.0 French_Bearn

Distance to: RNB27
0.02224449 Spanish_Catalonia_(Catalan)
0.04306325 French_Bearn
0.06011094 French_Seine-Maritime
0.07658217 Danish
0.07891178 Norwegian
0.12972577 Estonian
0.15007519 Latvian
0.15238917 Palestinian_Beit_Sahour
0.19094974 Tajik_Afghanistan
0.21427516 Balochi_Pakistan

[cass]

Target: RNB27
Distance: 2.0874% / 0.02087362
38.4 Spanish_Cataluna
32.4 French_Bearn
16.2 Norwegian
11.8 Palestinian_Beit_Sahour
1.2 Balochi_Pakistan

Distance to: RNB27
0.03330850 Spanish_Cataluna
0.04306325 French_Bearn
0.06011094 French_Seine-Maritime
0.08288353 Danish:414
0.08362747 Norwegian
0.12972577 Estonian
0.15007519 Latvian
0.15238917 Palestinian_Beit_Sahour
0.19094974 Tajik_Afghanistan
0.21427516 Balochi_Pakistan

-------

With alternative samples:

Target: RNB27
Distance: 1.8667% / 0.01866670
81.8 Spanish_Catalonia_(Catalan)
9.0 Norwegian
6.0 Palestinian_Beit_Sahour
2.2 Tajik_Afghanistan
1.0 French_Bearn

Distance to: RNB27
0.02224449 Spanish_Catalonia_(Catalan)
0.04306325 French_Bearn
0.06011094 French_Seine-Maritime
0.07658217 Danish
0.07891178 Norwegian
0.12972577 Estonian
0.15007519 Latvian
0.15238917 Palestinian_Beit_Sahour
0.19094974 Tajik_Afghanistan
0.21427516 Balochi_Pakistan

Throw in 1 Celt and both Celts and you'll see how sample limiting works in the G25 mechanism.

Irish,0.13348786,0.13421198,0.061490713,0.04913036 2,0.037682915,0.019507468,0.0031975426,0.004725595 7,0.0037010106,0.0026656489,-0.0068444681,0.0057682979,-0.014125883,-0.013712457,0.025906638,0.0050425745,-0.011339266,0.0019718298,0.00084242553,0.001584489 4,0.0050629043,0.001637734,0.00069488298,0.0144803 09,0.00080768085
Irish_Ulster,0.129758,0.136081,0.064111,0.055556,0 .037853,0.019801,0.007285,0.007154,0.000818,0.0087 47,-0.006496,0.008243,-0.017096,-0.017616,0.027416,0.005701,-0.010822,-0.000887,-0.005656,0.002876,-0.000499,0.007914,-0.003944,0.014942,-0.003952

[Athalafuns]

Throw in 1 Celt and both Celts and you'll see how sample limiting works in the G25 mechanism.
1 Celt

Target: RNB27
Distance: 2.0949% / 0.02094853
38.2 Spanish_Cataluna
31.0 French_Bearn
16.0 Norwegian
13.0 Palestinian_Beit_Sahour
1.8 Irish


2 Celts

Target: RNB27
Distance: 2.0824% / 0.02082375
36.8 Spanish_Cataluna
30.6 French_Bearn
13.4 Palestinian_Beit_Sahour
12.2 Norwegian
7.0 Irish_Ulster

[cass]

1 Celt

Target: RNB27
Distance: 2.0949% / 0.02094853
38.2 Spanish_Cataluna
31.0 French_Bearn
16.0 Norwegian
13.0 Palestinian_Beit_Sahour
1.8 Irish


2 Celts

Target: RNB27
Distance: 2.0824% / 0.02082375
36.8 Spanish_Cataluna
30.6 French_Bearn
13.4 Palestinian_Beit_Sahour
12.2 Norwegian
7.0 Irish_Ulster

And try the variant with only Irish_Ulster.

[Upsilander]

And try the variant with only Irish_Ulster.


No difference since there are enough references for him to be modeled as something else than just Baltic or Sardinian.

This type of calculator is exactly what was spammed on gedmatch for a decade. Scoring either something Baltic or Basque or Sardinian, so it appeared that everybody was "southern European", except those who created them.

