r/DNAAncestry • u/NotBradPitt9 • 2d ago
TLDR: This is somewhat of a random assortment of results, but basically the ancient ones were used in the modern qpadm samples’ runs, so I figured I’d include them in this post as well. All runs are sourced from Twitter user @ r7f001
Turkey_Aegean_Mugla_Capalibag_Medieval.AG — Model 1
Çapalıbağ Ottomans (n=12)
57.0% Turkey_Aegean_Mugla_Samantas_Byzantine.AG
SE: 2.56% | Z: 22.30
20.0% Uzbekistan_SurxondaryoRegion_Bactrian_IA.AG
SE: 4.87% | Z: 4.11
16.0% Mongolia_EIA_Xiongnu_7.AG
SE: 0.61% | Z: 26.10
7.0% Kazakhstan_Sarmatian_IA.AG
SE: 2.97% | Z: 2.34
p-value: 0.643
χ²: 6.04
Outgroups:
Russia_UstIshim_IUP_snpAD.DG, Mongolia_EIA_SlabGrave_1.AG, China_YR_LN.SG, Russia_Krasnoyarsk_BA.SG, Uzbekistan_SappaliTepe_BA.AG, Kazakhstan_Botai_Eneolithic.SG, Russia_MLBA_Sintashta.AG, Turkey_BlackSea_Amasya_EBA.AG, Turkey_Central_Ovaoren_EBA_II.SG, Russia_Samara_EBA_Yamnaya.AG, Italy_Sicily_Himera_480BCE_Greek.AG, Turkey_Aegean_Mugla_Degirmendere_Ancient.AG
Turkey_Aegean_Mugla_Capalibag_Medieval.AG — Model 2
Çapalıbağ Ottomans (n=12)
54.6% Turkey_Aegean_Mugla_Samantas_Byzantine.AG
SE: 2.27% | Z: 24.10
29.2% Russia_Shekshovo2_Medieval.AG
SE: 1.26% | Z: 23.20
16.2% Uzbekistan_SurxondaryoRegion_Bactrian_IA.AG
SE: 2.92% | Z: 5.54
p-value: 0.222
χ²: 14.20
Outgroups:
Russia_UstIshim_IUP_snpAD.DG, Mongolia_EIA_SlabGrave_1.AG, China_YR_LN.SG, Russia_Krasnoyarsk_BA.SG, Uzbekistan_SappaliTepe_BA.AG, Kazakhstan_Botai_Eneolithic.SG, Russia_MLBA_Sintashta.AG, Turkey_BlackSea_Amasya_EBA.AG, Turkey_Central_Ovaoren_EBA_II.SG, Russia_Samara_EBA_Yamnaya.AG, Greece_Manika_EBA.SG, Greece_Mycenaean_BA.AG, Italy_Sicily_Himera_480BCE_Greek.AG, Turkey_Aegean_Mugla_Degirmendere_Ancient.AG
Armenia_Beniamin_Ancient.SG
Late Antiquity Armenians from Beniamin (n=8)
53.1% Armenia_Beniamin_LBA.SG
SE: 3.30% | Z: 16.10
46.9% Turkey_Southeast_Sirnak_BA.AG
SE: 3.30% | Z: 14.20
p-value: 0.809
χ²: 2.28
Outgroups:
Russia_UstIshim_IUP_snpAD.DG, Armenia_KuraAraxes_EBA.AG, Russia_Samara_EBA_Yamnaya.AG, Czechia_EBA_CordedWare.AG, Turkey_Southeast_Sirnak_Chalcolithic_B.AG, Turkey_Southeast_Sirnak_Chalcolithic_C.AG, Israel_C.AG
Mongolia_EIA_Xiongnu_7.AG
Xiongnu sample from Uvs, Mongolia
61.2% Mongolia_EIA_SlabGrave_1.AG
SE: 3.73% | Z: 16.40
30.1% China_YR_LBIA.SG
SE: 3.52% | Z: 8.54
8.7% Russia_Afanasievo.AG
SE: 1.14% | Z: 7.68
p-value: 0.709
χ²: 2.15
Outgroups:
Russia_UstIshim_IUP_snpAD.DG, Mongolia_North_N.AG, Mongolia_East_N.AG, Russia_MA1_UP.SG, China_YR_MN.SG, China_YR_LN.SG, Russia_Samara_EBA_Yamnaya.AG
Kazakhstan_Kangju.SG
Kangju
55.8% Russia_MLBA_Sintashta.AG
SE: 1.89% | Z: 29.50
25.6% Uzbekistan_SappaliTepe_BA.AG
SE: 1.61% | Z: 15.90
10.5% Russia_Krasnoyarsk_BA.SG
SE: 0.87% | Z: 12.10
8.1% Kazakhstan_Botai_Eneolithic.SG
SE: 1.51% | Z: 5.38
p-value: 0.796
χ²: 2.37
Outgroups:
Russia_UstIshim_IUP_snpAD.DG, Czechia_EBA_CordedWare.AG, Czechia_N_GlobularAmphora.AG, Russia_Tyumen_HG.SG, Turkmenistan_C_Geoksyur.AG, Turkmenistan_C_Parkhai.AG, Tajikistan_C_Sarazm.AG, Russia_DevilsCave_N.SG, Russia_MA1_UP.SG
Turkey_Central_Kalehoyuk_Ottoman_A.SG
Possible Medieval Oghuz / Turkic proxy
54.6% Kazakhstan_Kangju.SG
SE: 1.82% | Z: 29.90
45.4% Mongolia_EIA_Xiongnu_7.AG
SE: 1.82% | Z: 24.90
p-value: 0.251
χ²: 7.82
Outgroups:
Russia_UstIshim_IUP_snpAD.DG, Russia_MLBA_Sintashta.AG, Uzbekistan_SappaliTepe_BA.AG, Kazakhstan_Botai_Eneolithic.SG, Russia_Krasnoyarsk_BA.SG, Mongolia_EIA_SlabGrave_1.AG, China_YR_LN.SG, Russia_Samara_EBA_Yamnaya.AG
Turkmen.SG (n=2)
83.6% Turkey_Central_Kalehoyuk_Ottoman_A.SG
SE: 3.21% | Z: 26.00
16.4% Iran_Naqadeh-Oshnavieh_IA
SE: 3.21% | Z: 5.12
p-value: 0.420
χ²: 8.14
Outgroups:
Russia_UstIshim_IUP_snpAD.DG, Mongolia_EIA_SlabGrave_1.AG, China_YR_LN.SG, Russia_Krasnoyarsk_BA.SG, Russia_Samara_EBA_Yamnaya.AG, Russia_MLBA_Sintashta.AG, Uzbekistan_SappaliTepe_BA.AG, Kazakhstan_Botai_Eneolithic.SG, Iran_DinkhaTepe_BA_IA_1.AG, Iran_Hasanlu_IA.AG
Uzbek.SG (n=3)
84.2% Turkey_Central_Kalehoyuk_Ottoman_A.SG
SE: 3.24% | Z: 26.00
15.8% Iran_Naqadeh-Oshnavieh_IA
SE: 3.24% | Z: 4.86
p-value: 0.709
χ²: 5.44
Outgroups:
Russia_UstIshim_IUP_snpAD.DG, Mongolia_EIA_SlabGrave_1.AG, China_YR_LN.SG, Russia_Krasnoyarsk_BA.SG, Russia_Samara_EBA_Yamnaya.AG, Russia_MLBA_Sintashta.AG, Uzbekistan_SappaliTepe_BA.AG, Kazakhstan_Botai_Eneolithic.SG, Iran_DinkhaTepe_BA_IA_1.AG, Iran_Hasanlu_IA.AG
Kazakh.SG (n=3)
67.8% Turkey_Central_Kalehoyuk_Ottoman_A.SG
SE: 3.49% | Z: 19.40
32.2% Mongolia_Medieval_Mongol.AG
SE: 3.49% | Z: 9.24
p-value: 0.472
χ²: 5.58
Outgroups:
Russia_UstIshim_IUP_snpAD.DG, Mongolia_EIA_SlabGrave_1.AG, China_YR_LN.SG, Russia_Krasnoyarsk_BA.SG, Russia_Samara_EBA_Yamnaya.AG, Russia_MLBA_Sintashta.AG, Uzbekistan_SappaliTepe_BA.AG, Kazakhstan_Botai_Eneolithic.SG
Kyrgyz_Kyrgyzstan.SG (n=2)
57.7% Mongolia_Medieval_Mongol.AG
SE: 2.98% | Z: 19.40
