The four corners of Europe, G25 model (Scaled coordinates).

[gixajo]

Target: Adam_Scaled
Distance: 4.1380% / 0.04138046
82.4 NorthAfrica
17.6 SouthWest_Europe


For me mozabites are not a good reference, Moroccan_North is I think the best reference for me.

Algerian average use to be quite strange also(at least Algerian Berber in datasheet is), maybe Moroccan+Tunisian would have been enough for you or the Berber average I made times ago:

Berber=MAR_ERR,+MAR_TIZ,+Tunisia_Chen,+Tunisia_Sen

Berber,-0.06548320,0.13410613,-0.00816420,-0.07538218,0.02581348,-0.03472953,-0.02944445,0.00831648,0.06752790,0.02796198,0.00707855,-0.00796418,0.02308645,-0.01552258,0.01677808,-0.01294335,-0.00285148,-0.02166338,-0.04415378,0.01019313,-0.01565483,-0.03933808,0.02467100,-0.00293920,0.00493865

[someonenotyou]

Target:
Distance: 1.5600% / 0.01559951
39.0 NorthWest_Europe
33.4 SouthEast_Europe
27.6 NorthEast_Europe

[Adamm]

Algerian average use to be quite strange also(at least Algerian Berber in datasheet is), maybe Moroccan+Tunisian would have been enough for you or the Berber average I made times ago:

Berber=MAR_ERR,+MAR_TIZ,+Tunisia_Chen,+Tunisia_Sen

Berber,-0.06548320,0.13410613,-0.00816420,-0.07538218,0.02581348,-0.03472953,-0.02944445,0.00831648,0.06752790,0.02796198,0.00707855,-0.00796418,0.02308645,-0.01552258,0.01677808,-0.01294335,-0.00285148,-0.02166338,-0.04415378,0.01019313,-0.01565483,-0.03933808,0.02467100,-0.00293920,0.00493865

This one is better:

Target: Adam_Scaled
Distance: 2.6646% / 0.02664557
80.6 NorthAfrica
10.2 SouthEast_Europe
9.2 SouthWest_Europe

But MAR_ERR and TIZ are southern Moroccan samples, some of them are heavily SSA.

[calxpal]

Target: cpalscaled
Distance: 2.9939% / 0.02993914
55.4 NorthWest_Europe
22.4 SouthEast_Europe
19.6 NorthEast_Europe
2.6 SouthWest_Europe

Distance to: cpalscaled
0.04382651 NorthWest_Europe
0.06624281 NorthEast_Europe
0.07289130 SouthWest_Europe
0.09034920 SouthEast_Europe

[alnortedelsur]

Adding a Northern African reference:

Target: Alnortedelsur_scaled
Distance: 2.2253% / 0.02225309
65.4 SouthWest_Europe
15.2 SouthEast_Europe
8.6 NorthAfrica
7.6 Amerindian
3.0 SSA
0.2 NorthWest_Europe

Target: Alnortedelsur_scaled
Distance: 2.4083% / 0.02408311 | ADC: 0.25x
68.6 SouthWest_Europe
12.4 SouthEast_Europe
10.4 NorthAfrica
6.8 Amerindian
1.8 SSA

Target: Alnortedelsur_scaled
Distance: 3.5943% / 0.03594322 | ADC: 0.5x
76.0 SouthWest_Europe
12.2 NorthAfrica
7.2 SouthEast_Europe
4.6 Amerindian

Distance to: Alnortedelsur_scaled
0.07180823 SouthWest_Europe
0.08671800 SouthEast_Europe
0.11169428 NorthWest_Europe
0.13240506 NorthEast_Europe
0.18250690 NorthAfrica
0.57103004 Amerindian
0.70151842 SSA:B

Credits again to Gixajo.

[gixajo]

This one is better:

Target: Adam_Scaled
Distance: 2.6646% / 0.02664557
80.6 NorthAfrica
10.2 SouthEast_Europe
9.2 SouthWest_Europe

But MAR_ERR and TIZ are southern Moroccan samples, some of them are heavily SSA.

And Tunisia samples have usually many European input (same than moroccan North), so they compensate between them.

You can always suggest me a new average when you want.

[mitalit]

And adding those 2?

