TLDR: ONLY groups which I have data for were added to the map. If you don’t see your group, it means I either don’t have data for it, or haven’t completed enough runs for it. This is a compilation of qpAdm runs for populations from the Levant and surrounding regions. A few more groups have been added compared with the first map. For the (n=1) samples they were determined to be within their designated population set before completing the runs.

Dataset:
https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/FFIDCW
Data used is from AADR+Human Origins panel+Individual samples

SYRIAN.HO (n=8)
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, 0.00892
Z-scores: 14.5, 4.15, 8.72

This is a strong model, with all three components statistically supported. Lebanon_Phoenician represents the main Levantine ancestry, while Armenia_Sarukhan_Early_Iron_Age represents additional Caucasus/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 components have standard errors close to 0.05, so their exact proportions should be treated as approximate.

DRUZE.HO (n=39)
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, 0.00803
Z-scores: 18.0, 4.84, 2.74
This is an excellent statistical fit. The Druze are modeled as mostly Levantine, with a substantial Caucasus/eastern Anatolian-related shift and a very small African-related component. All three components are statistically supported.

ASSYRIAN.HO (n=10)
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
SE: 5.64%, 5.64%
Z-scores: 13.3, 4.45
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% ancestry from Sasanian-era Bahrain.

LEBANESE_MUSLIM.HO (n=11)
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, 0.00913
Z-scores: 40.4, 3.95, 3.14
This is a strong and well-resolved model. Lebanon_Phoenician 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 (n=9)
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, 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/Caucasus-related shift. Its Z-score of 2.13 is only just above the usual cutoff, so the existence of a small secondary component is supported, but the exact 5% estimate should be treated cautiously.

PALESTINIAN.HO (n=34)
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, 0.00823
Z-scores: 43.1, 2.54, 8.32
This is a very strong model, with an excellent p-value, low chi-square, and all three components statistically supported. Palestinians are modeled as mostly Levantine, with smaller northern/Caucasus-shifted and African-related components. The Sarmatian-related component has the weakest Z-score, but it still passes the usual Z = 2 threshold.

SAMARITAN.DG (n=1)
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-period Lebanese population.

JORDANIAN.HO (n=10)
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, 0.00899
Z-scores: 39.0, 3.58, 13.6
This is an extremely strong model statistically. Jordanians are modeled as mostly Levantine, with a smaller northern/Caucasus-shifted component and a more substantial African-related component than in the Lebanese or Druze models. Dinka should be understood as the African proxy used by the model, not as evidence of direct ancestry specifically from modern Dinka people.

SAUDI.HO (n=5)
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. The Dinka component has a Z-score of 7.21.

BEDOUINB.HO (n=19)
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. The Dinka component has a Z-score of 7.86.

BEDOUINA.HO (n=25)
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
Z-scores:
Lebanon_Phoenician: 10.6
Syria_TellQarassa_Umayyad: 9.64
Dinka: 25.9
Kazakhstan_Sarmatian: 2.88
All four components are statistically supported.
This model passes and suggests that BedouinA can be modeled primarily as Levantine ancestry represented by Phoenician Lebanon and Umayyad-period Tell Qarassa, together with approximately 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.
Both BedouinA and BedouinB are genetic clusters consisting of Bedouins from unspecified tribes in the Negev Desert. BedouinA has a more northern genetic shift, while BedouinB has a stronger southern shift and clusters more closely with the Saudi average.

EGYPTIAN_COPT (n=1)
Alternative 2-way model:
97.3% SFI-43.SG
SE: 1.92%
Z: 50.7
2.7% Dinka.DG
SE: 1.92%
Z: 1.42
p-value: 0.592
χ²/dof: 11.227 / 13
SNPs: 661,321
Although the overall model fits extremely well, the estimated 2.7% Dinka component is not statistically supported (Z = 1.42). Therefore, this model does not provide strong evidence that Dinka-related ancestry is required.

EGYPTIANA.HO (n=7)
92.9% SFI-43.SG
SE: 1.57%
Z: 59.0
7.1% Dinka.DG
SE: 1.57%
Z: 4.52
p-value: 0.345
χ²/dof: 14.419 / 13
SNPs: 579,720
This is a strong passing model. The 7.1% Dinka-related component is statistically supported.

EGYPTIANB.HO (n=4)
91.6% SFI-43.SG
SE: 1.61%
Z: 56.9
8.4% Dinka.DG
SE: 1.61%
Z: 5.20
p-value: 0.594
χ²/dof: 11.204 / 13
SNPs: 579,720
This is an excellent-fitting model, with the 8.4% Dinka-related component strongly supported.