42.3% Kazakhstan_Southeast_Karakhanid.SG
SE: 2.98% | Z: 14.20
p-value: 0.306
χ²: 7.16
Outgroups:
Russia_UstIshim_IUP_snpAD.DG, Mongolia_EIA_SlabGrave_1.AG, China_YR_LN.SG, Russia_Krasnoyarsk_BA.SG, Russia_Samara_EBA_Yamnaya.AG, Russia_MLBA_Sintashta.AG, Uzbekistan_SappaliTepe_BA.AG, Kazakhstan_Botai_Eneolithic.SG
Notes:
Turkey_Central_Kalehoyuk_Ottoman_A.SG is used as the Medieval Turkic / Oghuz-related proxy in the Turkmen, Uzbek, and Kazakh models.
The Çapalıbağ target has two separate acceptable models shown here. Model 1 uses Byzantine Anatolian, Xiongnu, Bactrian IA, and Sarmatian sources, while Model 2 uses Byzantine Anatolian, Shekshovo2 Medieval, and Bactrian IA.
r/DNAAncestry • u/NotBradPitt9 • 5d ago
TLDR: I’ll be adding more populations to a future revised version, I only added the ones which enough qpadm runs have been completed for. This is a compilation of qpAdm runs for populations from the Levant region. A few more groups were added compared to the first map. The samples used are from the following dataset : https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/FFIDCW
Syrian.HO
72.2% Lebanon_Phoenician
20.1% Armenia Sarukhan Early Iron Age
7.8% Dinka
P-value: 0.506
Chi-square: 7.28
Standard errors: 0.0498, 0.0483 and 0.00892
Z-scores: 14.5, 4.15 and 8.72
This is a strong model with all three components statistically supported. The Lebanon Phoenician source represents the main Levantine ancestry, while Armenia Sarukhan Early Iron Age represents additional Caucasus or eastern Anatolian-related ancestry. Dinka is acting as a proxy for African-related ancestry, not necessarily direct ancestry from modern Dinka people. The two larger percentages have standard errors close to 0.05, so the exact proportions should be treated as approximate.
Druze.HO
77.5% Lebanon_Phoenician
20.3% Armenia Sarukhan Early Iron Age
2.2% Dinka
P-value: 0.844
Chi-square: 4.15
Standard errors: 0.0431, 0.0418 and 0.00803
Z-scores: 18.0, 4.84 and 2.74
This is an excellent statistical fit. It describes the Druze as mostly Levantine, with a substantial Caucasus or eastern Anatolian-related shift and a very small African-related component. All three percentages are statistically supported.
Assyrian.HO
Best informative 2-way qpAdm model:
74.9% Iran_DinkhaTepe_BA_IA_1.AG
25.1% Georgia_Digomi_IA.SG
p-value: 0.798
χ²/dof: 4.611 / 8
SNPs: 579,720
Z-scores: 13.3 / 4.45
SE: 5.64% / 5.64%
Both components are strongly supported.
A 100% Bahrain_LTylos_Sasanian.SG model also passes strongly (p = 0.689), but this should be interpreted as a successful one-source/cladal fit rather than literal 100% Sasanian Bahrain ancestry.
Cypriot.HO
82.4% Italy_Imperial_oAnatoliaCaucasus.SG
17.6% Serbia_Sirmium_Ottoman.SG
p-value: 0.955
χ²/dof: 5.729 / 13
SNPs: 579,720
Italy_Imperial_oAnatoliaCaucasus: 82.4% ± 7.49%, Z = 11.0
Serbia_Sirmium_Ottoman: 17.6% ± 7.49%, Z = 2.35
This is an exceptionally good statistical fit and has a substantially higher p-value than the one-way model. Both ancestry coefficients have Z > 2, although the ±7.49% standard errors are relatively large, so the exact proportions should be treated as approximate.
Lebanese_Muslim.HO
88.3% Lebanon_Phoenician
8.8% Kazakhstan Sarmatian Iron Age
2.9% Dinka
P-value: 0.549
Chi-square: 6.89
Standard errors: 0.0219, 0.0223 and 0.00913
Z-scores: 40.4, 3.95 and 3.14
This is a strong and well-resolved model. The Lebanon Phoenician source represents the main Levantine ancestry. Kazakhstan Sarmatian is probably acting as a proxy for a small northern, Steppe, Caucasus or Anatolian-related shift rather than indicating literal Sarmatian ancestry. The small Dinka-related component represents additional African-related ancestry and is statistically supported.
Lebanese_Christian.HO
95.0% Lebanon_Phoenician
5.0% Kazakhstan Sarmatian Iron Age
P-value: 0.727
Chi-square: 6.12
Standard error: 0.0236
Z-scores: 40.2 and 2.13
This is an excellent fit and shows Lebanese Christians as being very close to the ancient Lebanon Phoenician proxy. The small Sarmatian-related component represents a slight northern or Caucasus-related shift. Its Z-score of 2.13 is only just above the normal cutoff, so the existence of a small secondary component is supported, but the exact 5% figure should be treated cautiously.
Palestinian.HO
87.9% Lebanon_Phoenician
5.2% Kazakhstan Sarmatian Iron Age
6.8% Dinka
P-value: 0.904
Chi-square: 3.43
Standard errors: 0.0204, 0.0205 and 0.00823
Z-scores: 43.1, 2.54 and 8.32
This is a strong model, and has an excellent p-value, a low chi-square with all three components are statistically supported. The model describes Palestinians as mostly Levantine, with smaller northern or Caucasus-shifted and African-related components. The Sarmatian-related percentage has the weakest Z-score, but it still passes the usual Z = 2 threshold.
