g25 VS qpadm/admixtools2 comparison.

[kingmob]

Had some time to kill so here goes.

These are my best ‘mixed mode’ results for each period for G25 Illustrative DNA. The raw dna file that was used to produce these results was an extract from my Whole Genome Sequence Nebula Genomics file, that has 99.9% SNP coverage with eurogenes’ template, meaning it is the best possible that could have been used.

https://i.ibb.co/hdTtPW4/Screenshot-2023-12-21-at-13-20-28-ILLUSTRATIVE-DNA.png
https://i.ibb.co/Y7PDXwW/Screenshot-2023-12-21-at-13-20-19-ILLUSTRATIVE-DNA.png




Now, I tried to recreate all these models on qpadm/admixtools2 to check for the validity of my results. The reference samples that were used were the exact same ones used by illustrative DNA, meaning for “Corded Ware Culture” I used: N44, N45, pcw040, pcw041, pcw061, pcw070, pcw211, pcw350, pcw361. The same goes for the rest of the references. The raw dna file that was merged to the Reich dataset was also the same that was used to produce the g25 results.

These are the qpadm/admixtools2 results, using a fairly ‘easy’ right list to give the model some breathway.




> right = c('Mbuti.DG', 'Iran_N', 'Natufian', 'Iberomaurusian', 'Russia_AfontovaGora3', 'Russia_MA1_HG.SG', 'Turkey_Epipaleolithic', 'WHG', 'Iraq_PPN', 'ONG.SG')
> target = c('dosas')
> left = c('Copper_Age_Anatolian','Corded_Ware_Culture')
> results = qpadm(prefix, left, right, target, allsnps = TRUE)
ℹ Reading metadata...
ℹ Computing block lengths for 1150639 SNPs...
ℹ Computing 18 f4-statistics for block 713 out of 713...
ℹ "allsnps = TRUE" uses different SNPs for each f4-statistic
Number of SNPs used for each f4-statistic:
pop1 pop2 pop3 pop4 n
1 dosas Copper_Age_Anatolian Mbuti.DG Iberomaurusian 639471
2 dosas Copper_Age_Anatolian Mbuti.DG Iran_N 613110
3 dosas Copper_Age_Anatolian Mbuti.DG Iraq_PPN 271162
4 dosas Copper_Age_Anatolian Mbuti.DG Natufian 139462
5 dosas Copper_Age_Anatolian Mbuti.DG ONG.SG 665456
6 dosas Copper_Age_Anatolian Mbuti.DG Russia_AfontovaGora3 155549
7 dosas Copper_Age_Anatolian Mbuti.DG Russia_MA1_HG.SG 472363
8 dosas Copper_Age_Anatolian Mbuti.DG Turkey_Epipaleolithic 510849
9 dosas Copper_Age_Anatolian Mbuti.DG WHG 462873
10 dosas Corded_Ware_Culture Mbuti.DG Iberomaurusian 663322
11 dosas Corded_Ware_Culture Mbuti.DG Iran_N 630366
12 dosas Corded_Ware_Culture Mbuti.DG Iraq_PPN 276211
13 dosas Corded_Ware_Culture Mbuti.DG Natufian 140980
14 dosas Corded_Ware_Culture Mbuti.DG ONG.SG 708861
15 dosas Corded_Ware_Culture Mbuti.DG Russia_AfontovaGora3 156781
16 dosas Corded_Ware_Culture Mbuti.DG Russia_MA1_HG.SG 497634
17 dosas Corded_Ware_Culture Mbuti.DG Turkey_Epipaleolithic 524260
18 dosas Corded_Ware_Culture Mbuti.DG WHG 467622
ℹ Computing admixture weights...
ℹ Computing standard errors...
ℹ Computing number of admixture waves...
> results$weights
# A tibble: 2 × 5
target left weight se z
<chr> <chr> <dbl> <dbl> <dbl>
1 dosas Copper_Age_Anatolian 0.622 0.0447 13.9
2 dosas Corded_Ware_Culture 0.378 0.0447 8.45
> results$popdrop
# A tibble: 3 × 13
pat wt dof chisq p f4rank Copper_Age_Anatolian Corded_Ware_Cul…¹ feasi…² best dofdiff chisq…³ p_nes…⁴
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
1 00 0 8 22.1 4.73e- 3 1 0.622 0.378 TRUE NA NA NA NA
2 01 1 9 219. 3.41e-42 0 1 NA TRUE TRUE 0 -270. 1
3 10 1 9 489. 1.26e-99 0 NA 1 TRUE TRUE NA NA NA
# … with abbreviated variable names ¹​Corded_Ware_Culture, ²​feasible, ³​chisqdiff, ⁴​p_nested



The same model gives me 62.2% Copper Age Anatolian (4.47% s.e.) and 37.8% Corded Ware Culture (4.47% s.e.), percentages similar to g25 but the p-value is extremely low at 0.00473 meaning the model is a fail (p.value required above 5%).

Now for the Iron Age, where g25 gives me 49% IA Thracian and 51% Etiuni (Caucasus-Trialeti).





> results = qpadm(prefix, left, right, target, allsnps = TRUE)
ℹ Reading metadata...
ℹ Computing block lengths for 1150639 SNPs...
ℹ Computing 18 f4-statistics for block 713 out of 713...
ℹ "allsnps = TRUE" uses different SNPs for each f4-statistic
Number of SNPs used for each f4-statistic:
pop1 pop2 pop3 pop4 n
1 dosas Etiuni Mbuti.DG Iberomaurusian 657869
2 dosas Etiuni Mbuti.DG Iran_N 627599
3 dosas Etiuni Mbuti.DG Iraq_PPN 275421
4 dosas Etiuni Mbuti.DG Natufian 140826
5 dosas Etiuni Mbuti.DG ONG.SG 693364
6 dosas Etiuni Mbuti.DG Russia_AfontovaGora3 156721
7 dosas Etiuni Mbuti.DG Russia_MA1_HG.SG 489370
8 dosas Etiuni Mbuti.DG Turkey_Epipaleolithic 521589
9 dosas Etiuni Mbuti.DG WHG 467356
10 dosas Thracian Mbuti.DG Iberomaurusian 641747
11 dosas Thracian Mbuti.DG Iran_N 616376
12 dosas Thracian Mbuti.DG Iraq_PPN 272303
13 dosas Thracian Mbuti.DG Natufian 139943
14 dosas Thracian Mbuti.DG ONG.SG 668717
15 dosas Thracian Mbuti.DG Russia_AfontovaGora3 155919
16 dosas Thracian Mbuti.DG Russia_MA1_HG.SG 474445
17 dosas Thracian Mbuti.DG Turkey_Epipaleolithic 512834
18 dosas Thracian Mbuti.DG WHG 464542
ℹ Computing admixture weights...
ℹ Computing standard errors...
ℹ Computing number of admixture waves...
> results$weights
# A tibble: 2 × 5
target left weight se z
<chr> <chr> <dbl> <dbl> <dbl>
1 dosas Thracian 0.542 0.0764 7.10
2 dosas Etiuni 0.458 0.0764 5.99
> results$popdrop
# A tibble: 3 × 13
pat wt dof chisq p f4rank Thracian Etiuni feasible best dofdiff chisqdiff p_nested
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
1 00 0 8 41.7 1.56e- 6 1 0.542 0.458 TRUE NA NA NA NA
2 01 1 9 318. 4.12e-63 0 1 NA TRUE TRUE 0 -74.4 1
3 10 1 9 392. 6.08e-79 0 NA 1 TRUE TRUE NA NA NA



Qpadm gives me roughly the same percentages 54.2% (s.e. 7.64%) for Thracian and 45.8% (s.e. 7.64%) for Etiuni, but the p-value again is abysmally low at 0.00000156 indicating a fail.


I swap around some stufff and run my own model:




eading metadata...
ℹ Computing block lengths for 1150639 SNPs...
ℹ Computing 57 f4-statistics for block 713 out of 713...
ℹ "allsnps = TRUE" uses different SNPs for each f4-statistic
Number of SNPs used for each f4-statistic:
.
.
.
ℹ Computing admixture weights...
ℹ Computing standard errors...
ℹ Computing number of admixture waves...

warning: solve(): system is singular (rcond: 2.0141e-17); attempting approx solution
> results$weights
# A tibble: 3 × 5
target left weight se z
<chr> <chr> <dbl> <dbl> <dbl>
1 dosas Spain_Hellenistic_Emporion 0.390 0.0636 6.12
2 dosas Armenia_LBA.SG 0.527 0.0739 7.13
3 dosas AV2 0.0836 0.0467 1.79
> results$popdrop
# A tibble: 7 × 14
pat wt dof chisq p f4rank Spain_Hellen…¹ Armen…² AV2 feasi…³ best dofdiff
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl>
1 000 0 17 27.3 5.39e- 2 2 0.390 0.527 0.0836 TRUE NA NA


It works.

39% Empuries2 + 52.7% Armenia_LBA + 8.36% Slav AV2. Tail is 5.39% and s.e. almost at 5%.

Before someone mentions the obvious, that this is a 3way model, nowhere on illustrative dna I get a result that is even remotely close to the above.


TLDR:

Those who put their blind faith on their g25 results they should keep in mind that those do not correspond necessarily to proper fstats modelling.

[kingmob]

Bumpity.

[Feiichy]

Apart from fact that samples used here are mixed like Ottoman one, is this legit than?

https://i.ibb.co/q7yxVMW/genetic-map-of-greece-visualized-from-the-latest-study-v0-p1ow6f9xee7c1.jpg

[Jingle Bell]

Interesting, seens that g25 is not that bad at least in admix-estimatives (at least in 2-way models) but the problem is that we cant know if thd model fails or not, if u try a model in g25 with Empuries2 + Armenia LBA + Slav AV2 what results u got? They are similar to qpadm?

[kingmob]

Apart from fact that samples used here are mixed like Ottoman one, is this legit than?






The point is that these genetics don't exist in a vacuum. The model works because the 'ottoman' sample is heavy on the East Med cline.

Modern Greeks and Turks are extremely close when you run fst distances, those small %s of east eurasian that Turks score are not enough to create the exaggerated difference you may see on a PCA (like g25).