EGYPTIAN.HO (n=8)
86.7% SFI-43.SG
SE: 1.50%
Z: 57.7
13.3% Dinka.DG
SE: 1.50%
Z: 8.83
p-value: 0.412
χ²/dof: 13.470 / 13
SNPs: 579,720
This is also a strong passing model. The 13.3% Dinka-related component is very strongly supported.

SYRIAN_JEW (n=1)
4-way model:
45.0% Italy_Imperial_C6.SG
SE: 9.75%
Z: 4.62
26.4% Bahrain_LTylos_Sasanian.SG
SE: 11.2%
Z: 2.37
20.0% Israel_Akhziv_Phoenician.AG
SE: 8.88%
Z: 2.25
8.6% CanaryIslands_Guanche.SG
SE: 3.58%
Z: 2.38
p-value: 0.182
χ²/dof: 12.581 / 9
SNPs: 295,151
Of the Syrian Jewish models tested, this model has the highest p-value at 0.182. All four components also have Z-scores above 2.
The recurring pattern across the models is substantial ancestry represented by Roman/Republican Italian-related and Bahrain Late Tylos/Sasanian-related sources. When a Levantine source is introduced directly, Israel_Akhziv_Phoenician contributes approximately 20–24% and remains statistically supported (Z = 2.25–2.66).
The 4-way model additionally identifies 8.6% Guanche-related ancestry, which may be better interpreted as a North African-related signal rather than literal ancestry from the Canary Islands.

CYPRIOT.HO (n=8)
Best model:
100% @R126.SG
p-value: 0.592
χ²/dof: 11.222 / 13
SNPs: 579,720
This is the strongest and most parsimonious model in the batch. Cypriot.HO is statistically consistent with being modeled entirely by @R126.SG under this outgroup set, with a good p-value and no additional ancestry source required. Because the one-way model already passes comfortably, qpAdm does not statistically require a second source.

PALESTINIAN_CHRISTIAN (n=1)
100.0% Lebanon_Hellenistic.SG
p-value: 0.363
χ²/dof: 12.007 / 11
SNPs: 412,920
This is a passing one-source model. Palestinian_Christian is statistically consistent with Lebanon_Hellenistic.SG relative to the selected outgroups. As with other one-way qpAdm models, the 100% result should be interpreted as statistical consistency with the proxy rather than literal complete descent from that sampled population.

NOTES ON THE SOURCE POPULATIONS

Lebanon_Phoenician (500–300 BCE) represents the main Levantine-related ancestry in many of these models. It is an average of Lebanon_Phoenician samples.

Kazakhstan_Sarmatian_IA (500–300 BCE) represents a more northern Steppe/Caucasus-shifted element. It should not necessarily be interpreted as literal Sarmatian ancestry.

Dinka represents African-related ancestry in these models and should not necessarily be interpreted as direct ancestry specifically from modern Dinka people.

Armenia_Sarukhan_EIA represents an Armenian/Caucasus or eastern Anatolian-related ancestry component.

Canary_Islands_Guanche = clusters with North Africans
Bahrain_LTylos_Sasanian = clusters with Mesopotamians
R126 = pan- Eastern Mediterranean ancestry

SFI-43 is an ancient Egyptian-related sample found in the Lebanon
Syria_TellQarassa_Umayyad = clusters with Peninsular Arabians

Georgia_Digomi_IA.SG = clusters with Caucasus
Iran_DinkhaTepe_BA_IA_1.AG = clusters with Mesopotamians

Italy_Imperial_C6 = Italic+Anatolian. Roughly the mix found during the Roman Era in Southern Italy and the Greek Islands

Lebanon_Hellenistic, dating to around 200 BCE, has broadly similar ancestry to Lebanon_Phoenician but comes from a later historical period.

IMPORTANT NOTE
These are qpAdm proxy models. The source labels should not necessarily be interpreted as literal direct ancestral populations. Instead, they represent ancestry streams or genetic proxies that successfully model the target populations relative to the particular set of outgroups used in each analysis.