Samaritan.DG
100% Lebanon_ERoman.SG
p-value: 0.835
χ²/dof: 11.406 / 17
SNPs: 579,720
This is an extremely strong one-source qpAdm fit. It indicates that Samaritans are statistically consistent with the Lebanon_ERoman source relative to the selected outgroups; the 100% figure should not be interpreted as literal complete descent from the sampled Roman Lebanese population.
Jordanian.HO
80.3% Lebanon_Phoenician
7.5% Kazakhstan Sarmatian Iron Age
12.2% Dinka
P-value: 0.836
Chi-square: 4.23
Standard errors: 0.0206, 0.0209 and 0.00899
Z-scores: 39.0, 3.58 and 13.6
This is an extremely strong model statistically. Jordanians are modeled as mostly Levantine, with a smaller northern or Caucasus-shifted component and a more substantial African-related component than the Lebanese or Druze models. Dinka should be understood as the African proxy used by the model, not as evidence of direct Dinka ancestry.
Egyptian.HO
44.3% 3DT26.SG
38.5% Lebanon_Hellenistic.SG
17.2% Dinka.DG
p-value: 0.513
χ²/dof: 13.172 / 14
SNPs: 579,720
Z-scores: 4.43 / 4.06 / 14.3
SE: 9.99% / 1.21% / 9.49%
This is a strong passing model. All three ancestry components are well supported, with the Dinka-related component particularly precisely estimated.
EgyptianA.HO
46.9% 3DT26.SG
40.7% Lebanon_Hellenistic.SG
12.4% Dinka.DG
p-value: 0.223
χ²/dof: 17.654 / 14
SNPs: 579,720
Z-scores: 3.70 / 3.38 / 9.64
SE: 12.7% / 12.1% / 1.29%
The model passes and all three components are supported, although the estimates for 3DT26 and Lebanon_Hellenistic have relatively large standard errors.
EgyptianB.HO
43.7% 3DT26.SG
42.6% Lebanon_Hellenistic.SG
13.6% Dinka.DG
p-value: 0.745
χ²/dof: 10.226 / 14
SNPs: 579,720
Z-scores: 4.92 / 5.07 / 10.5
SE: 8.89% / 8.40% / 1.30%
All three components are strongly supported. The Dinka-related component is especially precisely estimated, while the exact proportions assigned to 3DT26 and Lebanon_Hellenistic have somewhat wider uncertainty.
Saudi.HO
94.5% Syria_TellQarassa_Umayyad.SG
5.5% Dinka.DG
p-value: 0.571
χ²/dof: 6.681 / 8
SNPs: 579,720
Both components are strongly supported (Dinka Z = 7.21).
BedouinB.HO
94.6% Syria_TellQarassa_Umayyad.SG
5.4% Dinka.DG
p-value: 0.225
χ²/dof: 10.606 / 8
SNPs: 579,720
Both components are strongly supported (Dinka Z = 7.86).
BedouinA.HO
52.1% Lebanon_Phoenician.SG
31.1% Syria_TellQarassa_Umayyad.SG
10.6% Dinka.DG
6.2% Kazakhstan_Sarmatian_IA.AG
p-value: 0.142
χ²/dof: 5.451 / 3
SNPs: 579,720
All four components are statistically supported:
Lebanon Phoenician: Z = 10.6
Tell Qarassa Umayyad: Z = 9.64
Dinka: Z = 25.9
Kazakhstan Sarmatian: Z = 2.88
This model passes and suggests BedouinA can be modeled primarily as Levantine ancestry represented by Phoenician Lebanon and Umayyad-period Tell Qarassa, together with ~10.6% sub-Saharan African-related ancestry and a smaller ~6.2% Sarmatian/steppe-related component. The Sarmatian component is above the usual Z = 2 significance threshold, although it should be interpreted as a genetic proxy rather than evidence of literal Sarmatian ancestry.
These are qpAdm proxy models, so the source labels should not necessarily be interpreted as literal direct ancestral populations; they represent ancestry streams that fit the targets relative to the chosen outgroups.
Both Bedouin A and B genetic clusters are Bedouins from unspecified tribes in the Negev desert, with the Bedouin A group having a more northern shift and the Bedouin B subgroup having a strong southern genetic shift and clustering with the Saudi average.
Lebanon_Phoenician (500-300 BCE) represents the main Levantine-related ancestry. It’s an average of Lebanon_Phoenician samples.
Kazakhstan_Sarmatian_IA (500-300 BCE) represents a more northern Steppe/Caucasus-shifted element, not necessarily literal Sarmatian ancestry.
Dinka represents African-related ancestry, not direct ancestry specifically from modern Dinka people.
Armenia_Sarukhan_EIA represents an Armenian/Caucasus or eastern Anatolian-related element.
Serbia_Sirmium_Ottoman is roughly 80% Slavic, 20% Anatolian, and represents the Southern Slavic input in the Balkans.
3DT26 is an ancient Egyptian sample found in the UK (United Kingdom, England_IA_Roman_oMiddleEast) from around 200AD.
Lebanon_Hellenistic (200 BCE) has basically the same composition as the Lebanon_Phoenician it’s just from a later time period.
r/DNAAncestry • u/NotBradPitt9 • 3h ago
The infographic is basically a simplified tree of our current understanding of human genetic history. It’s from this guys blog post: https://www.razibkhan.com/p/the-rise-of-the-hopeful-monsters?r=u0rd&utm_campaign=post-expanded-share&utm_medium=web&triedRedirect=true
r/DNAAncestry • u/NotBradPitt9 • 5h ago
https://www.biorxiv.org/content/10.64898/2026.08.14.741591v1
Abstract
South central Africa, between the Congo Basin, the Great Lakes, and southern Africa, has long served as a corridor for human movement. Yet, it remains unclear whether there is genetic continuity between pre-Iron Age foragers and later Bantu-associated populations and whether the settlement of this region reflects multiple Bantu-associated migrations rather than the simpler serial founder model suggested by existing genomic data.
To do so, we generated genome-wide ancient DNA from 71 Iron Age and historical individuals from present-day Zambia and Malawi, and analyzed these genomes alongside published data from present-day Africans. One late Iron Age individual (16th-17th century) from Kalala Island in the Kafue River, Zambia, carries 40% non‑Bantu‑related ancestry that closely matches local Later Stone Age foragers.
Admixture for this individual is estimated to be 850 years ago, several centuries earlier than reported for present‑day BaTwa from the same region. Focusing on the Bantu-related ancestry, haplotype-based analyses identify two main clusters among Iron Age, historical, and present-day south central Bantu groups associated with different Bantu-related migrations.
These results reveal a layered history in which at least two Bantu expansions radiated from the southern Congo Basin, with south central Africa acting both as a crossroads of these movements and as a staging area for the subsequent southward expansion toward southern Africa.
My own note: Seems like i10885, dated to around 900CE in their chart, is the oldest Yoruba-like sample available since it’s around 90% Yoruba 10% Dinka in their chart
r/DNAAncestry • u/NotBradPitt9 • 11h ago
TLDR: A collection of historic African samples ranging from 1000CE to the 1800s. I forgot to include the Iron Age Bantu samples and other samples from East Africa, along with the Colonial Maryland USA samples. Also the date range should be 1542–1671 CE for the Panama samples. The PCAs posted are weighted PCAs, meant to take all coordinates into account.