As for the rest, Bronze Age Aegean and Roman Anatolia are already so close as to be interchangeable.

Relevant commentary:

https://twitter.com/iosif_lazaridis/status/1737200323926847572

[kingmob]

Interesting, seens that g25 is not that bad at least in admix-estimatives (at least in 2-way models) but the problem is that we cant know if thd model fails or not, if u try a model in g25 with Empuries2 + Armenia LBA + Slav AV2 what results u got? They are similar to qpadm?


g25 tends to exaggerate Eastern Euro, I think the dimensional space reference was tweaked as to be able to differentiate western from eastern euros, of course, unless eg shares his methodology, it's mere speculation from my part.

[HelloGuys]

Maybe is a dumb question, but I am genuinely interested: qpAdm just can model until 3-way? Or you can do more? Like a 4-way, 5-way, etc...There is a possibility?

[kingmob]

Maybe is a dumb question, but I am genuinely interested: qpAdm just can model until 3-way? Or you can do more? Like a 4-way, 5-way, etc...There is a possibility?

Yes, you can add as many references as you want (theoretically) in your left list, but it becomes exponentially harder to score a passing model with big lists.

Southern arc paper managed to model 5-way, which is an impressive feat in itself, and underlines the work it went into extracting decent quality samples, in terms of SNP count, from their archeology.

[kingmob]

So, who wants to give it a shot?

[Avicenna]

So, who wants to give it a shot?

Hey man, can you do one for South central Asians?

[kingmob]

Hey man, can you do one for South central Asians?

I've never done one for south asians before, but I am willing to do it.

What I need from you is to give me the following info you want me to try:

right list: ancestral (neolithic and older) populations to the references (left list) you are going to use for your model.
left list: your model's references.
target: your chosen population, as long as there is a modern reference for it in the HO database, will also check myself of course.

[HelloGuys]

Yes, you can add as many references as you want (theoretically) in your left list, but it becomes exponentially harder to score a passing model with big lists.

Southern arc paper managed to model 5-way, which is an impressive feat in itself, and underlines the work it went into extracting decent quality samples, in terms of SNP count, from their archeology.

Thanks! so theoretically is possible to model myself there? For example for an Iron Age/Classical Antiquity I'd need at least a 5-way or even as much as 7-way due my roots.

[kingmob]

Thanks! so theoretically is possible to model myself there? For example for an Iron Age/Classical Antiquity I'd need at least a 5-way or even as much as 7-way due my roots.

7 is pushing it.

5 could be more realistic.

But, we won't know until we try.

[HelloGuys]

So, who wants to give it a shot?

Could you model the roman Portuguese references? Using a 3-way: Iberia_IA (Sw_Iberia_IA, N_Iberia_IA and E_Iberia_IA labeled the three as Iberia_IA), Roman (Imperial_Rome and Late_Antiquity_Rome labeled the two as Roman) and Mozabite.

[kingmob]

Could you model the roman Portuguese references? Using a 3-way: Iberia_IA (Sw_Iberia_IA, N_Iberia_IA and E_Iberia_IA labeled the three as Iberia_IA), Roman (Imperial_Rome and Late_Antiquity_Rome labeled the two as Roman) and Mozabite.


Can you provide sample IDs?

They exist in the g25 list and also on the illustrative website.

[Jingle Bell]

Could you model the roman Portuguese references? Using a 3-way: Iberia_IA (Sw_Iberia_IA, N_Iberia_IA and E_Iberia_IA labeled the three as Iberia_IA), Roman (Imperial_Rome and Late_Antiquity_Rome labeled the two as Roman) and Mozabite.

U mean Conimbriga, Monte da Nora or Miroico samples?

[HelloGuys]

Can you provide sample IDs?

They exist in the g25 list and also on the illustrative website.

Do you mean this?

Test:
Portugal_Conimbriga_Roman.SG,0.113254,0.146236,0.0 50911,0.007752,0.0486245,0.001952,0.00423,0.001615 5,0.0330305,0.0309805,-0.0025985,0.0082425,-0.019623,-0.0108725,0.0146575,0.005436,0.001499,0.004244,0.0 02514,0.003064,0.006426,0.001422,-0.003636,-0.0091575,0.0025145
Portugal_Miroico_LateRoman_oAfrica.SG,0.068863,0.1 4319,0.021496,-0.0334305,0.0326215,-0.016873,-0.015628,-0.0027695,0.044177,0.0342605,0.0005685,-0.0005245,0.0045345,-0.015276,0.0085505,0.0002655,-0.0007825,-0.0051305,-0.0106845,0.004127,0.007237,-0.012736,0.00228,-0.010483,0.0035925
Portugal_Miroico_LateRoman.SG,0.0984572,0.1428512, 0.0355123,-0.0088825,0.0444697,-0.0058567,-0.0054052,0.0023075,0.0305082,0.0322557,-0.0036808,0.007968,-0.0091178,-0.0163312,0.0095458,0.0004642,0.0001957,-0.0019423,-0.0102235,0.0005212,0.0028285,-0.0021637,0.0010473,-0.0044583,0.0009182
Portugal_MonteDaNora_LateRoman.SG,0.0830907,0.1445 437,0.0235073,-0.0230407,0.0336473,-0.0090173,-0.010262,-0.0005383,0.0289743,0.02934,-0.002057,0.0016487,-0.004757,-0.0084407,0.009817,-0.002961,-0.0033467,-0.0059543,-0.0080027,0.001334,-0.001872,-0.0056057,0.0041903,-0.0041773,-0.00012

Sources:
Iberian_IA:Spain_IA_Celt,0.12179067,0.14657467,0.0 64110667,0.014212,0.058369667,0.0042763333,-0.00517,0.0083073333,0.027610667,0.035657667,-0.000487,0.0085423333,-0.020862,-0.012615333,0.00751,-0.0053036667,-0.0091703333,0.002407,0.0056563333,-0.0032933333,0.0074453333,0.007543,-0.0077643333,-0.0037753333,-0.0053883333
Iberian_IA:Spain_IA,0.12548992,0.14759017,0.058202 25,0.0057870833,0.060241917,-0.0033699167,-0.00217375,0.0032499167,0.0322125,0.045665417,-0.0051153333,0.01255125,-0.023959167,-0.012718667,0.0085164167,0.0066516667,0.0076058333 ,0.00030633333,0.0045148333,-0.0031995,0.0046064167,-0.00012358333,-0.0048784167,-0.012692417,-0.0024948333
Iberian_IA:Spain_EIA_Tartessian:I12171,0.120652,0. 144205,0.056568,-0.006783,0.061858,-0.004183,0.00235,0.009,0.040905,0.049204,0.005034, 0.009442,-0.027354,-0.023671,0.0038,0.009149,0.009779,-0.002914,0.00352,0.003627,0.013227,-0.006925,-0.00419,-0.020364,-0.005269
Roman:Italy_Imperial.SG,0.1088149,0.1499502,-0.0232629,-0.0568757,0.0039744,-0.0205662,-0.0006916,-0.0056899,-0.0031497,0.0210144,0.0036328,0.0025435,-0.0056491,-0.0006134,-0.0106328,-0.0022274,0.0049509,0.000981,0.0025067,-0.0049167,-0.002763,0.0029712,-0.0016515,0.0006852,0.0003387
Roman:Italy_LA.SG,0.1062111,0.1500444,-0.010913,-0.0451796,0.0137717,-0.0169949,-0.0006756,-0.0048891,0.0021092,0.0228594,0.0018472,0.0044022,-0.0074144,-0.0006622,-0.0083976,-0.0015248,0.0036181,0.000863,0.0015869,-0.0025559,-0.0020044,0.0018471,-0.0003159,-0.0001279,-0.0009804
North_African:Mozabite,-0.0649782,0.135551,-0.0032793,-0.0717622,0.0260249,-0.0328364,-0.0260656,0.0108257,0.0617306,0.0303463,0.0065097,-0.006366,0.021795,-0.0165685,0.0163159,-0.016176,-0.0027097,-0.0219282,-0.0435571,0.0082757,-0.0146263,-0.0367947,0.0246817,-0.0042277,0.0056594

[HelloGuys]

U mean Conimbriga, Monte da Nora or Miroico samples?

Yep bro.

[kingmob]

Do you mean this?




Yeah, sure.

The test are the targets?

[HelloGuys]

7 is pushing it.

5 could be more realistic.

But, we won't know until we try.

I see, so bad Idk how to use it :lol: maybe one day I could learn, but it is nice to know that I can be modeled on that professional tool.

[HelloGuys]

Yeah, sure.

The test are the targets?

Yeah

[kingmob]

I see, so bad Idk how to use it :lol: maybe one day I could learn, but it is nice to know that I can be modeled on that professional tool.


I have a tutorial on this website, you can check it out, I'll see what I can do now with a couple of your targets.

https://www.theapricity.com/forum/showthread.php?363817-admixtools2-TUTORIAL-for-WINDOWS&highlight=admixtools2+tutorial

[HelloGuys]

I have a tutorial on this website, you can check it out, I'll see what I can do now with a couple of your targets.

https://www.theapricity.com/forum/showthread.php?363817-admixtools2-TUTORIAL-for-WINDOWS&highlight=admixtools2+tutorial

Ok! I will give it a look then! I hope to do the process well lol

About the targets, thanks!

[kingmob]

It may take some time as it's late, but I'll post them as soon as I have them ready. Keep an eye on the thread.

[HelloGuys]

Well, this thread is about comparations between G25 and qpAdm so I'll show some models that I have on hand:

Note: I used scaled samples for G25

G25:

Target: Iberia_Southeast_c.5-8CE
Distance: 2.2777% / 0.02277679
65.8 Iberia_Northeast_c.6-8CE_ES
23.6 Canary_Islands_Guanche
10.6 Jordan_EBA

Target: Iberia_Southeast_c.10-16CE
Distance: 1.5954% / 0.01595403
67.2 Iberia_Northeast_c.6-8CE_ES
20.2 Canary_Islands_Guanche
12.6 Jordan_EBA


qpAdm:

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



G25:

Target: Iberia_Northeast_c.8-12CE
Distance: 2.1564% / 0.02156441
93.6 Iberia_Northeast_c.6-8CE_ES
6.4 Morocco_LN.SG


qpAdm:
https://i.imgur.com/1yucIiQ.png

[HelloGuys]

It may take some time as it's late, but I'll post them as soon as I have them ready. Keep an eye on the thread.