[djipon]

Target: djipon_AncestryDNA_scaled
Distance: 3.0507% / 0.03050654
38.4 Palestinian_Beit_Sahour
29.8 Latvian
17.8 Spanish_Cataluna
10.2 French_Seine-Maritime
3.8 Norwegian

[Athalafuns]

And try the variant with only Irish_Ulster.
Target: RNB27
Distance: 2.0824% / 0.02082375
36.8 Spanish_Cataluna
30.6 French_Bearn
13.4 Palestinian_Beit_Sahour
12.2 Norwegian
7.0 Irish_Ulster

[cass]

No difference since there are enough references for him to be modeled as something else than just Baltic or Sardinian.

This type of calculator is exactly what was spammed on gedmatch for a decade. Scoring either something Baltic or Basque or Sardinian, so it appeared that everybody was "southern European", except those who created them.


I checked it on his sample and there was a difference. The extra Irish ate the Tajik's surplus Yamnaya and some of the Palestinian, despite the fact that the extra sample shouldn't have changed anything. In this case, the result may be different in each round. Whenever you have too few samples and test an individual away from the G25 reference points, you get random results.



Target: RNB27_Scaled
Distance: 1.8436% / 0.01843560
76.6 Spanish_Catalonia_(Catalan)
14.0 Irish_Ulster
8.4 Palestinian_Beit_Sahour
0.6 Spanish_Cataluna
0.4 Danish

Target: RNB27_Scaled
Distance: 1.8632% / 0.01863175
83.4 Spanish_Catalonia_(Catalan)
5.6 Palestinian_Beit_Sahour
3.8 Danish
3.2 Norwegian
2.2 Tajik_Afghanistan
1.8 Irish

[celticdragongod]

Distance to: CDG_scaled
0.02624009 Norwegian
0.03456581 Danish:414
0.04309981 French_Seine-Maritime
0.07739867 Estonian
0.07825673 Spanish_Cataluna
0.08418461 French_Bearn
0.10011557 Latvian
0.19161902 Tajik_Afghanistan
0.20398451 Palestinian_Beit_Sahour
0.22351471 Balochi_Pakistan

Target: CDG_scaled
Distance: 1.9395% / 0.01939502
56.0 Norwegian
24.2 Danish:414
7.0 French_Seine-Maritime
5.8 Spanish_Cataluna
3.2 French_Bearn
3.0 Estonian
0.8 Balochi_Pakistan

[celticdragongod]

Throw in 1 Celt and both Celts and you'll see how sample limiting works in the G25 mechanism.

Irish,0.13348786,0.13421198,0.061490713,0.04913036 2,0.037682915,0.019507468,0.0031975426,0.004725595 7,0.0037010106,0.0026656489,-0.0068444681,0.0057682979,-0.014125883,-0.013712457,0.025906638,0.0050425745,-0.011339266,0.0019718298,0.00084242553,0.001584489 4,0.0050629043,0.001637734,0.00069488298,0.0144803 09,0.00080768085
Irish_Ulster,0.129758,0.136081,0.064111,0.055556,0 .037853,0.019801,0.007285,0.007154,0.000818,0.0087 47,-0.006496,0.008243,-0.017096,-0.017616,0.027416,0.005701,-0.010822,-0.000887,-0.005656,0.002876,-0.000499,0.007914,-0.003944,0.014942,-0.003952

Distance to: CDG_scaled
0.01798938 Irish
0.02624009 Norwegian
0.02799479 Irish_Ulster
0.03456581 Danish:414
0.04309981 French_Seine-Maritime
0.07739867 Estonian
0.07825673 Spanish_Cataluna
0.08418461 French_Bearn
0.10011557 Latvian
0.19161902 Tajik_Afghanistan
0.20398451 Palestinian_Beit_Sahour
0.22351471 Balochi_Pakistan

Target: CDG_scaled
Distance: 1.3884% / 0.01388407
61.4 Irish
28.4 Norwegian
5.0 Danish:414
3.0 Latvian
1.8 Spanish_Cataluna
0.4 Palestinian_Beit_Sahour

[celticdragongod]

Using the "valentine's average collection", it actually gives me more of it with the average, so used all individuals samples and used the ones that created more separation

With the averages

Target: Upsilander_Scaled
Distance: 2.2493% / 0.02249271
43.2 Danish
20.0 French_Bearn
17.8 Latvian
11.8 French_Seine-Maritime
7.2 Spanish_Cataluna

Without

Target: Upsilander_Scaled
Distance: 2.3181% / 0.02318077
23.4 French_Bearn
21.2 French_Seine-Maritime
17.0 Danish
16.0 Estonian
10.6 Latvian
6.4 Spanish_Cataluna
5.4 Norwegian