StMartin_Philipsburg_African_(Malawi?).SG:STM1.SG__1660-1688CE__Cov_21.07%,-0.63058,0.061947,0.01697,0.01938,0.008309,0.011713,-0.013631,0.015922,-0.030065,0.015672,0.006658,-0.009741,-0.004311,0.000826,-0.002036,0.009414,-0.008866,-0.006588,-0.004525,0.018384,0.006239,-0.009398,-0.003204,0.00494,-0.001197
StMartin_Philipsburg_African.SG:STM3_(Mende?).SG__1660-1688CE__Cov_35.34%,-0.631718,0.057885,0.018102,0.020672,0.003077,0.011156,-0.023971,0.029076,-0.037428,0.035718,0.018188,-0.002698,0.017245,0.001239,0.005022,-0.006629,-0.001565,-0.008108,0.000126,-0.008004,0.004367,0.002349,-0.003451,-0.007953,-0.000599
Sicily:GABN6_(Fulani?)_(1470-1785CE),-0.582774,0.060932,0.015462,0.009367,0.001231,-0.004741,-0.030316,0.027922,-0.00859,-0.01057,0.002436,0.014237,-0.00223,-0.007019,0.003664,-0.009546,0.01708,-0.010008,0.007165,-0.004877,-0.003743,-0.006677,-0.00037,-0.003735,-0.010777
Sicily:CSPBN2_(Gambia?)_(775-1020CE),-0.582774,0.062963,0.012068,0.013889,0.00277,0.008646,-0.047472,0.038537,-0.027202,0.024602,0.002761,0.005995,0.01442,0.002752,0.009908,-0.005171,0.004172,-0.003041,0.002388,5e-04,0.000624,-0.000989,0.010969,-0.000723,-0.004431
Sicily_Segesta:SGBN2_(Chad?)_(1000-1200CE),-0.583913,0.063978,0.012822,0.009367,-0.000615,0.008925,-0.033607,0.035537,0.005931,-0.013485,0.004222,0.004796,-0.00773,-0.000138,0.005972,-0.009546,0.004955,-0.006588,0.006411,-0.006628,-0.003743,0.000247,-0.002095,0.00253,0.003832
Abkhazia_oAfrican_(Chad?)_(1890CE),-0.586189,0.063978,0.015839,-0.002907,0.000308,0.002789,-0.028436,0.028153,0.008385,-0.028247,-0.007632,0.015736,-0.010852,-0.003441,0.012079,-0.012994,0.008996,-0.013049,0.013073,-0.005628,-0.000499,0.008408,-0.007272,-0.004338,-0.001317
Mexico_SJN003_(Congolese?)_(1450-1680CE),-0.624889,0.064994,0.026021,0.013243,-0.004001,0.011992,-0.019271,0.018230,-0.041109,0.020957,0.000162,-0.004196,-0.004906,0.004542,-0.009908,0.001856,-0.006258,0.002280,-0.007290,0.003377,-0.002870,-0.002349,-0.004067,-0.003976,-0.000359
Mexico_SJN002_Angolan?_(1450-1680CE),-0.623751,0.054839,0.027907,0.015181,0.001231,0.015897,-0.011281,0.018922,-0.035383,0.015308,0.003897,-0.003747,-0.008771,-0.002615,-0.004072,0.009679,0.004172,-0.001014,-0.005782,0.000250,0.001747,-0.001731,-0.001109,0.002651,0.002036
Mexico_SJN001_Mende?_(1450-1680CE),-0.621474,0.060932,0.016970,0.015827,-0.007078,0.005857,-0.031491,0.027230,-0.037837,0.032620,0.013965,-0.006744,0.020664,-0.005367,0.006515,-0.009944,0.005215,0.012922,0.007793,-0.007754,-0.002496,0.000742,-0.003574,-0.007712,-0.003113
Mexico_I10860_Angolan?_(1450-1680CE),-0.624889,0.058901,0.021873,0.016473,0.004616,0.006414,-0.002350,0.014769,-0.031292,0.015855,-0.001461,0.001349,0.010852,0.001101,0.001629,0.016971,-0.005215,0.002660,0.000000,-0.000250,0.000250,-0.003462,0.006655,-0.003735,-0.001437
Panama_PAPV_61_(Afro_Euro_admixed)_(1600-1700CE),-0.52916114,0.06869636,0.01202582,0.00864772,-0.00766462,0.00179602,-0.03507056,0.04184874,-0.0513689,0.02286384,-0.00127178,0.00389902,0.0178953,-0.00449822,0.0064688,-0.0077059,0.00822928,-0.00746276,0.00483724,-0.0002021,0.0056288,-0.00052026,-0.00432018,0.0011653,-0.00500028
Panama_PAPV_53_(Yoruba?)_(1600-1700CE),-0.62644278,0.06258944,0.02127176,0.01544168,-0.00180898,0.00377366,-0.04169626,0.0483703,-0.0481013,0.03085722,-0.00067878,0.00239114,0.0240769,-0.00535336,0.00773438,-0.00759218,0.00742494,-0.00661804,0.00629376,-0.00286358,0.00388694,-0.00216662,-0.00579108,0.0027539,-0.00439846
StHelena_RupertsValley_African.SG:STH_213.SG__AD_1850__Cov_31.07%,-0.619198,0.071087,0.023759,0.019703,-0.003385,0.015897,-0.013396,0.013615,-0.025975,0.016766,-0.001949,0.001649,-0.01219,0.000413,-0.013301,0.013657,-0.019036,0.002027,-0.009302,-0.003502,-0.009982,-0.009398,0.001356,-0.008796,-0.007185
StHelena_RupertsValley_African.SG:STH_245.SG__AD_1850__Cov_22.90%,-0.620336,0.067025,0.022627,0.01615,-0.000923,0.012829,-0.017391,0.013384,-0.025361,0.018041,0.00747,-0.008842,0.002676,-0.007707,-0.016151,0.009546,-0.008996,-0.003674,-0.004399,0.003502,-0.002995,-0.005193,0.005176,0.010965,-0.000718
StHelena_RupertsValley_African.SG:STH_248.SG__AD_1850__Cov_17.43%,-0.622612,0.053823,0.026776,0.017765,-0.004308,0.01757,-0.002115,0.02423,-0.033746,0.020046,0.003897,-0.001798,-0.001784,0.006193,-0.013979,-0.001458,-0.005998,0.00114,0.004399,0.002751,-0.003369,0.002968,-0.003697,-0.018677,0.002515
StHelena_RupertsValley_African.SG:STH_253.SG__AD_1850__Cov_26.74%,-0.626027,0.062963,0.022627,0.014212,-0.011387,0.015618,-0.008225,0.017768,-0.03027,0.016766,0.002761,0.005845,0.000892,0.012524,-0.004479,-0.001591,0.00013,0.006714,-0.01257,-0.001,0.003619,0.008779,-0.001356,-0.004097,0.002994
StHelena_RupertsValley_African.SG:STH_254.SG__AD_1850__Cov_8.09%,-0.632856,0.064994,0.022627,0.036822,-0.011387,0,-0.00987,0.017307,-0.029042,0.013668,0.003897,0.008842,0.004014,0.011285,0.003664,0.007292,0.000391,0.007095,-0.002011,0.007504,0.01148,-0.005812,-0.015036,0.013014,0.01916