No problem bro! Do not worry, I will :)

[HelloGuys]

Other one. Same targets and sources as in qpAdm:

-Spanish: Carolingian and Visigoth
-Amazigh: Guanche and MAR_TIZ/Ifrane (Souss-Massa)

Note 1: Since Idk how many samples or which ones were used for the modern spaniards in qpAdm, I made an average using all the provinces.

Note 2: I used scaled samples for G25.


G25:

Target: Spain_Medieval
Distance: 2.9850% / 0.02984972
89.4 Spanish
10.6 Amazigh

Target: Spain_Islamic
Distance: 2.8401% / 0.02840057
77.6 Spanish
22.4 Amazigh

Target: Spain_Islamic_Zira
Distance: 3.7529% / 0.03752911
66.8 Spanish
33.2 Amazigh

Target: Spain_Islamic_Almohade
Distance: 3.1507% / 0.03150685
60.8 Spanish
39.2 Amazigh

Target: Spain_NazariPeriod_LateMuslim
Distance: 3.9273% / 0.03927294
55.0 Amazigh
45.0 Spanish

Target: Spain_NazariPeriod_Muslim
Distance: 3.7830% / 0.03783029
65.0 Spanish
35.0 Amazigh

Target: Spanish
Distance: 2.5259% / 0.02525885
92.6 Spanish
7.4 Amazigh


qpAdm:

https://i.imgur.com/yBpSfUP.jpg


Just 3 out 7 G25 admixture models matched with qpAdm, the rest of them were off.

[Boudin]

<chr><chr><dbl><dbl><dbl><chr><dbl><dbl><dbl><dbl><dbl><dbl><dbl><lgl><lgl><dbl><dbl><dbl>The same model gives me 62.2% Copper Age Anatolian (4.47% s.e.) and 37.8% Corded Ware Culture (4.47% s.e.), percentages similar to g25 but the p-value is extremely low at 0.00473 meaning the model is a fail (p.value required above 5%).

<chr><chr><dbl><dbl><dbl><chr><dbl><dbl><dbl><dbl><dbl><dbl><dbl><lgl><lgl><dbl><dbl><dbl><chr><chr><dbl><dbl><dbl><chr><dbl><dbl><dbl><dbl><dbl><dbl><dbl><dbl><lgl><lgl><dbl>Is it possible, in theory, to get a meaningful p-value using only G25 coordinates? For example, by modifying the Vahaduo code? Also, what does the p-value and s.e. mean in practical terms? How are they relevant to someone seeking to model their ancestry?</dbl></lgl></lgl></dbl></dbl></dbl></dbl></dbl></dbl></dbl></dbl></chr></dbl></dbl></dbl></chr></chr></dbl></dbl></dbl></lgl></lgl></dbl></dbl></dbl></dbl></dbl></dbl></dbl></chr></dbl></dbl></dbl></chr></chr></dbl></dbl></dbl></lgl></lgl></dbl></dbl></dbl></dbl></dbl></dbl></dbl></chr></dbl></dbl></dbl></chr></chr>

[kingmob]

Do you mean this?



1.**pass**




> results$weights
# A tibble: 3 × 5
target left weight se z
<chr> <chr> <dbl> <dbl> <dbl>
1 Portugal_Conimbriga_Roman.SG Iberian_IA 0.726 0.103 7.05
2 Portugal_Conimbriga_Roman.SG Roman 0.217 0.131 1.66
3 Portugal_Conimbriga_Roman.SG North_African.DG 0.0563 0.0347 1.63
> results$popdrop
# A tibble: 7 × 14
pat wt dof chisq p f4rank Iberian_IA Roman North_African.DG feasible best dofdiff chisqd…¹ p_nes…²
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
1 000 0 8 13.6 9.19e- 2 2 0.726 0.217 0.0563 TRUE NA NA NA NA



2.**pass**




> results$weights
# A tibble: 3 × 5
target left weight se z
<chr> <chr> <dbl> <dbl> <dbl>
1 Portugal_Miroico_LateRoman_oAfrica.SG Iberian_IA 0.467 0.0916 5.10
2 Portugal_Miroico_LateRoman_oAfrica.SG Roman 0.206 0.114 1.81
3 Portugal_Miroico_LateRoman_oAfrica.SG North_African.DG 0.328 0.0302 10.8
> results$popdrop
# A tibble: 7 × 14
pat wt dof chisq p f4rank Iberian_IA Roman North_African.DG feasible best dofdiff chisqd…¹ p_nes…²
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
1 000 0 8 10.4 2.35e- 1 2 0.467 0.206 0.328 TRUE NA NA NA NA



3.**fail**




> results$weights
# A tibble: 3 × 5
target left weight se z
<chr> <chr> <dbl> <dbl> <dbl>
1 Portugal_Miroico_LateRoman.SG Iberian_IA 0.503 0.0709 7.09
2 Portugal_Miroico_LateRoman.SG Roman 0.397 0.0898 4.42
3 Portugal_Miroico_LateRoman.SG North_African.DG 0.0996 0.0236 4.23
> results$popdrop
# A tibble: 7 × 14
pat wt dof chisq p f4rank Iberian_IA Roman North_African.DG feasible best dofdiff chisqd…¹ p_nes…²
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
1 000 0 8 28.3 4.28e- 4 2 0.503 0.397 0.0996 TRUE NA NA NA NA



4.**pass (close call)**




> results$weights
# A tibble: 3 × 5
target left weight se z
<chr> <chr> <dbl> <dbl> <dbl>
1 Portugal_MonteDaNora_LateRoman.SG Iberian_IA 0.403 0.0690 5.84
2 Portugal_MonteDaNora_LateRoman.SG Roman 0.395 0.0843 4.69
3 Portugal_MonteDaNora_LateRoman.SG North_African.DG 0.202 0.0226 8.95
> results$popdrop
# A tibble: 7 × 14
pat wt dof chisq p f4rank Iberian_IA Roman North_African.DG feasible best dofdiff chisqd…¹ p_nes…²
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
1 000 0 8 15.7 4.67e- 2 2 0.403 0.395 0.202 TRUE NA NA NA NA

[kingmob]

<chr><chr><dbl><dbl><dbl><chr><dbl><dbl><dbl><dbl><dbl><dbl><dbl><lgl><lgl><dbl><dbl><dbl><chr><chr><dbl><dbl><dbl><chr><dbl><dbl><dbl><dbl><dbl><dbl><dbl><dbl><lgl><lgl><dbl>Is it possible, in theory, to get a meaningful p-value using only G25 coordinates? For example, by modifying the Vahaduo code? Also, what does the p-value and s.e. mean in practical terms? How are they relevant to someone seeking to model their ancestry?</dbl></lgl></lgl></dbl></dbl></dbl></dbl></dbl></dbl></dbl></dbl></chr></dbl></dbl></dbl></chr></chr></dbl></dbl></dbl></lgl></lgl></dbl></dbl></dbl></dbl></dbl></dbl></dbl></chr></dbl></dbl></dbl></chr></chr></dbl></dbl></dbl></lgl></lgl></dbl></dbl></dbl></dbl></dbl></dbl></dbl></chr></dbl></dbl></dbl></chr></chr>


1. No.
2. p-value shows the viability of the model (Reich models require 0.05 and above). The standard error shows the deviations in the weight. The smaller the s.e. the more accurate the results (Reich models aim for 5% and below), in some cases high standard errors are inevitable.

[kingmob]

Is it possible, in theory, to get a meaningful p-value using only G25 coordinates?

Just a clarification, in theory, g25 could hit the jackpot with a model, but you won't know until you test with fstats.

It's not an automatic fail axiomatically.

[Eurafricanid]

Other one. Same targets and sources as in qpAdm:

-Spanish: Carolingian and Visigoth
-Amazigh: Guanche and MAR_TIZ/Ifrane (Souss-Massa)

Note 1: Since Idk how many samples or which ones were used for the modern spaniards in qpAdm, I made an average using all the provinces.

Note 2: I used scaled samples for G25.


G25:

Target: Spain_Medieval
Distance: 2.9850% / 0.02984972
89.4 Spanish
10.6 Amazigh

Target: Spain_Islamic
Distance: 2.8401% / 0.02840057
77.6 Spanish
22.4 Amazigh

Target: Spain_Islamic_Zira
Distance: 3.7529% / 0.03752911
66.8 Spanish
33.2 Amazigh

Target: Spain_Islamic_Almohade
Distance: 3.1507% / 0.03150685
60.8 Spanish
39.2 Amazigh

Target: Spain_NazariPeriod_LateMuslim
Distance: 3.9273% / 0.03927294
55.0 Amazigh
45.0 Spanish

Target: Spain_NazariPeriod_Muslim
Distance: 3.7830% / 0.03783029
65.0 Spanish
35.0 Amazigh

Target: Spanish
Distance: 2.5259% / 0.02525885
92.6 Spanish
7.4 Amazigh


qpAdm:

https://i.imgur.com/yBpSfUP.jpg


Just 3 out 7 G25 admixture models matched with qpAdm, the rest of them were off.

I did the same thing and the results were a bit different (Green is match, yellow is parcial match, red is not a match):

Target: Spain_Medieval (0.4% off)
Distance: 3.0218% / 0.03021759
90.0 Spanish
10.0 Amazigh

Target: Spain_Islamic (0.5% off)
Distance: 2.9308% / 0.02930775
78.4 Spanish
21.6 Amazigh

Target: Spain_Islamic_Zira (~10% off)
Distance: 3.8128% / 0.03812817
67.8 Spanish
32.2 Amazigh

Target: Spain_Islamic_Almohade (~10% off)
Distance: 3.2127% / 0.03212695
62.0 Spanish
38.0 Amazigh

Target: Spain_NazariPeriod_LateMuslim (~20% off)
Distance: 4.0167% / 0.04016679
51.4 Amazigh
48.6 Spanish

Target: Spain_NazariPeriod_Muslim (~7% off)
Distance: 3.8508% / 0.03850788
66.2 Spanish
33.8 Amazigh

Target: Spanish (1.1% off)
Distance: 2.3849% / 0.02384907
93.4 Spanish
6.6 Amazigh


Yes, some are not so close, but only one is very different, I would say that 4 out of 7 were good, 2 were ok and 1 was bad, but it whould be amaxing to know what study did you take this information from.