But you can try both, same with Cataluna


Danish,0.13112418,0.13513707,0.066324435,0.0522766 ,0.041437471,0.019368141,0.0051036941,0.0074196,0. 0033758588,-0.0026262824,-0.0053511647,0.0034098588,-0.0084526588,-0.0068843294,0.018785318,0.0059150706,-0.0067217412,0.0019898235,0.0033982706,0.004321152 9,0.0055064235,0.0023610235,0.00073516471,0.013840 247,0.00044803529
Norwegian,0.13180044,0.12968906,0.067948176,0.0548 15,0.040704324,0.019784735,0.0042922353,0.00595888 24,0.0061958529,-0.0029425,-0.0047667353,0.0042889412,-0.0094224412,-0.0096295588,0.020162441,0.0055805,-0.0079840588,0.0034354412,0.0034492647,0.004682323 5,0.0056077059,0.0036114118,0.00018114706,0.013286 618,-0.00023594118
Spanish_Catalonia_(Catalan),0.114582,0.14623633,0. 045883333,0.0023686667,0.047188333,-2.8912058e-19,-0.0020366667,0.0023843333,0.022361333,0.030494333,-0.0018946667,0.0085923333,-0.016006,-0.010642667,0.0088673333,0.001591,-0.000652,-0.001647,-0.001131,-0.00095866667,0.0061973333,-0.005729,-0.0039026667,-0.001928,0.00095766667


Target: Danish
Distance: 0.6330% / 0.00633021
80.8 Norwegian
10.2 French_Seine-Maritime
5.8 Estonian
3.2 Spanish_Cataluna

Distance to: CDG_scaled
0.01919413 Danish
0.01997112 Norwegian
0.07538632 Spanish_Catalonia_(Catalan)

Target: CDG_scaled
Distance: 1.8447% / 0.01844690
47.4 Danish
46.0 Norwegian
6.6 Spanish_Catalonia_(Catalan)

[pelikarski]

Target: DDimitrov_scaled
Distance: 2.9005% / 0.02900469 | R4P
32.2 Latvian
29.6 Palestinian_Beit_Sahour
21.2 Danish
17.0 Spanish_Cataluna

[tk'es]

Target: tk'es_scaled
Distance: 7.4979% / 0.07497904
38.8 Tajik_Afghanistan
33.6 Palestinian_Beit_Sahour
24.6 Norwegian
3.0 Balochi_Pakistan



Target: tk'es_scaled
Distance: 7.5766% / 0.07576623 | ADC: 2x RC
43.2 Tajik_Afghanistan
30.2 Palestinian_Beit_Sahour
26.6 French_Seine-Maritime

[ScandinavianCelt]

Distance to: CDG_scaled
0.02624009 Norwegian
0.03456581 Danish:414
0.04309981 French_Seine-Maritime
0.07739867 Estonian
0.07825673 Spanish_Cataluna
0.08418461 French_Bearn
0.10011557 Latvian
0.19161902 Tajik_Afghanistan
0.20398451 Palestinian_Beit_Sahour
0.22351471 Balochi_Pakistan

Target: CDG_scaled
Distance: 1.9395% / 0.01939502
56.0 Norwegian
24.2 Danish:414
7.0 French_Seine-Maritime
5.8 Spanish_Cataluna
3.2 French_Bearn
3.0 Estonian
0.8 Balochi_Pakistan


Distance to: CDG_scaled
0.01798938 Irish
0.02624009 Norwegian
0.02799479 Irish_Ulster
0.03456581 Danish:414
0.04309981 French_Seine-Maritime
0.07739867 Estonian
0.07825673 Spanish_Cataluna
0.08418461 French_Bearn
0.10011557 Latvian
0.19161902 Tajik_Afghanistan
0.20398451 Palestinian_Beit_Sahour
0.22351471 Balochi_Pakistan

Target: CDG_scaled
Distance: 1.3884% / 0.01388407
61.4 Irish
28.4 Norwegian
5.0 Danish:414
3.0 Latvian
1.8 Spanish_Cataluna
0.4 Palestinian_Beit_Sahour

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

without and with Irish samples above:


without Irish:

Target: SC_Official_Ancestry#2_Scaled
Distance: 1.8689% / 0.01868875
34.8 Norwegian
23.4 Danish:414
21.0 Spanish_Cataluna
15.0 Estonian
5.8 Balochi_Pakistan


with Irish:

Target: SC_Official_Ancestry#2_Scaled
Distance: 1.4691% / 0.01469122
50.6 Irish
14.4 Estonian
13.2 Spanish_Cataluna
8.6 Norwegian
8.4 Danish:414
4.0 Balochi_Pakistan
0.8 Tajik_Afghanistan

[Jingle Bell]

Target: JingleBell_Dad_scaled
Distance: 0.6289% / 0.00628922
36.0 SSA
30.4 Spanish_Cataluna
15.2 Palestinian_Beit_Sahour
10.8 French_Bearn
5.6 AMERINDIAN
1.4 Danish
0.6 Estonian

Target: JingleBell_scaled
Distance: 1.8435% / 0.01843527
46.2 SSA
26.2 French_Bearn
13.0 Spanish_Cataluna
11.4 Palestinian_Beit_Sahour
2.2 AMERINDIAN
1.0 Balochi_Pakistan

[Damião de Góis]

I was expecting the model to favour Catalonia ahead of the rest of the samples:


Target: Gil_Vicente
Distance: 2.7556% / 0.02755573
53.8 French_Bearn
18.4 Norwegian
14.4 Palestinian_Beit_Sahour
9.6 Spanish_Cataluna
3.8 Balochi_Pakistan

But i noticed my distance to Catalonia was bigger than it is on G25, which means this Catalonia sample is different.


Distance to: Gil_Vicente
0.04652037 Spanish_Cataluna
0.04728802 French_Bearn
0.06488606 French_Seine-Maritime
0.08655059 Norwegian
0.09213272 Danish
0.13548323 Estonian
0.14905499 Palestinian_Beit_Sahour
0.15382108 Latvian
0.18985729 Tajik_Afghanistan
0.20958702 Balochi_Pakistan

If i try with the original Catalonia sample then i get this:

Target: Gil_Vicente
Distance: 2.5643% / 0.02564349
54.4 Spanish_Cataluna
23.0 French_Bearn
9.8 Norwegian
8.0 Palestinian_Beit_Sahour
4.8 Balochi_Pakistan

[vader]

Target: Algarvio_scaled
Distance: 2.0880% / 0.02088034
47.4 Spanish_Cataluna
33.0 French_Bearn
14.8 Palestinian_Beit_Sahour
4.6 Norwegian
0.2 Estonian

Distance to: Algarvio_scaled
0.03343263 Spanish_Cataluna
0.04436193 French_Bearn
0.07051677 French_Seine-Maritime
0.09514572 Danish
0.09537421 Norwegian
0.13855157 Estonian
0.14568660 Palestinian_Beit_Sahour
0.15960841 Latvian
0.19251756 Tajik_Afghanistan
0.21551239 Balochi_Pakistan

[cass]

I was expecting the model to favour Catalonia ahead of the rest of the samples:


Target: Gil_Vicente
Distance: 2.7556% / 0.02755573
53.8 French_Bearn
18.4 Norwegian
14.4 Palestinian_Beit_Sahour
9.6 Spanish_Cataluna
3.8 Balochi_Pakistan

But i noticed my distance to Catalonia was bigger than it is on G25, which means this Catalonia sample is different.


Distance to: Gil_Vicente
0.04652037 Spanish_Cataluna
0.04728802 French_Bearn
0.06488606 French_Seine-Maritime
0.08655059 Norwegian
0.09213272 Danish
0.13548323 Estonian
0.14905499 Palestinian_Beit_Sahour
0.15382108 Latvian
0.18985729 Tajik_Afghanistan
0.20958702 Balochi_Pakistan

If i try with the original Catalonia sample then i get this:

Target: Gil_Vicente
Distance: 2.5643% / 0.02564349
54.4 Spanish_Cataluna
23.0 French_Bearn
9.8 Norwegian
8.0 Palestinian_Beit_Sahour
4.8 Balochi_Pakistan

Catalan too? This is ridiculous.