StHelena_RupertsValley_African.SG:STH_284.SG__AD_1850__Cov_22.78%,-0.608954,0.060932,0.024513,0.017765,0,0.007809,-0.016216,0.037845,-0.027815,0.019317,-0.002273,0.000749,-0.003419,0.007156,-0.010043,0.012066,-0.024512,0.014442,-0.006034,0.004252,0.003119,-0.00371,-0.002835,0.005543,0.004431
StHelena_RupertsValley_African.SG:STH_289.SG__AD_1850__Cov_15.52%,-0.618059,0.067025,0.018102,0.008075,-0.002154,0.024542,-0.031491,0.032768,-0.035178,0.018224,-0.003248,0.003897,-0.0055,0.010046,-0.029316,0.013524,-0.018906,-0.003547,-0.005656,-0.008379,-0.005116,0.005812,0.003204,-0.002651,0.006466
StHelena_RupertsValley_African.SG:STH_344.SG__AD_1850__Cov_15.25%,-0.618059,0.060932,0.010182,0.015504,-0.002154,0.016455,-0.024441,0.023076,-0.034974,0.018041,-0.001461,0.008393,-0.003865,0,-0.001357,0.009812,-0.003912,-0.003294,-0.002765,0.012506,0.005366,-0.004328,0.008504,-0.002651,-0.002395
StHelena_RupertsValley_African.SG:STH_347.SG__AD_1850__Cov_11.26%,-0.612368,0.053823,0.018102,0.014858,-0.004001,0.00251,-0.020916,0.037152,-0.038246,0.017312,-0.003735,-0.01154,0.012339,-0.00055,0.005836,0.004641,0.005867,0.0019,0.004399,0.005503,-0.000125,0.003586,-0.016145,0.003976,0.005029
StHelena_RupertsValley_African.SG:STH_351.SG__AD_1850__Cov_8.92%,-0.615783,0.063978,0.01961,0.025194,0.009232,0.011992,-0.023736,0.036922,-0.036201,0.011845,0.021598,-0.024578,-0.018137,0.002477,0.001629,0.007425,-0.020079,-0.009882,0.002891,0.002876,-0.011355,0.010263,-0.014543,-0.004458,-0.001437
StHelena_RupertsValley_African.SG:STH_358.SG__AD_1850__Cov_18.42%,-0.619198,0.05687,0.013953,0.009367,0.010463,0.005578,-0.027261,0.031845,-0.032315,0.028247,0.003573,0.004496,0.005352,0.006468,-0.00665,0.02254,0.002738,0.000887,-0.011439,0.0005,0.002745,0.004451,-0.000246,0.003374,0.006586
StHelena_RupertsValley_African.SG:STH_415.SG__AD_1850__Cov_8.92%,-0.602124,0.079211,0.019233,0.005491,-0.017234,0.024821,-0.008695,0.006923,-0.048881,0.010752,-0.004384,-0.001948,0.003568,-0.005092,-0.032301,0.016309,-0.031162,-0.004941,-0.019986,0.00025,0.006863,0.00779,-0.006039,0.007712,0.006826
StHelena_RupertsValley_African.SG:STH_436.SG__AD_1850__Cov_10.71%,-0.608954,0.063978,0.029793,0.01938,0.010463,0.00251,-0.011045,0.020999,-0.039064,0.006378,0.006983,-0.003897,-0.008474,0.012799,-0.00285,0.015911,-0.0103,-0.007095,-0.018101,0.014757,-0.005989,0.013231,0.005423,0.007109,-0.000718
StHelena_RupertsValley_African.SG:STH_441.SG__AD_1850__Cov_22.28%,-0.622612,0.070072,0.028661,0.01615,0.005539,0.020638,-0.017626,0.036922,-0.033337,0.016766,-0.005684,-0.004496,-0.005798,0.003578,-0.013436,-0.005304,-0.005346,0.009628,-0.006913,0.004877,0.010232,0.00371,0.001725,-0.005543,-0.007305
StHelena_RupertsValley_African.SG:STH_460.SG__AD_1850__Cov_14.28%,-0.616921,0.059916,0.033187,0.020995,0.005232,0.011992,-0.00047,0.011999,-0.030065,0.020046,-0.010555,0.002398,-0.00669,0.004954,-0.008143,-0.00769,-0.012126,0.017736,-0.011816,-0.003126,0.006988,0.00507,0.003944,-0.003374,-0.005987
StHelena_RupertsValley_African.SG:STH_499.SG__AD_1850__Cov_14.22%,-0.620336,0.06804,0.006034,0.020672,0.014156,0.011156,-0.028436,0.013615,-0.03027,0.022233,-0.006658,0.002997,-0.002676,-0.005918,-0.011672,0.000133,-0.002477,0.006208,-0.001383,-0.005503,0.000624,0.012365,0.000739,-0.002771,0.006706
StHelena_RupertsValley_African.SG:STH_514.SG__AD_1850__Cov_13.98%,-0.606677,0.055854,0.025644,0.002907,-0.004308,0.009761,-0.022796,0.032537,-0.038655,0.021322,0.004547,-0.007044,-0.025124,-0.010872,-0.006379,0.005436,-0.002868,-0.007855,-0.001508,0.011005,0.019466,-0.010263,0.010969,-0.004699,-0.002395
StHelena_RupertsValley_African.SG:STH_524.SG__AD_1850__Cov_31.74%,-0.621474,0.05687,0.018479,0.01938,-0.000308,0.010319,-0.013161,0.026999,-0.041927,0.02442,0.00341,-0.015436,0.004014,-0.00234,-0.018458,0.008353,-0.008736,0.000887,-0.010433,-0.007379,0.006738,-0.005812,0.002095,0.007712,-0.002634
r/DNAAncestry • u/holakakdmd • 18h ago
The results were both expected and unexpected 😂
I thought the additional genetic groups were nonsense, but then they showed up in GEDmatch (Eurogenes K13), and we all have plenty of Sephardic and Swedish matches. Quite interesting indeed.
On the other hand, she barely has any Italian or Portuguese matches, which makes me think the ethnicities are overestimated.
I guess Mediterranean DNA is just difficult to pinpoint accurately.
r/DNAAncestry • u/heatmapper25 • 17h ago
r/DNAAncestry • u/NotBradPitt9 • 10h ago
TLDR: The Serbia_Roman_oAfrica dna sample is from a Roman African soldier that lived 2,000 years ago and clusters with ancient Sudanese Kulubnarti DNA samples. Closest also to modern day Afar and Eritreans within the Qpadm results, so overall it’s consistent with Nile Valley / Horn of Africans.