[Jingle Bell]

1.**pass**




> results$weights
# A tibble: 3 × 5
target left weight se z
<chr> <chr> <dbl> <dbl> <dbl>
1 Portugal_Conimbriga_Roman.SG Iberian_IA 0.726 0.103 7.05
2 Portugal_Conimbriga_Roman.SG Roman 0.217 0.131 1.66
3 Portugal_Conimbriga_Roman.SG North_African.DG 0.0563 0.0347 1.63
> results$popdrop
# A tibble: 7 × 14
pat wt dof chisq p f4rank Iberian_IA Roman North_African.DG feasible best dofdiff chisqd…¹ p_nes…²
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
1 000 0 8 13.6 9.19e- 2 2 0.726 0.217 0.0563 TRUE NA NA NA NA



2.**pass**




> results$weights
# A tibble: 3 × 5
target left weight se z
<chr> <chr> <dbl> <dbl> <dbl>
1 Portugal_Miroico_LateRoman_oAfrica.SG Iberian_IA 0.467 0.0916 5.10
2 Portugal_Miroico_LateRoman_oAfrica.SG Roman 0.206 0.114 1.81
3 Portugal_Miroico_LateRoman_oAfrica.SG North_African.DG 0.328 0.0302 10.8
> results$popdrop
# A tibble: 7 × 14
pat wt dof chisq p f4rank Iberian_IA Roman North_African.DG feasible best dofdiff chisqd…¹ p_nes…²
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
1 000 0 8 10.4 2.35e- 1 2 0.467 0.206 0.328 TRUE NA NA NA NA



3.**fail**




> results$weights
# A tibble: 3 × 5
target left weight se z
<chr> <chr> <dbl> <dbl> <dbl>
1 Portugal_Miroico_LateRoman.SG Iberian_IA 0.503 0.0709 7.09
2 Portugal_Miroico_LateRoman.SG Roman 0.397 0.0898 4.42
3 Portugal_Miroico_LateRoman.SG North_African.DG 0.0996 0.0236 4.23
> results$popdrop
# A tibble: 7 × 14
pat wt dof chisq p f4rank Iberian_IA Roman North_African.DG feasible best dofdiff chisqd…¹ p_nes…²
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
1 000 0 8 28.3 4.28e- 4 2 0.503 0.397 0.0996 TRUE NA NA NA NA



4.**pass (close call)**




> results$weights
# A tibble: 3 × 5
target left weight se z
<chr> <chr> <dbl> <dbl> <dbl>
1 Portugal_MonteDaNora_LateRoman.SG Iberian_IA 0.403 0.0690 5.84
2 Portugal_MonteDaNora_LateRoman.SG Roman 0.395 0.0843 4.69
3 Portugal_MonteDaNora_LateRoman.SG North_African.DG 0.202 0.0226 8.95
> results$popdrop
# A tibble: 7 × 14
pat wt dof chisq p f4rank Iberian_IA Roman North_African.DG feasible best dofdiff chisqd…¹ p_nes…²
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
1 000 0 8 15.7 4.67e- 2 2 0.403 0.395 0.202 TRUE NA NA NA NA



Hm very interesting, MonteDaNora begin Celtiberian as it is Roman its very interesting
in g25 looking like this:

https://i.imgur.com/1vALoP6.png

[HelloGuys]

Hm very interesting, MonteDaNora begin Celtiberian as it is Roman its very interesting
in g25 looking like this:

https://i.imgur.com/1vALoP6.png

Miroico late roman don't have North African, that's the reason it failed in qpAdm; so using other component would be its right source.

What samples did you use btw?

[HelloGuys]

1.**pass**




> results$weights
# A tibble: 3 × 5
target left weight se z
<chr> <chr> <dbl> <dbl> <dbl>
1 Portugal_Conimbriga_Roman.SG Iberian_IA 0.726 0.103 7.05
2 Portugal_Conimbriga_Roman.SG Roman 0.217 0.131 1.66
3 Portugal_Conimbriga_Roman.SG North_African.DG 0.0563 0.0347 1.63
> results$popdrop
# A tibble: 7 × 14
pat wt dof chisq p f4rank Iberian_IA Roman North_African.DG feasible best dofdiff chisqd…¹ p_nes…²
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
1 000 0 8 13.6 9.19e- 2 2 0.726 0.217 0.0563 TRUE NA NA NA NA



2.**pass**




> results$weights
# A tibble: 3 × 5
target left weight se z
<chr> <chr> <dbl> <dbl> <dbl>
1 Portugal_Miroico_LateRoman_oAfrica.SG Iberian_IA 0.467 0.0916 5.10
2 Portugal_Miroico_LateRoman_oAfrica.SG Roman 0.206 0.114 1.81
3 Portugal_Miroico_LateRoman_oAfrica.SG North_African.DG 0.328 0.0302 10.8
> results$popdrop
# A tibble: 7 × 14
pat wt dof chisq p f4rank Iberian_IA Roman North_African.DG feasible best dofdiff chisqd…¹ p_nes…²
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
1 000 0 8 10.4 2.35e- 1 2 0.467 0.206 0.328 TRUE NA NA NA NA



3.**fail**




> results$weights
# A tibble: 3 × 5
target left weight se z
<chr> <chr> <dbl> <dbl> <dbl>
1 Portugal_Miroico_LateRoman.SG Iberian_IA 0.503 0.0709 7.09
2 Portugal_Miroico_LateRoman.SG Roman 0.397 0.0898 4.42
3 Portugal_Miroico_LateRoman.SG North_African.DG 0.0996 0.0236 4.23
> results$popdrop
# A tibble: 7 × 14
pat wt dof chisq p f4rank Iberian_IA Roman North_African.DG feasible best dofdiff chisqd…¹ p_nes…²
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
1 000 0 8 28.3 4.28e- 4 2 0.503 0.397 0.0996 TRUE NA NA NA NA



4.**pass (close call)**




> results$weights
# A tibble: 3 × 5
target left weight se z
<chr> <chr> <dbl> <dbl> <dbl>
1 Portugal_MonteDaNora_LateRoman.SG Iberian_IA 0.403 0.0690 5.84
2 Portugal_MonteDaNora_LateRoman.SG Roman 0.395 0.0843 4.69
3 Portugal_MonteDaNora_LateRoman.SG North_African.DG 0.202 0.0226 8.95
> results$popdrop
# A tibble: 7 × 14
pat wt dof chisq p f4rank Iberian_IA Roman North_African.DG feasible best dofdiff chisqd…¹ p_nes…²
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
1 000 0 8 15.7 4.67e- 2 2 0.403 0.395 0.202 TRUE NA NA NA NA



Thanks bro! It's interesting that Miroico Late Roman failed, so maybe using Greek? (As for the NE_Iberia_c.6-8CE_ES in 2019 study).

Target: Portugal_Conimbriga_Roman.SG
Distance: 2.0861% / 0.02086144
88.0 Iberian_IA
8.0 Roman
4.0 North_African

Target: Portugal_Miroico_LateRoman_oAfrica.SG
Distance: 2.3469% / 0.02346904
47.6 Iberian_IA
29.8 North_African
22.6 Roman

Target: Portugal_Miroico_LateRoman.SG
Distance: 1.5184% / 0.01518409
67.0 Iberian_IA
19.6 Roman
13.4 North_African

Target: Portugal_MonteDaNora_LateRoman.SG
Distance: 1.3043% / 0.01304294
45.8 Iberian_IA
34.2 Roman
20.0 North_African

[kingmob]

Thanks bro! It's interesting that Miroico Late Roman failed, so maybe using Greek? (As for the NE_Iberia_c.6-8CE_ES in 2019 study).




You can see g25 has trouble telling populations apart if they are relatively similar due to the lack of a right ancestral list that helps differentiate properly between them.

[Jingle Bell]

Miroico late roman don't have North African, that's the reason it failed in qpAdm; so using other component would be it's right source.

What samples did you use btw?

The samples that u left in the thread, i just made a g25 model with them

[HelloGuys]

The samples that u left in the thread, i just made a g25 model with them

Yeah, I saw and compared the results, I wasn't paying too much attention lol

Have you tried to model yourself with those references? :)

[HelloGuys]

You can see g25 has trouble telling populations apart if they are relatively similar due to the lack of a right ancestral list that helps differentiate properly between them.

Do you mean an outgroup panel like in qpAdm?

[HelloGuys]

I did the same thing and the results were a bit different (Green is match, yellow is parcial match, red is not a match):

Target: Spain_Medieval (0.4% off)
Distance: 3.0218% / 0.03021759
90.0 Spanish
10.0 Amazigh

Target: Spain_Islamic (0.5% off)
Distance: 2.9308% / 0.02930775
78.4 Spanish
21.6 Amazigh

Target: Spain_Islamic_Zira (~10% off)
Distance: 3.8128% / 0.03812817
67.8 Spanish
32.2 Amazigh

Target: Spain_Islamic_Almohade (~10% off)
Distance: 3.2127% / 0.03212695
62.0 Spanish
38.0 Amazigh

Target: Spain_NazariPeriod_LateMuslim (~20% off)
Distance: 4.0167% / 0.04016679
51.4 Amazigh
48.6 Spanish

Target: Spain_NazariPeriod_Muslim (~7% off)
Distance: 3.8508% / 0.03850788
66.2 Spanish
33.8 Amazigh

Target: Spanish (1.1% off)
Distance: 2.3849% / 0.02384907
93.4 Spanish
6.6 Amazigh


Yes, some are not so close, but only one is very different, I would say that 4 out of 7 were good, 2 were ok and 1 was bad, but it whould be amaxing to know what study did you take this information from.