TLDR: Compilation of qpAdm models for modern Southeast Asian and Island Southeast Asian populations. The information is based on qpadm runs from twitter user @matchawang_ and outgroups based on this study - https://www.cell.com/iscience/fulltext/S2589-0042(26)01349-0

Cambodian.DG (n=9) — 4-way model

17.8% Taiwan_Hanben_IA.AG
SE: 4.24% | Z: 4.21

59.4% Laos_LN_BA.SG
SE: 4.07% | Z: 14.6

15.8% China_YR_LN.SG
SE: 3.30% | Z: 4.79

7.0% Iran_ShahrISokhta_BA2.AG
SE: 0.844% | Z: 8.23

p-value: 0.302
χ²/dof: 8.359 / 7
SNPs: 1,878,396
Fit: Excellent

Mon.HO (n=10) — 4-way model

11.5% Taiwan_Hanben_IA.AG
SE: 3.38% | Z: 3.40

40.8% Laos_LN_BA.SG
SE: 3.28% | Z: 12.4

35.6% China_YR_LN.SG
SE: 2.71% | Z: 13.1

12.1% Iran_ShahrISokhta_BA2.AG
SE: 0.803% | Z: 15.1

p-value: 0.100
χ²/dof: 12.018 / 7
SNPs: 579,720
Fit: Good

Nyah_Kur.HO (n=10) — 4-way model

14.6% Taiwan_Hanben_IA.AG
SE: 4.59% | Z: 3.17

65.3% Laos_LN_BA.SG
SE: 4.49% | Z: 14.5

11.9% China_YR_LN.SG
SE: 3.54% | Z: 3.37

8.2% Iran_ShahrISokhta_BA2.AG
SE: 0.973% | Z: 8.42

p-value: 0.357
χ²/dof: 7.727 / 7
SNPs: 579,720
Fit: Excellent

Karen_Sgaw.HO (n=10) — 2-way model

61.0% Laos_LN_BA.SG
SE: 2.61% | Z: 23.4

39.0% China_Upper_YR_LN.SG
SE: 2.61% | Z: 14.9

p-value: 0.625
χ²/dof: 7.121 / 9
SNPs: 579,720
Fit: Excellent

Maniq.HO (n=9) — 2-way model

40.2% Laos_LN_BA.SG
SE: 2.43% | Z: 16.6

59.8% Laos_Hoabinhian.SG
SE: 2.43% | Z: 24.6

p-value: 0.361
χ²/dof: 9.876 / 9
SNPs: 579,720
Fit: Excellent

Lawa.HO (n=10) — 2-way model

66.5% Laos_LN_BA.SG
SE: 2.66% | Z: 25.0

33.5% China_Upper_YR_LN.SG
SE: 2.66% | Z: 12.6

p-value: 0.772
χ²/dof: 5.680 / 9
SNPs: 579,720
Fit: Excellent

Ilocano.HO (n=2) — 2-way model

95.8% Taiwan_Hanben_IA.AG
SE: 1.26% | Z: 75.9

4.2% Laos_Hoabinhian.SG
SE: 1.26% | Z: 3.33

p-value: 0.331
χ²/dof: 10.243 / 9
SNPs: 579,720
Fit: Excellent

Visayan.HO (n=4) — 3-way model

81.4% Taiwan_Hanben_IA.AG
SE: 2.58% | Z: 31.6

12.6% Laos_Hoabinhian.SG
SE: 1.07% | Z: 11.8

5.9% China_YR_LN.SG
SE: 2.58% | Z: 2.29

p-value: 0.332
χ²/dof: 9.124 / 8
SNPs: 579,720
Fit: Excellent

Tagalog.HO (n=5) — 4-way model

77.3% Taiwan_Hanben_IA.AG
SE: 3.44% | Z: 22.5

7.4% Laos_Hoabinhian.SG
SE: 1.54% | Z: 4.80

10.8% China_YR_LN.SG