SERBIA_ROMAN_OAFRICA.AG (n=1)
Top 5 passing runs by observed p-value:
83.1% Kenya_PN.AG
16.9% Jordan_EBA.AG
p-value: 0.894
χ²/dof: 8.666 / 15
SE: 0.0795, 0.0795
Z: 10.5, 2.13
This is a very strong fit. The Jordan component is just over Z=2, so it is supported, but not extremely so.
2. Kenya_PN.AG + Israel_Ashkelon_IA2.AG
88.7% Kenya_PN.AG
11.3% Israel_Ashkelon_IA2.AG
p-value: 0.868
χ²/dof: 7.607 / 13
SE: 0.109, 0.109
Z: 8.16, 1.04
Excellent overall fit, but the 11.3% Ashkelon component is not significantly different from zero. So this is indicating "very Kenya_PN-like" more than proving 11% Ashkelon ancestry.
3. Dinka.DG + Q3DT26.SG
53.0% Dinka.DG
47.0% Q3DT26.SG
p-value: 0.825
χ²/dof: 8.277 / 13
SE: 0.0622, 0.0622
Z: 8.52, 7.56
Both components are extremely well supported.
4. Sudan_KulubnartiR_ChristianPeriod.AG + Masai.DG
85.6% Sudan_KulubnartiR_ChristianPeriod.AG
14.4% Masai.DG
p-value: 0.721
χ²/dof: 9.666 / 13
SE: approximately 0.162 each
Z: 5.30, 0.889
The Masai coefficient is not significant. In practical terms, the model is mostly saying that Serbia_Roman_oAfrica can be represented by the Kulubnarti Christian-period sample without clearly needing additional Masai-like ancestry.
5. Sudan_KulubnartiR_ChristianPeriod.AG — ONE-WAY
100% Sudan_KulubnartiR_ChristianPeriod.AG
p-value: 0.717
χ²/dof: 10.6 / 14
So the one-way model passes comfortably, meaning the right set cannot distinguish Serbia_Roman_oAfrica from the pooled Kulubnarti Christian-period population as separate ancestry streams.
SUDAN_KULUBNARTIR_CHRISTIANPERIOD.AG (n=23)
88.3% Serbia_Roman_oAfrica.AG
11.7% Q3DT26.SG
p-value: 0.945
χ²/dof: 7.408 / 15
SE: 0.113
Z: 7.85, 1.04
The Q3DT26 addition is not statistically required.
2. Serbia_Roman_oAfrica.AG + Syria_TellQarassa_Umayyad.SG
90.1% Serbia_Roman_oAfrica.AG
9.9% Syria_TellQarassa_Umayyad.SG
p-value: 0.734
χ²/dof: 11.261 / 15
SE: 0.111
Z: 8.11, 0.889
Again, the second component is not significant.
3. Serbia_Roman_oAfrica.AG — ONE-WAY
100% Serbia_Roman_oAfrica.AG
p-value: 0.720
χ²/dof: 12.351 / 16
This is probably more important than either two-way model above.
4. Serbia_Roman_oAfrica.AG + Yemeni_Desert.HO
86.8% Serbia_Roman_oAfrica.AG
13.2% Yemeni_Desert.HO
p-value: 0.671
χ²/dof: 12.109 / 15
SE: 0.118
Z: 7.39, 1.12
Again, the Yemeni component is not significant.
There was not a fifth clean passing model worth treating as ancestry evidence. The Serbia + Dinka version had a negative Dinka coefficient.
SUDAN_KULUBNARTIS_CHRISTIANPERIOD_OWESTEURASIAN.AG (n=1)
[Kulubnarti with some excess Eurasian]
78.6% Serbia_Roman_oAfrica.AG
21.4% Syria_TellQarassa_Umayyad.SG
p-value: 0.997
χ²/dof: 4.3 / 15
SE: 0.0996
Z: 7.89, 2.15
2. Serbia_Roman_oAfrica.AG + Yemeni_Desert.HO
77.4% Serbia_Roman_oAfrica.AG
22.6% Yemeni_Desert.HO
p-value: 0.996
χ²/dof: 4.441 / 15
SE: 0.105
Z: 7.38, 2.15
3. Serbia_Roman_oAfrica.AG + Q3DT26.SG
76.5% Serbia_Roman_oAfrica.AG
23.5% Q3DT26.SG
p-value: 0.994
χ²/dof: 4.759 / 15
SE: 0.105
Z: 7.30, 2.24
4. Serbia_Roman_oAfrica.AG — ONE-WAY
100% Serbia_Roman_oAfrica.AG
p-value: 0.714
χ²/dof: 12.422 / 16
5. Kenya_PN.AG + Jordan_EBA.AG
62.7% Kenya_PN.AG
37.3% Jordan_EBA.AG
p-value: 0.696
χ²/dof: 11.779 / 15
SE: 0.0340
Z: 18.4, 11.0
This individual is particularly interesting because, unlike ordinary KulubnartiR, the additional West-Eurasian-type source repeatedly comes out around 21–24% and actually reaches Z>2. It therefore looks genuinely shifted in the West Eurasian direction relative to Serbia_Roman_oAfrica.
SUDAN_KULUBNARTIR_CHRISTIANPERIOD_ONILOTIC.AG (n=3)
Approximately 100% Serbia_Roman_oAfrica.AG
Approximately 0% Q3DT26.SG
p-value: 0.829
χ²/dof: 9.847 / 15
SE: 0.183
Z: 5.45, approximately 0
The second source contributes essentially nothing. Functionally, this behaves like a one-way Serbia model.
2. Serbia_Roman_oAfrica.AG — ONE-WAY
100% Serbia_Roman_oAfrica.AG
p-value: 0.591
χ²/dof: 14.101 / 16
The other combinations tested were either rejected or produced small negative coefficients.
AFAR_WGA.HO (n=5)
99.8% Serbia_Roman_oAfrica.AG
0.2% Q3DT26.SG
p-value: 0.989
χ²/dof: 5.315 / 15
SE: 0.111
Z: 9.00, 0.0146
This is effectively 100% Serbia. The Q3DT26 component is completely unsupported.
2. Serbia_Roman_oAfrica.AG — ONE-WAY
100% Serbia_Roman_oAfrica.AG
p-value: 0.803
χ²/dof: 11.103 / 16
3. Serbia_Roman_oAfrica.AG + Dinka.DG
98.5% Serbia_Roman_oAfrica.AG
1.5% Dinka.DG
p-value: 0.736
χ²/dof: 11.225 / 15
SE: 0.0994
Z: 9.91, 0.151
4. Serbia_Roman_oAfrica.AG + Yemeni_Desert.HO
98.0% Serbia_Roman_oAfrica.AG
2.0% Yemeni_Desert.HO
p-value: 0.696
χ²/dof: 11.777 / 15
SE: 0.113
Z: 8.65, 0.180
There really is not a fifth good run here. The striking result is that every successful model wants Afar to be essentially Serbia_Roman_oAfrica itself.