Ah! I used a new average of Canary Islands reference with 30 individuals, that's the reason there were a difference between our results.

The qpAdm model, sincerely Idk what study is; if I remember well, I found it because someone in Anthrogenica posted the image (Before its closure).

[Jingle Bell]

I see, so bad Idk how to use it :lol: maybe one day I could learn, but it is nice to know that I can be modeled on that professional tool.


Yeah, I saw and compared the results, I wasn't paying too much attention lol

Have you tried to model yourself with those references? :)


Dad:

Target: Dad_SimulatedK36
Distance: 1.3010% / 0.01301007
35.8 SSA
30.2 Iberian_IA
21.0 Roman
7.2 North_African
5.8 NAM

Mine simulated K36:

Target: result_K36
Distance: 1.1470% / 0.01146991
44.4 SSA
26.6 Iberian_IA
17.6 Roman
9.4 North_African
2.0 NAM

Mine g25:

Target: JingleBell_scaled
Distance: 2.0194% / 0.02019405
45.2 SSA
30.0 Iberian_IA
15.8 Roman
6.2 North_African
2.8 NAM

Damn, almost 16% Roman begin just 1/2 Portuguese? Ave Ceasare!
Overall looking very nice, some of NA can be from my Fula/North Nigerian Ancestry, and extra Roman a indicative of Serfadi ancestry, but who know, maybe im just a Roman-Punic remanescent in america XD

[Eurafricanid]

Ah! I used a new average of Canary Islands reference with 30 individuals, that's the reason there were a difference between our results.

The qpAdm model, sincerely Idk what study is; if I remember well, I found it because someone in Anthrogenica posted the image (Before its closure).

It needs to be the exact same as the ones done in the study, if it's not like that it doesn't work as a comparison.

[Eurafricanid]

Dad:

Target: Dad_SimulatedK36
Distance: 1.3010% / 0.01301007
35.8 SSA
30.2 Iberian_IA
21.0 Roman
7.2 North_African
5.8 NAM

Mine simulated K36:

Target: result_K36
Distance: 1.1470% / 0.01146991
44.4 SSA
26.6 Iberian_IA
17.6 Roman
9.4 North_African
2.0 NAM

Mine g25:

Target: JingleBell_scaled
Distance: 2.0194% / 0.02019405
45.2 SSA
30.0 Iberian_IA
15.8 Roman
6.2 North_African
2.8 NAM

Damn, almost 16% Roman begin just 1/2 Portuguese? Ave Ceasare!
Overall looking very nice, some of NA can be from my Fula/North Nigerian Ancestry, and extra Roman a indicative of Serfadi ancestry, but who know, maybe im just a Roman-Punic remanescent in america XD

Using your same model :thumb001:

Target: Eurafricanid_scaled
Distance: 0.9608% / 0.00960802
47.2 SSA
30.2 Iberian_IA
20.0 Roman
2.6 SAM

[HelloGuys]

It needs to be the exact same as the ones done in the study, if it's not like that it doesn't work as a comparison.

Sadly in the study we do not know how many Guanches were in the average.

[HelloGuys]

Dad:

Target: Dad_SimulatedK36
Distance: 1.3010% / 0.01301007
35.8 SSA
30.2 Iberian_IA
21.0 Roman
7.2 North_African
5.8 NAM

Mine simulated K36:

Target: result_K36
Distance: 1.1470% / 0.01146991
44.4 SSA
26.6 Iberian_IA
17.6 Roman
9.4 North_African
2.0 NAM

Mine g25:

Target: JingleBell_scaled
Distance: 2.0194% / 0.02019405
45.2 SSA
30.0 Iberian_IA
15.8 Roman
6.2 North_African
2.8 NAM

Damn, almost 16% Roman begin just 1/2 Portuguese? Ave Ceasare!
Overall looking very nice, some of NA can be from my Fula/North Nigerian Ancestry, and extra Roman a indicative of Serfadi ancestry, but who know, maybe im just a Roman-Punic remanescent in america XD

Yeah, the model is interesting, it was made by A Flores-Bello · 2021 study (Genetic origins, singularity, and heterogeneity of Basques).

Target: HelloGuys_scaled
Distance: 3.0487% / 0.03048737
37.4 Indigenous_American
34.4 Iberian_IA
19.8 Roman
4.8 North_African
3.6 West_African

I am 4% more Roman :p but 1.4% less North African.

I used Western Mande peoples for my West African reference (Mende_Sierra Leone, Bambara_Mali and Mandinka_Gambia) and just one for my Indigenous American side (USA_Nevada_LovelockCave_1850BP: Uto-Aztecs before the arrival of Nahuas to Mexico, but the reference is used like a proxy because it's not the right source of nahua's ancestors).

[Eurafricanid]

Yeah, the model is interesting, it was made by I Olalde · 2019 study (The genomic history of the Iberian Peninsula over the past 8000 years).

Target: HelloGuys_scaled
Distance: 3.0487% / 0.03048737
37.4 Indigenous_American
34.4 Iberian_IA
19.8 Roman
4.8 North_African
3.6 West_African

I am 4% more Roman :p but 1.4% less North African.

I used Western Mande peoples for my West African reference (Mende_Sierra Leone, Bambara_Mali and Mandinka_Gambia) and just one for my Indigenous American side (USA_Nevada_LovelockCave_1850BP, used like a proxy of a Uto-Aztec before the arrival of Nahuas to Mexico).

IK I don't score it and Mozabite is fine, but Berber_MAR_TIZ is much better than Mozabite, IMO:

Target: Berber_MAR_TIZ
Distance: 2.0043% / 0.02004303
41.6 Morocco_Iberomaurusian
38.2 ANF
12.0 Sub_Saharan_African
3.6 Yamnaya
2.2 Israel_PPNB
1.8 Israel_Natufian
0.6 WHG

Target: Mozabite
Distance: 2.2299% / 0.02229853
39.6 ANF
33.0 Morocco_Iberomaurusian
10.0 Sub_Saharan_African
6.0 Yamnaya
5.8 Iran_C
4.8 Israel_Natufian
0.8 WHG

[HelloGuys]

IK I don't score it and Mozabite is fine, but Berber_MAR_TIZ is much better than Mozabite, IMO:

Target: Berber_MAR_TIZ
Distance: 2.0043% / 0.02004303
41.6 Morocco_Iberomaurusian
38.2 ANF
12.0 Sub_Saharan_African
3.6 Yamnaya
2.2 Israel_PPNB
1.8 Israel_Natufian
0.6 WHG

Target: Mozabite
Distance: 2.2299% / 0.02229853
39.6 ANF
33.0 Morocco_Iberomaurusian
10.0 Sub_Saharan_African
6.0 Yamnaya
5.8 Iran_C
4.8 Israel_Natufian
0.8 WHG

It would be interesting what would happen in qpAdm using that berber reference.

Btw what a fail lol the model was made by A Flores-Bello · 2021 study (Genetic origins, singularity, and heterogeneity of Basques) not by Olalde.

[Eurafricanid]

Other one. Same targets and sources as in qpAdm:

-Spanish: Carolingian and Visigoth
-Amazigh: Guanche and MAR_TIZ/Ifrane (Souss-Massa)

Note 1: Since Idk how many samples or which ones were used for the modern spaniards in qpAdm, I made an average using all the provinces.

Note 2: I used scaled samples for G25.


G25:

Target: Spain_Medieval
Distance: 2.9850% / 0.02984972
89.4 Spanish
10.6 Amazigh

Target: Spain_Islamic
Distance: 2.8401% / 0.02840057
77.6 Spanish
22.4 Amazigh

Target: Spain_Islamic_Zira
Distance: 3.7529% / 0.03752911
66.8 Spanish
33.2 Amazigh

Target: Spain_Islamic_Almohade
Distance: 3.1507% / 0.03150685
60.8 Spanish
39.2 Amazigh

Target: Spain_NazariPeriod_LateMuslim
Distance: 3.9273% / 0.03927294
55.0 Amazigh
45.0 Spanish

Target: Spain_NazariPeriod_Muslim
Distance: 3.7830% / 0.03783029
65.0 Spanish
35.0 Amazigh

Target: Spanish
Distance: 2.5259% / 0.02525885
92.6 Spanish
7.4 Amazigh


qpAdm:

https://i.imgur.com/yBpSfUP.jpg


Just 3 out 7 G25 admixture models matched with qpAdm, the rest of them were off.

BTW, Ifrane is not Souss-Massa, TIZ is, but Ifrane isn't.

https://i.imgur.com/kR7GMQq.png https://i.imgur.com/ggyGIgg.pnghttps://i.imgur.com/UgjzTQZ.png

[Jingle Bell]

1.**pass**




> results$weights
# A tibble: 3 × 5
target left weight se z
<chr> <chr> <dbl> <dbl> <dbl>
1 Portugal_Conimbriga_Roman.SG Iberian_IA 0.726 0.103 7.05
2 Portugal_Conimbriga_Roman.SG Roman 0.217 0.131 1.66
3 Portugal_Conimbriga_Roman.SG North_African.DG 0.0563 0.0347 1.63
> results$popdrop
# A tibble: 7 × 14
pat wt dof chisq p f4rank Iberian_IA Roman North_African.DG feasible best dofdiff chisqd…¹ p_nes…²
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
1 000 0 8 13.6 9.19e- 2 2 0.726 0.217 0.0563 TRUE NA NA NA NA



2.**pass**




> results$weights
# A tibble: 3 × 5
target left weight se z
<chr> <chr> <dbl> <dbl> <dbl>
1 Portugal_Miroico_LateRoman_oAfrica.SG Iberian_IA 0.467 0.0916 5.10
2 Portugal_Miroico_LateRoman_oAfrica.SG Roman 0.206 0.114 1.81
3 Portugal_Miroico_LateRoman_oAfrica.SG North_African.DG 0.328 0.0302 10.8
> results$popdrop
# A tibble: 7 × 14
pat wt dof chisq p f4rank Iberian_IA Roman North_African.DG feasible best dofdiff chisqd…¹ p_nes…²
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
1 000 0 8 10.4 2.35e- 1 2 0.467 0.206 0.328 TRUE NA NA NA NA