Arabian,=Saudi,+(Yemenite_Al_Jawf,+Yemenite_Mahra, )
Levantine=(Levant_Yehud_IBA,+Levant_Ashkelon_IA1,) +Palestinian_Beit_Sahour

NorthAfrica,-0.0673137,0.1314590,-0.0116907,-0.0712517,0.0206577,-0.0312307,-0.0239980,0.0074100,0.0542707,0.0230963,0.0068190,-0.0077440,0.0248620,-0.0128367,0.0141237,-0.0078340,-0.0032800,-0.0154520,-0.0330237,0.0072563,-0.0099777,-0.0268773,0.0190723,-0.0015783,0.0024743
NorthWest_Europe,0.1325593,0.1337507,0.0638800,0.0508907,0.0394997,0.0199777,0.0031217,0.0057113,0.0037393,-0.0007613,-0.0054230,0.0055750,-0.0099407,-0.0108430,0.0222443,0.0036457,-0.0109377,0.0022727,0.0024637,0.0005757,0.0058040,0.0025773,0.0010957,0.0142847,0.0009677
NorthEast_Europe,0.1310153,0.1214563,0.0711987,0.0603063,0.0356400,0.0220150,0.0089957,0.0116723,-0.0034180,-0.0234717,-0.0007067,-0.0075860,0.0157850,0.0231097,-0.0123050,-0.0018747,0.0027710,-0.0005210,0.0028207,0.0022073,-0.0037993,-0.0040860,0.0049800,-0.0048143,-0.0007887
SouthWest_Europe,0.1127253,0.1464038,0.0406260,-0.0010165,0.0449500,-0.0025714,-0.0027779,0.0015101,0.0246433,0.0325341,-0.0026677,0.0075804,-0.0142454,-0.0123391,0.0108006,-0.0001258,-0.0041015,-0.0006735,-0.0030864,-0.0014932,0.0036968,-0.0019572,-0.0022307,-0.0031847,0.0014280
SouthEast_Europe,0.1168672,0.1439147,0.0075187,-0.0235787,0.0165243,-0.0061066,0.0025563,0.0000703,-0.0000882,0.0123834,0.0017905,0.0018742,-0.0016914,0.0064181,-0.0128488,-0.0009988,0.0065265,0.0002924,0.0041233,-0.0039529,-0.0074012,0.0008815,0.0023408,0.0002892,-0.0016262


Arabian,0.05059585,0.13995270,-0.06513990,-0.11723870,-0.00940130,-0.04997380,-0.01229238,-0.00808298,0.05608075,-0.00410653,0.01556333,-0.03192903,0.06243548,0.00350273,0.00455410,0.02525745,-0.02140830,0.00386218,0.00015448,0.02687405,0.01263658,0.01614353,-0.00905183,0.00697205,-0.00832413
Levantine,0.08970675,0.15220263,-0.04970895,-0.08630155,-0.00821318,-0.02909195,-0.00308430,-0.00400938,0.01374138,0.01814400,0.00735825,-0.00407470,0.00702445,0.00651988,-0.00855050,0.00501358,-0.00108388,0.00259705,0.00276545,0.00053945,-0.00321313,0.00803751,0.00093205,0.00186763,0.00126450

Target: Xabier_scaled
Distance: 2.5481% / 0.02548054
70.6 SouthWest_Europe
18.4 NorthWest_Europe
9.6 SouthEast_Europe
1.4 NorthAfrica

[Adamm]

And Tunisia samples have usually many European input (same than moroccan North), so they compensate between them.

You can always suggest me a new average when you want.

Could you make an average with these samples:

Berber_Zenatan,-0.01935,0.138112,-0.001131,-0.069445,0.026159,-0.04016,-0.027026,0.003692,0.065243,0.021504,0.001949,-0.010641,0.021556,-0.014038,0.016829,-0.011668,0.004694,-0.02027,-0.04148,0.007879,-0.010731,-0.037838,0.021322,-0.011809,0.005029
Moroccan_North:MNA1,-0.020488,0.131003,0.002263,-0.070737,0.02462,-0.034582,-0.025851,-0.003923,0.06238,0.027518,0.003085,-0.008992,0.023191,-0.007707,0.009093,-0.016176,0.00339,-0.019763,-0.04412,0.007879,-0.009358,-0.032397,0.017871,-0.001325,-0.000479
Mozabite:HGDP01263,-0.027318,0.137096,-0.004525,-0.071706,0.029236,-0.033188,-0.024441,0.011076,0.062789,0.032802,0.004547,-0.006444,0.015461,-0.01734,0.012893,-0.012596,0.004042,-0.01837,-0.043492,0.011631,-0.015098,-0.035859,0.021322,-0.001807,0.006107
Berber_ALG_Chaoui,-0.025041,0.145221,-0.011314,-0.072675,0.033852,-0.032351,-0.028436,0.002308,0.06422,0.0277,0.004222,-0.003447,0.014866,-0.016928,0.014251,-0.010209,0.004042,-0.01989,-0.041857,0.004877,-0.009608,-0.0413,0.025266,0.003253,0.006945

[gixajo]

Could you make an average with these samples:

Ok, but take into account that we must make valid references for all Moroccans, not only references that fit you well, because maybe tomorrow will come new Moroccan members and this reference is not valid for them.

Anyway in future models with many references, I can add also this reference and others.

[Adamm]

Ok, but take into account that we must make valid references for all Moroccans, not only references that fit you well, because maybe tomorrow will come new Moroccan members and this reference is not valid for them.

Anyway in future models with many references, I can add also this reference and others.

Haha I understand, these references are probably a bit biased. How do you make average samples btw?