SE: 3.37% | Z: 3.21

4.5% Spanish.DG
SE: 0.815% | Z: 5.55

p-value: 0.0811
χ²/dof: 11.244 / 6
SNPs: 579,720
Fit: Good

Murut.HO (n=10) — 2-way model

76.4% Taiwan_Hanben_IA.AG
SE: 2.77% | Z: 27.6

23.6% Laos_LN_BA.SG
SE: 2.77% | Z: 8.54

p-value: 0.137
χ²/dof: 13.611 / 9
SNPs: 579,720
Fit: Good

Dusun.DG (n=2) — 2-way model

79.0% Taiwan_Hanben_IA.AG
SE: 3.68% | Z: 21.5

21.0% Laos_LN_BA.SG
SE: 3.68% | Z: 5.72

p-value: 0.845
χ²/dof: 4.880 / 9
SNPs: 1,878,396
Fit: Excellent

Indonesia_Tanimbar_Tumbur.DG (n=1) — 2-way model

59.9% Taiwan_Hanben_IA.AG
SE: 1.68% | Z: 35.7

40.1% Papuan.DG
SE: 1.68% | Z: 23.9

p-value: 0.401
χ²/dof: 9.405 / 9
SNPs: 1,878,396
Fit: Excellent

Indonesia_Tanimbar_Makatian.DG (n=1) — 2-way model

57.1% Taiwan_Hanben_IA.AG
SE: 1.73% | Z: 33.0

42.9% Papuan.DG
SE: 1.73% | Z: 24.8

p-value: 0.415
χ²/dof: 9.247 / 9
SNPs: 1,878,396
Fit: Excellent

Indonesia_Tanimbar_Fordata.DG (n=1) — 2-way model

57.3% Taiwan_Hanben_IA.AG
SE: 1.83% | Z: 31.2

42.7% Papuan.DG
SE: 1.83% | Z: 23.3

p-value: 0.390
χ²/dof: 9.532 / 9
SNPs: 1,878,396
Fit: Excellent

Indonesia_Sumatra_Toba.DG (n=7) — 4-way model

59.8% Taiwan_Hanben_IA.AG
SE: 3.05% | Z: 19.6

23.7% Laos_LN_BA.SG
SE: 3.32% | Z: 7.15

7.7% Laos_Hoabinhian.SG
SE: 1.68% | Z: 4.57

8.7% Iran_ShahrISokhta_BA2.AG
SE: 1.01% | Z: 8.66

p-value: 0.0538
χ²/dof: 13.858 / 7
SNPs: 1,878,396
Fit: Good

Indonesia_Sulawesi_Mandar.DG (n=6) — 3-way model

75.4% Taiwan_Hanben_IA.AG
SE: 2.58% | Z: 29.2

13.2% Laos_LN_BA.SG
SE: 2.84% | Z: 4.65

11.4% Papuan.DG
SE: 0.996% | Z: 11.4

p-value: 0.291
χ²/dof: 9.640 / 8
SNPs: 1,878,396
Fit: Excellent

Indonesia_Sulawesi_Kajang.DG (n=6) — 3-way model

71.7% Taiwan_Hanben_IA.AG
SE: 2.58% | Z: 27.8

14.2% Laos_LN_BA.SG
SE: 2.86% | Z: 4.98

14.1% Papuan.DG
SE: 0.962% | Z: 14.7

p-value: 0.0796
χ²/dof: 14.084 / 8
SNPs: 1,878,396
Fit: Good

Indonesia_Nias_Hilitobara.DG (n=8) — 3-way model

89.7% Taiwan_Hanben_IA.AG
SE: 2.78% | Z: 32.2

8.5% Laos_LN_BA.SG
SE: 3.29% | Z: 2.59

1.8% Laos_Hoabinhian.SG
SE: 0.992% | Z: 1.80

p-value: 0.0697
χ²/dof: 14.495 / 8
SNPs: 1,878,396
Fit: Good

Note: the Laos_Hoabinhian.SG component has Z = 1.80, below the Z ≥ 2 threshold shown in the run.