3.**fail**




> results$weights
# A tibble: 3 × 5
target left weight se z
<chr> <chr> <dbl> <dbl> <dbl>
1 Portugal_Miroico_LateRoman.SG Iberian_IA 0.503 0.0709 7.09
2 Portugal_Miroico_LateRoman.SG Roman 0.397 0.0898 4.42
3 Portugal_Miroico_LateRoman.SG North_African.DG 0.0996 0.0236 4.23
> results$popdrop
# A tibble: 7 × 14
pat wt dof chisq p f4rank Iberian_IA Roman North_African.DG feasible best dofdiff chisqd…¹ p_nes…²
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
1 000 0 8 28.3 4.28e- 4 2 0.503 0.397 0.0996 TRUE NA NA NA NA



4.**pass (close call)**




> results$weights
# A tibble: 3 × 5
target left weight se z
<chr> <chr> <dbl> <dbl> <dbl>
1 Portugal_MonteDaNora_LateRoman.SG Iberian_IA 0.403 0.0690 5.84
2 Portugal_MonteDaNora_LateRoman.SG Roman 0.395 0.0843 4.69
3 Portugal_MonteDaNora_LateRoman.SG North_African.DG 0.202 0.0226 8.95
> results$popdrop
# A tibble: 7 × 14
pat wt dof chisq p f4rank Iberian_IA Roman North_African.DG feasible best dofdiff chisqd…¹ p_nes…²
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
1 000 0 8 15.7 4.67e- 2 2 0.403 0.395 0.202 TRUE NA NA NA NA



Hi eupator, sry for asking and i understand of u dont want to but can u try model modern Portuguese with Hispano_Roman: Miroico/Conimbriga/MonteDaNora + Germanic:Visigoth_Iberia + German_Alemmanic (The closest we have from Suebi Confederaction)

Source:

Hispano_Roman:Portugal_Miroico_LateRoman_oAfrica.S G,0.068863,0.14319,0.021496,-0.0334305,0.0326215,-0.016873,-0.015628,-0.0027695,0.044177,0.0342605,0.0005685,-0.0005245,0.0045345,-0.015276,0.0085505,0.0002655,-0.0007825,-0.0051305,-0.0106845,0.004127,0.007237,-0.012736,0.00228,-0.010483,0.0035925
Hispano_Roman:Portugal_Miroico_LateRoman.SG,0.0984 572,0.1428512,0.0355123,-0.0088825,0.0444697,-0.0058567,-0.0054052,0.0023075,0.0305082,0.0322557,-0.0036808,0.007968,-0.0091178,-0.0163312,0.0095458,0.0004642,0.0001957,-0.0019423,-0.0102235,0.0005212,0.0028285,-0.0021637,0.0010473,-0.0044583,0.0009182
Hispano_Roman:Portugal_MonteDaNora_LateRoman.SG,0. 0830907,0.1445437,0.0235073,-0.0230407,0.0336473,-0.0090173,-0.010262,-0.0005383,0.0289743,0.02934,-0.002057,0.0016487,-0.004757,-0.0084407,0.009817,-0.002961,-0.0033467,-0.0059543,-0.0080027,0.001334,-0.001872,-0.0056057,0.0041903,-0.0041773,-0.00012
Germanic_Settler:Spain_Visigoth,0.1272542,0.135877 8,0.0463104,0.02261,0.0377302,0.0069724,0.00658,0. 0029076,0.0075264,0.0115536,-0.0050666,0.008782,-0.0121604,-0.0059452,0.0059446,0.0051178,0.0050328,0.0032434,-0.0004274,0.0055778,0.0060892,0.0015828,-0.002539,0.0017352,-0.0021316
Germanic_Settler:Germany_EMedieval_Alemanic,0.1274 815,0.1310035,0.067693,0.054587,0.034314,0.0174305 ,0.0096355,0.0092305,0.002659,0.0010935,-0.005846,0.007943,-0.0102575,-0.013005,0.0164225,0.01127,0.001369,0.0011405,0.00 1697,0.002939,0.0069255,0.0062445,-0.000863,0.0165085,0.0016165


Target:
Portugal:Portuguese,0.10484364,0.14515298,0.036857 289,-0.0031295111,0.0419496,-0.0034086667,-0.0036973778,0.0029844444,0.025642711,0.028979556,-0.0020280444,0.0060413556,-0.011806978,-0.011477778,0.011478911,-0.0013052667,-0.0033059111,-0.00090655556,-0.0050363333,-0.0012617111,0.0014779333,-0.0025911778,0.0014077556,-0.0017993556,-0.00062268889
Spain:Spanish_Galicia_(Galician),0.10876428,0.1464 6189,0.041064167,-0.0016508889,0.041204278,-9.2944444E-05,-0.0054572222,0.0024230556,0.024713333,0.0300285,-0.0021291111,0.0057365,-0.012611333,-0.012156667,0.011144111,0.00058927778,-0.0042375,-0.0021606667,-0.0050417778,-0.0010075556,0.00087344444,-0.002899,-0.00080794444,-0.0036818333,0.0013037778
Spain:Spanish_Extremadura_(Extremaduran),0.1050966 7,0.14995967,0.033061,-0.0011843333,0.040930333,-0.0027886667,-0.003995,-0.0010003333,0.024679,0.031223,-0.0012993333,0.0050453333,-0.010604667,-0.012248,0.007555,0.0026076667,-0.002347,-0.003294,-0.0064106667,0.000417,0.0021213333,-0.00474,-0.0014786667,-0.0027713333,0.0014373333

[Russki]

g25 tends to exaggerate Eastern Euro


The exact methodology is written out here.

https://www.theapricity.com/forum/showthread.php?375412-Decoding-values-of-G25-coordinates

[Laredo]

Dad:

Target: Dad_SimulatedK36
Distance: 1.3010% / 0.01301007
35.8 SSA
30.2 Iberian_IA
21.0 Roman
7.2 North_African
5.8 NAM

Mine simulated K36:

Target: result_K36
Distance: 1.1470% / 0.01146991
44.4 SSA
26.6 Iberian_IA
17.6 Roman
9.4 North_African
2.0 NAM

Mine g25:

Target: JingleBell_scaled
Distance: 2.0194% / 0.02019405
45.2 SSA
30.0 Iberian_IA
15.8 Roman
6.2 North_African
2.8 NAM

Damn, almost 16% Roman begin just 1/2 Portuguese? Ave Ceasare!
Overall looking very nice, some of NA can be from my Fula/North Nigerian Ancestry, and extra Roman a indicative of Serfadi ancestry, but who know, maybe im just a Roman-Punic remanescent in america XD

Mine bro


https://gcdnb.pbrd.co/images/EGs4J9hanIkw.jpg?o=1

https://pasteboard.co/4EI6cDraOye0.jpg

https://gcdnb.pbrd.co/images/4EI6cDraOye0.jpg?o=1

[HelloGuys]

Mine bro


https://gcdnb.pbrd.co/images/EGs4J9hanIkw.jpg?o=1

https://pasteboard.co/4EI6cDraOye0.jpg

https://gcdnb.pbrd.co/images/4EI6cDraOye0.jpg?o=1

When you have average references use them in an admixture model with averages.

Besides, wrong choice of Native American and SSA references, your parents are more or less from the same zone as me, so you have 2 options of Amerindians:

1.USA_Nevada_,LovelockCave_1850BP
2.Nahua

The SSA would have to be 3 options too:

1.Gambia
2.Mandinka_Gambia
3.Western Mandé people (Ménde+Mandinka+Bambara) -Not very recommend as the first 2 SSA options-

Amerindians and SSA averages in a admixture model made with averages.

No one in Mexico has only Bantu SW ancestry, we're overwhelmingly Senegambian due the slave trade to the Nueva España (Even your AncestryDNA results prove it) so in consequence our diaspora too.

[HelloGuys]

BTW, Ifrane is not Souss-Massa, TIZ is, but Ifrane isn't.

https://i.imgur.com/kR7GMQq.png https://i.imgur.com/ggyGIgg.pnghttps://i.imgur.com/UgjzTQZ.png

Thanks bro, I'll check it then.

[HelloGuys]

Dad:

Target: Dad_SimulatedK36
Distance: 1.3010% / 0.01301007
35.8 SSA
30.2 Iberian_IA
21.0 Roman
7.2 North_African
5.8 NAM

Mine simulated K36:

Target: result_K36
Distance: 1.1470% / 0.01146991
44.4 SSA
26.6 Iberian_IA
17.6 Roman
9.4 North_African
2.0 NAM

Mine g25:

Target: JingleBell_scaled
Distance: 2.0194% / 0.02019405
45.2 SSA
30.0 Iberian_IA
15.8 Roman
6.2 North_African
2.8 NAM

Damn, almost 16% Roman begin just 1/2 Portuguese? Ave Ceasare!
Overall looking very nice, some of NA can be from my Fula/North Nigerian Ancestry, and extra Roman a indicative of Serfadi ancestry, but who know, maybe im just a Roman-Punic remanescent in america XD


Using your same model :thumb001:

Target: Eurafricanid_scaled
Distance: 0.9608% / 0.00960802
47.2 SSA
30.2 Iberian_IA
20.0 Roman
2.6 SAM

Good news bros: I had to read, choose and search for 6 hours; but finally I found all the samples in that study (Flores-Bello 2021).

The admixture model I posted was incomplete so when I have a chance, I'll open a thread with the full and right admixture model.

[Jingle Bell]

When you have average references use them in an admixture model with averages.

Besides, wrong choice of Native American and SSA references, your parents are more or less from the same zone as me, so you have 2 options of Amerindians:

1.USA_Nevada_,LovelockCave_1850BP
2.Nahua

The SSA would have to be 3 options too:

1.Gambia
2.Mandinka_Gambia
3.Western Mandé people (Ménde+Mandinka+Bambara) -Not very recommend as the first 2 SSA options-

Amerindians and SSA averages in a admixture model made with averages.

No one in Mexico has only Bantu SW ancestry, we're overwhelmingly Senegambian due the slave trade to the Nueva España (Even your AncestryDNA results prove it) so in consequence our diaspora too.