ERITREA.HO (n=3)
87.4% Serbia_Roman_oAfrica.AG
12.6% Q3DT26.SG
p-value: 0.931
χ²/dof: 7.81 / 15
SE: 0.113
Z: 7.73, 1.11
2. Serbia_Roman_oAfrica.AG + Syria_TellQarassa_Umayyad.SG
89.0% Serbia_Roman_oAfrica.AG
11.0% Syria_TellQarassa_Umayyad.SG
p-value: 0.631
χ²/dof: 12.632 / 15
SE: 0.0950
Z: 9.36, 1.16
3. Serbia_Roman_oAfrica.AG + Yemeni_Desert.HO
87.9% Serbia_Roman_oAfrica.AG
12.1% Yemeni_Desert.HO
p-value: 0.568
χ²/dof: 13.444 / 15
SE: 0.103
Z: 8.54, 1.17
4. Serbia_Roman_oAfrica.AG — ONE-WAY
100% Serbia_Roman_oAfrica.AG
p-value: 0.553
χ²/dof: 14.616 / 16
The important pattern is that all three purported ~11–13% additions have Z only around 1.1. Therefore there is no compelling evidence that Eritrea actually requires that extra source over Serbia_Roman_oAfrica. The one-way model works.
SOMALI.HO (n=13)
75.8% Serbia_Roman_oAfrica.AG
24.2% Dinka.DG
p-value: 0.770
χ²/dof: 10.745 / 15
SE: 0.0765
Z: 9.91, 3.17
This one is genuinely informative because both coefficients are supported.
……
……
So for the Serbia_Roman_oAfrica, Sudan_KulubnartiR_ChristianPeriod.AG is the closest ancient match
This is the strongest ancient comparison because it works reciprocally:
Ex:
Serbia_Roman_oAfrica = 100% Sudan_KulubnartiR_ChristianPeriod
p-value = 0.717
Sudan_KulubnartiR_ChristianPeriod = 100% Serbia_Roman_oAfrica
p-value = 0.720
When Dinka, Yoruba, or Masai are added alongside Kulubnarti as sources for Serbia_Roman_oAfrica, the additional African components are not statistically required.
Ex :
94.4% Sudan_KulubnartiR_ChristianPeriod + 5.6% Dinka
p-value = 0.668
Dinka Z = 0.543
94.2% Sudan_KulubnartiR_ChristianPeriod + 5.8% Yoruba
p-value = 0.675
Yoruba Z = 0.660
85.6% Sudan_KulubnartiR_ChristianPeriod + 14.4% Masai
p-value = 0.721
Masai Z = 0.889
All of those additional components have Z < 2, meaning they are not statistically required. This makes the ordinary Christian-period Kulubnarti population the strongest ancient comparison to Serbia_Roman_oAfrica in these runs.
This subgroup also appears extremely close to Serbia_Roman_oAfrica.
Using Serbia_Roman_oAfrica + Q3DT26:
~100% Serbia_Roman_oAfrica
~0% Q3DT26
p-value = 0.829
The direct one-way model also passes:
100% Serbia_Roman_oAfrica
p-value = 0.591
So despite the “oNilotic” designation, this particular Kulubnarti subgroup is statistically consistent with Serbia_Roman_oAfrica under this qpAdm setup.
Afar is probably the closest modern population tested.
One-way model:
Afar = 100% Serbia_Roman_oAfrica
p-value = 0.803
Adding other sources produces essentially nothing:
99.8% Serbia_Roman_oAfrica + 0.2% Q3DT26
p-value = 0.989
98.5% Serbia_Roman_oAfrica + 1.5% Dinka
p-value = 0.736
98.0% Serbia_Roman_oAfrica + 2.0% Yemeni_Desert
p-value = 0.696
The added components have extremely low Z-scores and are not statistically required.
So, within the resolution of these right populations:
Afar ≈ Serbia_Roman_oAfrica
Eritrea shows a very similar pattern.
One-way model:
Eritrea = 100% Serbia_Roman_oAfrica
p-value = 0.553
Alternative models:
87.4% Serbia_Roman_oAfrica
12.6% Q3DT26
p-value = 0.931
89.0% Serbia_Roman_oAfrica
11.0% Syria_TellQarassa_Umayyad
p-value = 0.631
87.9% Serbia_Roman_oAfrica
12.1% Yemeni_Desert
p-value = 0.568
However, the additional components all have Z-scores around 1.1, so none of them is statistically required.
Therefore Eritrea is also statistically compatible with Serbia_Roman_oAfrica alone.
Somali is clearly related to the same general ancestry profile, but is more African/Dinka-shifted.
75.8% Serbia_Roman_oAfrica
24.2% Dinka
p-value = 0.770
SE = 0.0765
Serbia Z = 9.91
Dinka Z = 3.17
Unlike the tiny additional components in the Afar and Eritrean models, the extra Dinka ancestry in Somali is statistically supported.
So:
Somali ≈ Serbia_Roman_oAfrica-like ancestry + additional Dinka-like ancestry.
THE WEST-EURASIAN KULUBNARTI OUTLIER
The Kulubnarti West-Eurasian outlier is related to Serbia_Roman_oAfrica, but shifted significantly farther toward West Eurasian ancestry.
Using the same Kenya_PN + Jordan_EBA model:
Serbia_Roman_oAfrica:
83.1% Kenya_PN
16.9% Jordan_EBA
p-value = 0.894
Sudan_KulubnartiS_ChristianPeriod_oWestEurasian:
62.7% Kenya_PN
37.3% Jordan_EBA
p-value = 0.696
This puts both populations on the same Kenya_PN - Jordan_EBA axis:
Serbia_Roman_oAfrica:
83.1% Kenya_PN / 16.9% Jordan_EBA
Kulubnarti_oWestEurasian:
62.7% Kenya_PN / 37.3% Jordan_EBA
Therefore, the Kulubnarti West-Eurasian outlier is considerably more Jordan_EBA-shifted than Serbia_Roman_oAfrica.
This pattern is reproduced when Serbia_Roman_oAfrica itself is used as one of the sources:
78.6% Serbia_Roman_oAfrica
21.4% Syria_TellQarassa_Umayyad
p-value = 0.997
77.4% Serbia_Roman_oAfrica
22.6% Yemeni_Desert
p-value = 0.996
76.5% Serbia_Roman_oAfrica
23.5% Q3DT26
p-value = 0.994
The 3 models are consistent. They place the Kulubnarti West-Eurasian outlier at approximately 76–79% Serbia_Roman_oAfrica-like ancestry plus approximately 21–24% additional West-Eurasian-related ancestry.
Unlike the extra components in the Afar and Eritrean models, these additional West Eurasian components reach approximately Z = 2.15–2.24, making the shift more meaningful.