Indonesia_Nias_Gomo.DG (n=7) — 2-way model

85.3% Taiwan_Hanben_IA.AG
SE: 2.83% | Z: 30.2

14.7% Laos_LN_BA.SG
SE: 2.83% | Z: 5.20

p-value: 0.620
χ²/dof: 7.164 / 9
SNPs: 1,878,396
Fit: Excellent

Indonesia_Mentawai.DG (n=10) — 2-way model

82.1% Taiwan_Hanben_IA.AG
SE: 2.90% | Z: 28.3

17.9% Laos_LN_BA.SG
SE: 2.90% | Z: 6.17

p-value: 0.501
χ²/dof: 8.330 / 9
SNPs: 1,878,396
Fit: Excellent

Indonesia_Lembata_TimurKadakewa.DG (n=4) — 4-way model

43.0% Taiwan_Hanben_IA.AG
SE: 2.91% | Z: 14.8

11.3% Laos_LN_BA.SG
SE: 3.34% | Z: 3.39

8.8% Laos_Hoabinhian.SG
SE: 3.23% | Z: 2.73

36.9% Papuan.DG
SE: 3.33% | Z: 11.1

p-value: 0.228
χ²/dof: 9.365 / 7
SNPs: 1,878,396
Fit: Excellent

Indonesia_Lembata_Waipukang.DG (n=3) — 2-way model

53.9% Taiwan_Hanben_IA.AG
SE: 1.12% | Z: 48.0

46.1% Papuan.DG
SE: 1.12% | Z: 41.0

p-value: 0.124
χ²/dof: 13.955 / 9
SNPs: 1,878,396
Fit: Good

Indonesia_Kei_Ohoidertutu.DG (n=2) — 2-way model

53.6% Taiwan_Hanben_IA.AG
SE: 1.21% | Z: 44.1

46.4% Papuan.DG
SE: 1.21% | Z: 38.2

p-value: 0.703
χ²/dof: 6.368 / 9
SNPs: 1,878,396
Fit: Excellent

Indonesia_Kei_Waur.DG (n=2) — 2-way model

48.7% Taiwan_Hanben_IA.AG
SE: 1.29% | Z: 37.8

51.3% Papuan.DG
SE: 1.29% | Z: 39.8

p-value: 0.170
χ²/dof: 12.842 / 9
SNPs: 1,878,396
Fit: Good

Indonesia_Kei_Faan.DG (n=2) — 2-way model

52.3% Taiwan_Hanben_IA.AG
SE: 1.35% | Z: 38.7

47.7% Papuan.DG
SE: 1.35% | Z: 35.2

p-value: 0.561
χ²/dof: 7.737 / 9
SNPs: 1,878,396
Fit: Excellent

Indonesia_Java_Dieng.DG (n=7) — 3-way model

33.7% Taiwan_Hanben_IA.AG
SE: 4.15% | Z: 8.12

62.5% Laos_LN_BA.SG
SE: 4.77% | Z: 13.1

3.9% Laos_Hoabinhian.SG
SE: 1.43% | Z: 2.70

p-value: 0.256
χ²/dof: 10.127 / 8
SNPs: 1,878,396
Fit: Excellent

Indonesia_Flores_Bere.DG (n=3) — 3-way model

41.6% Taiwan_Hanben_IA.AG
SE: 3.20% | Z: 13.0

30.0% Laos_LN_BA.SG
SE: 3.73% | Z: 8.04

28.4% Papuan.DG
SE: 1.32% | Z: 21.6

p-value: 0.183
χ²/dof: 11.348 / 8
SNPs: 1,878,396
Fit: Good

Indonesia_Flores_Bena.DG (n=12) — 4-way model

38.0% Taiwan_Hanben_IA.AG
SE: 2.42% | Z: 15.7

19.4% Laos_LN_BA.SG
SE: 2.74% | Z: 7.09

9.3% Laos_Hoabinhian.SG
SE: 2.91% | Z: 3.19

33.3% Papuan.DG
SE: 2.85% | Z: 11.7

p-value: 0.199
χ²/dof: 9.816 / 7
SNPs: 1,878,396
Fit: Good

Indonesia_Borneo_Maanyan.DG (n=7) — 3-way model

59.2% Taiwan_Hanben_IA.AG
SE: 3.11% | Z: 19.0

37.7% Laos_LN_BA.SG
SE: 3.61% | Z: 10.4

3.1% Laos_Hoabinhian.SG
SE: 1.11% | Z: 2.83

p-value: 0.349
χ²/dof: 8.920 / 8
SNPs: 1,878,396
Fit: Excellent

Indonesia_Flores_Cibol.DG (n=13) — 4-way model

40.1% Taiwan_Hanben_IA.AG
SE: 2.62% | Z: 15.3

31.1% Laos_LN_BA.SG
SE: 2.99% | Z: 10.4

5.5% Laos_Hoabinhian.SG
SE: 2.65% | Z: 2.08

23.2% Papuan.DG
SE: 2.73% | Z: 8.51

p-value: 0.264
χ²/dof: 8.842 / 7
SNPs: 1,878,396
Fit: Excellent

Indonesia_Bali_Gadon.DG (n=1) — 3-way model

36.3% Taiwan_Hanben_IA.AG
SE: 6.18% | Z: 5.88

56.2% Laos_LN_BA.SG
SE: 7.14% | Z: 7.86

7.5% Laos_Hoabinhian.SG
SE: 2.10% | Z: 3.59

p-value: 0.326
χ²/dof: 9.199 / 8
SNPs: 1,878,396
Fit: Excellent

Note: the displayed run flags at least one source because the Taiwan_Hanben_IA.AG and Laos_LN_BA.SG standard errors exceed 5%.

Notes

The map/compilation uses the 2-way Ilocano.HO model above. An alternative 3-way Ilocano model also passed overall (p=0.346; χ²/dof=8.953/8), but it produced a negative China_YR_LN.SG coefficient (-4.5%, Z=-1.24), so it was not used in the final compilation.