Laredo use that ones:

USA_Nevada_LovelockCave_1850BP.SG,0.0523583,-0.3209073,0.1184157,0.086564,-0.1167397,-0.0138513,-0.266032,-0.3173713,-0.0130213,-0.0201067,-0.0009743,-0.001898,0.0019823,0.015276,-0.0081433,-0.0019003,0.011126,-0.0003803,0.0045673,-0.000417,0.0008733,-0.0020197,0.0001643,0.0008833,0.0036723
USA_Nevada_LovelockCave_600BP.SG,0.05122,-0.327,0.121433,0.093347,-0.113867,-0.018128,-0.270027,-0.328371,-0.010226,-0.021504,-0.000162,-0.001199,0.005352,0.020093,-0.008279,0.007425,0.001956,-0.002407,0.001508,0.004127,-0.00574,0.004946,0.001972,-0.001566,0.006107
Gambia,-0.6165875,0.0671942,0.0197362,0.0114665,0.0021028, 0.0055777,-0.0358392,0.0387677,-0.0317353,0.0241463,0.0054132,-0.0036467,0.0162287,-0.0009865,0.011016,-0.0153362,0.009692,-0.0011823,-0.002116,-0.0032307,-0.001643,-0.0018137,0.0043958,-0.0001005,0.001377

[Laredo]

When you have average references use them in an admixture model with averages.

Besides, wrong choice of Native American and SSA references, your parents are more or less from the same zone as me, so you have 2 options of Amerindians:

1.USA_Nevada_,LovelockCave_1850BP
2.Nahua

The SSA would have to be 3 options too:

1.Gambia
2.Mandinka_Gambia
3.Western Mandé people (Ménde+Mandinka+Bambara) -Not very recommend as the first 2 SSA options-

Amerindians and SSA averages in a admixture model made with averages.

No one in Mexico has only Bantu SW ancestry, we're overwhelmingly Senegambian due the slave trade to the Nueva España (Even your AncestryDNA results prove it) so in consequence our diaspora too.

Will work on that, still learning how to use this things.

[Jingle Bell]

Mine bro


https://gcdnb.pbrd.co/images/EGs4J9hanIkw.jpg?o=1

https://pasteboard.co/4EI6cDraOye0.jpg

https://gcdnb.pbrd.co/images/4EI6cDraOye0.jpg?o=1

Nice, good amount of Roman and NA (A shift that is more comum in Latin-Americans than Iberians), in ur AncestryDNA thread u got 2% Jew, 1% Levant and 1% North Italian, prob indicative of Serfadi (3% - 5%), but despite ur South Mediterran shift u seens in a plausible variation anyway, can u share ur IllustrativeDNA results?

[Laredo]

Nice, good amount of Roman and NA (A shift that is more comum in Latin-Americans than Iberians), in ur AncestryDNA thread u got 2% Jew, 1% Levant and 1% North Italian, prob indicative of Serfadi (3% - 5%), but despite ur South Mediterran shift u seens in a plausible variation anyway, can u share ur IllustrativeDNA results?

Which ones Bro?

[Jingle Bell]

Which ones Bro?

Periodic Ancestry (Latin American) and mixed anciet mode

[Eurafricanid]

When you have average references use them in an admixture model with averages.

Besides, wrong choice of Native American and SSA references, your parents are more or less from the same zone as me, so you have 2 options of Amerindians:

1.USA_Nevada_,LovelockCave_1850BP
2.Nahua

The SSA would have to be 3 options too:

1.Gambia
2.Mandinka_Gambia
3.Western Mandé people (Ménde+Mandinka+Bambara) -Not very recommend as the first 2 SSA options-

Amerindians and SSA averages in a admixture model made with averages.

No one in Mexico has only Bantu SW ancestry, we're overwhelmingly Senegambian due the slave trade to the Nueva España (Even your AncestryDNA results prove it) so in consequence our diaspora too.

From what I've heard, the main source of slaves was Congo and Angola, which reflects on the Colonial sample from Campexe:


<tbody role="rowgroup" style="box-sizing: border-box;">
2.296
Nyaneka (Angola)


2.568
Umbundu (Angola)


2.926
Makhuwa (Mozambique)


2.932
Ganguela (Angola)


2.934
Herero (Namibia)


3.102
Ronga


3.346
Chewa (Malawi)


3.371
Tswa (Mozambique)


3.413
Sena (Mozambique)


3.423
Nyanja

</tbody>

[HelloGuys]

From what I've heard, the main source of slaves was Congo and Angola, which reflects on the Colonial sample from Campexe:


<tbody role="rowgroup" style="box-sizing: border-box;">
2.296
Nyaneka (Angola)


2.568
Umbundu (Angola)


2.926
Makhuwa (Mozambique)


2.932
Ganguela (Angola)


2.934
Herero (Namibia)


3.102
Ronga


3.346
Chewa (Malawi)


3.371
Tswa (Mozambique)


3.413
Sena (Mozambique)


3.423
Nyanja

</tbody>

The main source was Senegambian, and the second was Central Africans in México's case, I don't know what the other Latin American countries will be like.

[Eurafricanid]

The main source was Senegambian, and the second was Central Africans in México's case, I don't know what the other Latin American countries will be like.

I was talking about Mexico as the sample in from Mexico.

[Laredo]

Periodic Ancestry (Latin American) and mixed anciet mode

https://gcdnb.pbrd.co/images/RkYWOn5JlsR9.jpg?o=1

[Eurafricanid]

https://gcdnb.pbrd.co/images/RkYWOn5JlsR9.jpg?o=1

Could you click on the blue gear and unselect pict and roman britain and click on recalculate
https://i.imgur.com/DekadOo.png

[Laredo]

Could you click on the blue gear and unselect pict and roman britain and click on recalculate
https://i.imgur.com/DekadOo.png

Right now I'm at work that's why I'm taking long to reply , but will do it.

[HelloGuys]

I was talking about Mexico as the sample in from Mexico.

Yeah; I understood you bro, but it does not matter what she scores in G25, in the study (Using qpAdm for the 10 mexican samples) they concluded that the SSA mexican woman was of West African origin:

Burial 11–1
The two remaining individuals studied here have entirely non-Native ancestry. Previous bioanthropological assessment of Burial 11–1 suggested that this individual was a female of African ancestry who died at a young age, probably in her early twenties (similar to most first-generation African immigrants in the overall Campeche series; see Tiesler et al.2010). Her strontium isotope ratio was one of the highest measured in the cemetery, indicating that she was not born in the Yucatán peninsula (see below in our use of gendered pronouns for Burials 11–1 and 52–1). She also had stable carbon and nitrogen isotope values suggesting that C3 plants (such as rice) constituted most of her childhood diet, which is consistent with early life residence somewhere in West Africa (Priceet al. 2012). Her skeleton was found disarticulated and incomplete, indicating that she had been reburied. Her final resting place was 17m south-west of the main church entrance (Figure S2). This area was among the outer segments of the cemetery, and the burials here were closer to the ground surface than those nearer to the church. The outlying areas are likely to have harboured the latest interments of the cemetery, dating to the last decades of its use in the seventeenth century (Tiesler et al. 2010). Genome-wide and mitochondrial (L3 haplogroup) data for Burial 11–1 are consistent with an African origin (Figures 6 & 7 and Table S4). The high-resolution genetic analysis allows us to determine that Burial 11–1 had negligible European or Native American ancestry (OSM5). While additional statistical analysis did not reveal a specific geographical origin for Burial 11–1 (OSM5), we were able to determine that her ancestry was broadly West African.

© The Author(s), 2022. Published by Cambridge University Press on behalf of Antiquity Publications Ltd.

[Eurafricanid]

Yeah; I understood you bro, but it does not matter what she scores in G25, in the study (Using qpAdm for the 10 mexican samples) they concluded that the SSA mexican woman was of West African origin:

Burial 11–1
The two remaining individuals studied here have entirely non-Native ancestry. Previous bioanthropological assessment of Burial 11–1 suggested that this individual was a female of African ancestry who died at a young age, probably in her early twenties (similar to most first-generation African immigrants in the overall Campeche series; see Tiesler et al.2010). Her strontium isotope ratio was one of the highest measured in the cemetery, indicating that she was not born in the Yucatán peninsula (see below in our use of gendered pronouns for Burials 11–1 and 52–1). She also had stable carbon and nitrogen isotope values suggesting that C3 plants (such as rice) constituted most of her childhood diet, which is consistent with early life residence somewhere in West Africa (Priceet al. 2012). Her skeleton was found disarticulated and incomplete, indicating that she had been reburied. Her final resting place was 17m south-west of the main church entrance (Figure S2). This area was among the outer segments of the cemetery, and the burials here were closer to the ground surface than those nearer to the church. The outlying areas are likely to have harboured the latest interments of the cemetery, dating to the last decades of its use in the seventeenth century (Tiesler et al. 2010). Genome-wide and mitochondrial (L3 haplogroup) data for Burial 11–1 are consistent with an African origin (Figures 6 & 7 and Table S4). The high-resolution genetic analysis allows us to determine that Burial 11–1 had negligible European or Native American ancestry (OSM5). While additional statistical analysis did not reveal a specific geographical
origin for Burial 11–1 (OSM5), we were able to determine that her ancestry was broadly West African.

© The Author(s), 2022. Published by Cambridge University Press on behalf of Antiquity Publications Ltd.

I think for "West African" they meant west coast of Africa, not actual West Africa, can you show your medieval Latin American ILLUSTRATIVE DNA results and then click on the Sub-Saharan African section to see how much West African and how much Bantu you are.

This is my summary:

https://i.imgur.com/ZAH3qOJ.png

[HelloGuys]

I think for "West African" they meant west coast of Africa, not actual West Africa, can you show your medieval Latin American ILLUSTRATIVE DNA results and then click on the Sub-Saharan African section to see how much West African and how much Bantu you are.

There we are already assuming bro, until the study (Or a new one) decides something, it remains as it is in the study.

I trust in papers/studies and qpAdm, not so much with G25 while is a very good tool and matches with some professional studies, it is still not perfect and has its errors, so we have to trust in people who studied all this (Professionals) and published in the scientific community.