[Fabricius]

Target: Fabricius_simulated_g25_scaled
Distance: 5.4622% / 0.05462209 | R3P
61.2 Spanish_Cataluna
23.4 Palestinian_Beit_Sahour
15.4 Latvian

Target: Fabricius_simulated_g25_scaled
Distance: 6.6160% / 0.06615991 | ADC: 1x RC
100.0 Spanish_Cataluna

Target: Fabricius_simulated_g25_scaled
Distance: 5.5034% / 0.05503372 | ADC: 0.5x RC
58.6 Spanish_Cataluna
18.8 Norwegian
18.2 Palestinian_Beit_Sahour
2.2 Balochi_Pakistan
2.2 Tajik_Afghanistan

Target: Fabricius_simulated_g25_scaled
Distance: 5.4299% / 0.05429872 | ADC: 0.25x RC
59.0 Spanish_Cataluna
21.2 Palestinian_Beit_Sahour
10.6 Latvian
6.4 Norwegian
2.8 Tajik_Afghanistan

Target: Fabricius_simulated_g25_scaled
Distance: 5.4260% / 0.05426020
52.0 Spanish_Cataluna
21.6 Palestinian_Beit_Sahour
7.8 Latvian
6.4 French_Bearn
4.6 Estonian
4.6 Norwegian
2.8 Tajik_Afghanistan
0.2 Balochi_Pakistan


Distance to: Fabricius_simulated_g25_scaled
0.06615991 Spanish_Cataluna
0.08059232 French_Bearn
0.08797214 French_Seine-Maritime
0.10229057 Norwegian
0.10770084 Danish
0.13657082 Estonian
0.14661748 Palestinian_Beit_Sahour
0.15592513 Latvian
0.18305080 Tajik_Afghanistan
0.20438379 Balochi_Pakistan

***

With North and Central African samples:

Target: Fabricius_simulated_g25_scaled
Distance: 2.4139% / 0.02413939 | ADC: 0.5x RC
34.6 Spanish_Cataluna
33.4 Norwegian
28.8 North-African
3.2 French_Seine-Maritime

Target: Fabricius_simulated_g25_scaled
Distance: 1.0415% / 0.01041483 | ADC: 0.25x RC
25.6 French_Bearn
21.8 Spanish_Cataluna
15.8 Latvian
11.6 Palestinian_Beit_Sahour
11.2 North-African
9.0 Norwegian
5.0 SSA

Target: Fabricius_simulated_g25_scaled
Distance: 1.0390% / 0.01039039
26.4 French_Bearn
21.2 Spanish_Cataluna
16.0 Latvian
12.2 Palestinian_Beit_Sahour
10.4 North-African
8.6 Norwegian
5.2 SSA

[R1b-L51]

ABSURDATION DAMNATION

Target: ROBERTOFERN_scaled
Distance: 2.8030% / 0.02803014 | ADC: 0.5x RC
50.4 French_Bearn
33.4 Spanish_Cataluna
11.6 Palestinian_Beit_Sahour
4.6 Tajik_Afghanistan

Target: ROBERTOFERN_scaled
Distance: 2.7486% / 0.02748560
48.2 French_Bearn
30.4 Spanish_Cataluna
12.0 Palestinian_Beit_Sahour
5.8 Norwegian
3.6 Balochi_Pakistan

Target: ROBERTOFERN_scaled
Distance: 2.7486% / 0.02748560 | ADC: 0.25x RC
48.2 French_Bearn
30.4 Spanish_Cataluna
12.0 Palestinian_Beit_Sahour
5.8 Norwegian
3.6 Balochi_Pakistan


Distance to: ROBERTOFERN_scaled
0.04093499 Spanish_Cataluna
0.04525655 French_Bearn
0.07204308 French_Seine-Maritime
0.09404724 Norwegian
0.09569850 Danish
0.13848652 Estonian
0.14838144 Palestinian_Beit_Sahour
0.15795676 Latvian
0.19111373 Tajik_Afghanistan
0.21291248 Balochi_Pakistan

[Demirkazık]

Target: Demir
Distance: 5.6467% / 0.05646720
47.4 Tajik_Afghanistan
37.2 Palestinian_Beit_Sahour
9.4 Latvian
6.0 Spanish_Cataluna

With additional references for me:

Target: Demir
Distance: 3.0299% / 0.03029851
45.2 Turkmen
39.0 Palestinian_Beit_Sahour
10.6 Latvian
5.2 Norwegian

Target: Demir
Distance: 3.4476% / 0.03447626
50.8 Palestinian_Beit_Sahour
17.8 Latvian
15.6 Tajik_Afghanistan
15.0 Mongolian
0.8 Norwegian

Target: Demir
Distance: 2.2458% / 0.02245819
69.0 Greek_Central_Anatolia
23.0 Khakass_Kyzils
8.0 Estonian