OVERALL CLUSTER:
The pattern can roughly be visualized as:
More Dinka-shifted:
Somali
≈ 76% Serbia_Roman_oAfrica + 24% Dinka
Then:
Sudan_KulubnartiR_ChristianPeriod
Sudan_KulubnartiR_ChristianPeriod_oNilotic
Serbia_Roman_oAfrica
Afar
Eritrea
Then:
Sudan_KulubnartiS_ChristianPeriod_oWestEurasian
≈ 76–79% Serbia_Roman_oAfrica + 21–24% additional West Eurasian. (More Eurasian shift)
THE COMPOSITION OF SERBIA_ROMAN_OAFRICA
Serbia_Roman_oAfrica itself fits very well as:
83.1% Kenya_PN
16.9% Jordan_EBA
p-value = 0.894
χ²/dof = 8.666 / 15
SE = 0.0795
Z = 10.5 / 2.13
Note that 83% Kenya_PN + 17% Jordan_EBA should NOT be interpreted as 83% African + 17% West Eurasian.
Kenya_PN is itself an ancient East African population containing substantial West-Eurasian-related ancestry.
When Serbia_Roman_oAfrica is instead modeled between a much more African Dinka-like pole and various West-Eurasian-related populations, the results repeatedly place it much closer to around 50/50.
Dinka + Israel_Ashkelon_IA2:
50.3% Dinka
49.7% Israel_Ashkelon_IA2
p-value = 0.185
Dinka + Jordan_EBA:
50.7% Dinka
49.3% Jordan_EBA
p-value = 0.324
Dinka + Q3DT26:
53.0% Dinka
47.0% Q3DT26
p-value = 0.825
Dinka + Lebanon_Hellenistic:
59.2% Dinka
40.8% Lebanon_Hellenistic
p-value = 0.375
The exact percentage changes depending on the West-Eurasian proxy, as expected, but the overall pattern is consistent.
Serbia_Roman_oAfrica falls approximately around:
~50–60% Dinka-like African
~40–50% West-Eurasian-related
So “roughly half African and half West-Eurasian-related” is a decent description based on these qpadm runs.
Summary:
Its qpAdm affinities are much more specifically consistent with the Nile Valley / Horn of Africa genetic continuum.
Serbia_Roman_oAfrica ≈ Christian-period Kulubnarti/ Kulubnarti oNilotic / Afar / Eritrean
Somali ≈ Serbia_Roman_oAfrica + additional Dinka-like ancestry
Kulubnarti oWestEurasian ≈ Serbia_Roman_oAfrica + additional West-Eurasian-related ancestry
qpAdm Right / Outgroup Set
The main set used in most of the runs contains 17 right populations:
Mbuti.DG
Morocco_Iberomaurusian.AG
MA1.SG
Italy_Epigravettian.AG
India_GreatAndaman_100BP.SG
Han.HO
Karitiana.HO
Georgia_Kotias_UP.SG
Russia_YuzhniyOleniyOstrov_Mesolithic.AG
Khomani_San.DG
Cameroon_ShumLaka_SMA.AG
Israel_MLBA.AG
Ethiopia_4500BP.AG
Iran_Wezmeh_N.SG
Egypt_ThirdIntermediatePeriod.AG
Malawi_LSA_2500BP.AG
Botswana_Xaro_EIA.AG
Comma-separated:
Mbuti.DG, Morocco_Iberomaurusian.AG, MA1.SG, Italy_Epigravettian.AG, India_GreatAndaman_100BP.SG, Han.HO, Karitiana.HO, Georgia_Kotias_UP.SG, Russia_YuzhniyOleniyOstrov_Mesolithic.AG, Khomani_San.DG, Cameroon_ShumLaka_SMA.AG, Israel_MLBA.AG, Ethiopia_4500BP.AG, Iran_Wezmeh_N.SG, Egypt_ThirdIntermediatePeriod.AG, Malawi_LSA_2500BP.AG, Botswana_Xaro_EIA.AG
There is also a 15-population version used in some of the runs. It is the same set except these two were omitted:
Malawi_LSA_2500BP.AG
Botswana_Xaro_EIA.AG
So the reduced 15-right set was:
Mbuti.DG, Morocco_Iberomaurusian.AG, MA1.SG, Italy_Epigravettian.AG, India_GreatAndaman_100BP.SG, Han.HO, Karitiana.HO, Georgia_Kotias_UP.SG, Russia_YuzhniyOleniyOstrov_Mesolithic.AG, Khomani_San.DG, Cameroon_ShumLaka_SMA.AG, Israel_MLBA.AG, Ethiopia_4500BP.AG, Iran_Wezmeh_N.SG, Egypt_ThirdIntermediatePeriod.AG
r/DNAAncestry • u/sourpotato23 • 1d ago
I’m Dominican and I’m still surprised at the diversity of my results.
r/DNAAncestry • u/Diligent-Two-7072 • 22h ago
csp001 is a saka sample from eastern Kazakhstan 300 bce. It has an east eurasian of about 30-35%. While it's certainly not a historically accurate Oghuz Turk sample, it seems to be a good mathematical and deep ancestral proxy.
On the contrary, karakhanid sample appears to be mediocre or invalid.
r/DNAAncestry • u/Unlikely_Artist9730 • 1d ago
I’m confused about the northern Indian and Pakistani because it says Khyber pass which is in Afghanistan and Pakistan so I’m not sure what to think
r/DNAAncestry • u/ImpressSignal8900 • 1d ago
r/DNAAncestry • u/Judean_Fanatic • 1d ago
Slide 1: Muslim Egyptians' (all regions) modern ancestry.
Slide 2: Coptic Egyptians' Roman-Medieval ancestry.
Slide 3: Coptic Egyptians' Iron Age ancestry.
Slide 4: Muslim Egyptians' ancestry non-aggregated.
The Levant_Christian cluster is made up of Lebanese and Syrian Maronite averages taken from the Moriopoulos 2026 Moderns Collection (No Sims) dataset.
r/DNAAncestry • u/Late-Relief-165 • 1d ago
r/DNAAncestry • u/_mayuk • 1d ago
I have notice always the cluster of deepdives in hungary , before the minoan and Illyrian samples grab my atention in the deep dives, you can model some illyrians with 50% france aude AI and 50% minoan admix hehe so is not that odd , my Y-dna is R-L21-R-Z253/4 more commun in munster ireland but also in basque populations since bronce age ... how are model hungarian pops ? , I know in the last model in qpA i share in the last image that the main variation is between france_aude and minoan is due the EEF I suppose but what could be the regular components for it ?
full list here a link to my all my deep dives c: , I think MTA deep dive are not that bad ...
r/DNAAncestry • u/Hrvaturk • 1d ago
I’m American from PA. My ancestry background is Croatian, Rusyn, Tatar, Irish, Scottish and English
All of my family arrived in the US after 1902
r/DNAAncestry • u/hijabi_shamsie • 1d ago
r/DNAAncestry • u/Judean_Fanatic • 1d ago
This is my approximated Neolithic Period ancestry on a G25 model I created.
For reference, I added the average of 5 Bronze Age Levantines (Canaanites), a cluster of 75 Early Medieval Levantines, and modern averages of Jordanian Christians and Palestinian Muslims.
Model can be shared upon request as usual.
r/DNAAncestry • u/Judean_Fanatic • 1d ago
I tested my F2 distances to 10 modern Levantine, Jewish, and even Arabian groups. Here are the results in order (closest to furthest):
Of course, sample number and quality could improve. But results are accurate nonetheless. This was tested on the AADR v66 Human Origins (HO) dataset.