Anyway, here you have:

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

[Eurafricanid]

There we are already assuming bro, until the study (Or a new one) decides something, it remains as it is in the study.

I trust in papers/studies and qpAdm, not so much with G25 while is a very good tool and matches with some professional studies, it is still not perfect and has its errors, so we have to trust in people who studied all this (Professionals) and published in the scientific community.

Anyway, here you have:

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

In the Study they didn't even try to compare the sample to other SSA populations.

[Laredo]

Could you click on the blue gear and unselect pict and roman britain and click on recalculate
https://i.imgur.com/DekadOo.png


Here

https://gcdnb.pbrd.co/images/dfaQfgOI0F98.jpg?o=1

[Laredo]

Nice, good amount of Roman and NA (A shift that is more comum in Latin-Americans than Iberians), in ur AncestryDNA thread u got 2% Jew, 1% Levant and 1% North Italian, prob indicative of Serfadi (3% - 5%), but despite ur South Mediterran shift u seens in a plausible variation anyway, can u share ur IllustrativeDNA results?

Cool so I have real Jewish ancestry?

[Jingle Bell]

Cool so I have real Jewish ancestry?

Yep prob, im very sure u have, u also seens more East Med shifted
Could u share ur g25 scaled coords?

[Eurafricanid]

Here

https://gcdnb.pbrd.co/images/dfaQfgOI0F98.jpg?o=1

These are mine for you to compare:

https://i.imgur.com/7xXygSg.png

[Eurafricanid]

Yep prob, im very sure u have, u also seens more East Med shifted
Could u share ur g25 scaled coords?

Looking at my results, whould you say that I have Jewish, too?

[Laredo]

These are mine for you to compare:

https://i.imgur.com/7xXygSg.png

Cool :) the Iberian it's identical except you scored Levant while I got Germanic. Are Portuguese and Spaniards genetically Identical? As you guys all know I'm not knowledgeable when It comes to this things.

[Eurafricanid]

Cool :) the Iberian it's identical except you scored Levant while I got Germanic. Are Portuguese and Spaniards genetically Identical? As you guys all know I'm not knowledgeable when It comes to this things.

The Iberian is not identical I score almost 26%, while you score 21.4%, also remember that I'm only 1/2 Euro, while you're close to 60%.

[Laredo]

The Iberian is not identical I score almost 26%, while you score 21.4%, also remember that I'm only 1/2 Euro, while you're close to 60%.

Still doesn't explain the Germanic we are full colonial your euro Is Portuguese mine Is Northern Spanish? Could be the explanation of Germanic?

[Jingle Bell]

Here

https://gcdnb.pbrd.co/images/dfaQfgOI0F98.jpg?o=1

mine for a comparison:
https://i.imgur.com/pMBGIQL.png

overall very similar but my euro side seens more Levant towards while urs more NA towards

[Jingle Bell]

Looking at my results, whould you say that I have Jewish, too?

Prob, but u show a more Caucasus/Anatolian drift (Late Roman?) that its less comum in Jews, while me n Laredo a more Levant-like profile (and he scores some Jew in ANcestryDNA) , he also got a ton of NA while u got 0%, in the 3 u are the less or second less MENA shifted

[Laredo]

mine for a comparison:
https://i.imgur.com/pMBGIQL.png

overall very similar but my euro side seens more Levant towards while urs more NA towards

Cool :) but I'm wondering why you guys got more Levant (Jewish) than me are Portuguese more eastern Mediterranean than Spaniards? Why I got Germanic??!!!!!

[Laredo]

Prob, but u show a more Caucasus/Anatolian drift (Late Roman?) that its less comum in Jews, while me n Laredo a more Levant-like profile, he also got a ton of NA while u got 0%, in the 3 u are the less MENA shifted

Oh really?

[Jingle Bell]

Cool :) the Iberian it's identical except you scored Levant while I got Germanic. Are Portuguese and Spaniards genetically Identical? As you guys all know I'm not knowledgeable when It comes to this things.

Portuguese and West Spaniards are basically identical, but not the East/Vascones ones
U guys are very similar but u are more MENA shift proporcionally (EUAF is 50% Iberian while u is 60%)

[Jingle Bell]

Cool :) but I'm wondering why you guys got more Levant (Jewish) than me are Portuguese more eastern Mediterranean than Spaniards? Why I got Germanic??!!!!!

Brazil received a lot of Marranos (New-Christians) in the first Portuguese waves of 16CE, u got Germanic bcs u know Visigoths, Suebis, Vandals etc. . . but me and EUAF also got more Gaul (Celt-like) than u in a comparison. and no overall Portugal its not more East Med than Spain, but Portugal generally have more NA than MOST parts of Spain

[Laredo]

Portuguese and West Spaniards are basically identical, but not the East/Vascones ones
U guys are very similar but u are more MENA shift proporcionally (EUAF is 50% Iberian while u is 60%)

What part of Brazil would I be able to pass In your opinion? I think I can pass as a pardo. I know I'm more amerindian than literally all Brazilians in the world so I have that on mind.

[Jingle Bell]

What part of Brazil would I be able to pass In your opinion? I think I can pass as a pardo. I know I'm more amerindian than literally all Brazilians in the world so I have that on mind.

North, N Brazil has 20% - 35% Native in average, more or less ur range
despite that u would be pardo, moreno, cabloco etc, but u pass in all Brazil pretty well, less in South region

[HelloGuys]

Double post.

[HelloGuys]

1.**pass**




> results$weights
# A tibble: 3 × 5
target left weight se z
<chr> <chr> <dbl> <dbl> <dbl>
1 Portugal_Conimbriga_Roman.SG Iberian_IA 0.726 0.103 7.05
2 Portugal_Conimbriga_Roman.SG Roman 0.217 0.131 1.66
3 Portugal_Conimbriga_Roman.SG North_African.DG 0.0563 0.0347 1.63
> results$popdrop
# A tibble: 7 × 14
pat wt dof chisq p f4rank Iberian_IA Roman North_African.DG feasible best dofdiff chisqd…¹ p_nes…²
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
1 000 0 8 13.6 9.19e- 2 2 0.726 0.217 0.0563 TRUE NA NA NA NA



2.**pass**




> results$weights
# A tibble: 3 × 5
target left weight se z
<chr> <chr> <dbl> <dbl> <dbl>
1 Portugal_Miroico_LateRoman_oAfrica.SG Iberian_IA 0.467 0.0916 5.10
2 Portugal_Miroico_LateRoman_oAfrica.SG Roman 0.206 0.114 1.81
3 Portugal_Miroico_LateRoman_oAfrica.SG North_African.DG 0.328 0.0302 10.8
> results$popdrop
# A tibble: 7 × 14
pat wt dof chisq p f4rank Iberian_IA Roman North_African.DG feasible best dofdiff chisqd…¹ p_nes…²
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
1 000 0 8 10.4 2.35e- 1 2 0.467 0.206 0.328 TRUE NA NA NA NA



3.**fail**




> results$weights
# A tibble: 3 × 5
target left weight se z
<chr> <chr> <dbl> <dbl> <dbl>
1 Portugal_Miroico_LateRoman.SG Iberian_IA 0.503 0.0709 7.09
2 Portugal_Miroico_LateRoman.SG Roman 0.397 0.0898 4.42
3 Portugal_Miroico_LateRoman.SG North_African.DG 0.0996 0.0236 4.23
> results$popdrop
# A tibble: 7 × 14
pat wt dof chisq p f4rank Iberian_IA Roman North_African.DG feasible best dofdiff chisqd…¹ p_nes…²
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
1 000 0 8 28.3 4.28e- 4 2 0.503 0.397 0.0996 TRUE NA NA NA NA



4.**pass (close call)**




> results$weights
# A tibble: 3 × 5
target left weight se z
<chr> <chr> <dbl> <dbl> <dbl>
1 Portugal_MonteDaNora_LateRoman.SG Iberian_IA 0.403 0.0690 5.84
2 Portugal_MonteDaNora_LateRoman.SG Roman 0.395 0.0843 4.69
3 Portugal_MonteDaNora_LateRoman.SG North_African.DG 0.202 0.0226 8.95
> results$popdrop
# A tibble: 7 × 14
pat wt dof chisq p f4rank Iberian_IA Roman North_African.DG feasible best dofdiff chisqd…¹ p_nes…²
<chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
1 000 0 8 15.7 4.67e- 2 2 0.403 0.395 0.202 TRUE NA NA NA NA



What if in qpAdm you put together samples that are genetically distinct between them and labeled as a one reference?

For example a source 1 called African but with two different populations:

African: Gambian and Moroccan_North.

And a source 2 called Iberian, but the same issue:

Iberian: Sephardic_Jew and Spanish_Andalucia.

What would happen?

[Eurafricanid]

Prob, but u show a more Caucasus/Anatolian drift (Late Roman?) that its less comum in Jews, while me n Laredo a more Levant-like profile (and he scores some Jew in ANcestryDNA) , he also got a ton of NA while u got 0%, in the 3 u are the less or second less MENA shifted

This is mine in the personalized ancient with all the Roman Age samples:

https://i.imgur.com/sh86ppW.png

[kingmob]

What if in qpAdm you put together samples that are genetically distinct between them and labeled as a one reference?

For example a source 1 called African but with two different populations:

African: Gambian and Moroccan_North.

And a source 2 called Iberian, but the same issue:

Iberian: Sephardic_Jew and Spanish_Andalucia.

What would happen?

Big standard errors and nuked p values.

I am away atm, I will look into your request when I get back.

Please keep the thread clean, requests are overlooked.

[HelloGuys]

Big standard errors and nuked p values.

I am away atm, I will look into your request when I get back.

Please keep the thread clean, requests are overlooked.

Thanks! So do you think if you label this reference with these two populations would fail?

African: Angolan and Gambian.

One is from Central Africa (Bantú) and the another one is West Africa (Niger-Congo/Mandé), in G25 they have a distance between 0.05418 to 0.06334 (Depending the references used).

Btw I sent you a PM bro.

No problem, I'll try not to do Off-Topic.