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Most Philipino Gedmatch results that doesn't seem to have South Asian admixture or very little, and when do score some South Asian-like component on Harappa, Dodecad or other calcs, they don't usually have Iran_N admixture (Baloch, Gedrosia, Caucasus, etc). I think the South Asian-like signal most Pinos score is something Negrito or local AASI-like affinity rather than actual Indian gene flow. Nevertheless, the following kits seem to have them.
I don't know where in the Philippines these kits are originally from, but they seem to come from a place that have recent Indian settlers (Sepoy soldiers) like Cainta in Rizal, Luzon or maybe they come from a region where there it preserved better South Asian admixture than the rest of the archipelago possibly in Visayas or in Mindanao which is closer to Indonesia and Malaysia (Borneo). Maybe its precolonial and before the arrival of Spaniards? There used to be Indianized Hindu Buddhist Kingdoms in the Philippines before Spanish colonization: https://www.aswangproject.com/unders...gy-indianized/
https://kreately.in/indian-imprints-...l-philippines/
https://twitter.com/porbotialora/sta...11385830621184
It's plausible that the Moros (Filipino Muslims) might have more and preserve South Asian admixture better than Filo (another term for Filipino) Christians because they never got colonized by the Spaniards. Moreover, they lived in the far south in Mindanao and surrounding islands like Sulu, which is closer to Indonesia and Malaysia.
If you remember that Vizayan sample on G25, he/she seems to have some Indian admixture including Iran_N+Steppe but doesn't score any Spanish admixture:
Target: Vizayan:GS000019970
Distance: 1.5678% / 0.01567765
75.4 Igorot
10.4 MYS_LN
4.8 S_AASI_Sim(Hakkipikki)
3.8 Papuan
2.4 Yamnaya_RUS_Samara
1.4 Han_Zhejiang
1.2 Spanish_Extremadura
0.6 TKM_Gonur1_BA
Anyway let's start...
1. This individual have the highest South Asian admixture I have seen among Filipinos. She lives in Guam which has a huge Pinoy immigrant population but seems to originally come from Zamboanga which is Mindanao, in the far south which is near Indonesia and Malaysia. I'm not sure if her admix is from recent Indian settlers or dated back to the precolonial times:
Admix Results (sorted):
# Population Percent
1 SE-Asian 51.25
2 NE-Asian 25.4
3 S-Indian 12.99
4 Baloch 4.5
5 Papuan 2.95
6 Caucasian 1
7 San 0.82
8 NE-Euro 0.48
9 American 0.32
10 E-African 0.16
11 Siberian 0.12
Spoiler!
2. Not sure where in the Phils she is from. But she has the second highest South Asian admix I have seen among Filipinos.
Admix Results (sorted):
# Population Percent
1 SE-Asian 55.53
2 NE-Asian 25.61
3 S-Indian 10.44
4 Papuan 3.38
5 Baloch 3.09
6 Beringian 0.49
7 Caucasian 0.45
8 NE-Euro 0.31
9 SW-Asian 0.26
10 San 0.25
11 American 0.1
12 Mediterranean 0.09
Spoiler!
3. Not sure where in the Philippines she is originally from (maybe somewhere like Visayas or Mindanao) but she has the third highest South Asian I have seen among Pinoys. Much less than the first two though.
Admix Results (sorted):
# Population Percent
1 SE-Asian 56.58
2 NE-Asian 28.56
3 S-Indian 6.56
4 Papuan 3.05
5 Baloch 1.36
6 SW-Asian 0.93
7 Siberian 0.8
8 NE-Euro 0.62
9 Pygmy 0.45
10 Beringian 0.41
11 E-African 0.27
12 San 0.22
13 Mediterranean 0.18
Spoiler!
4. Not sure where in the Philippines she is originally from (maybe somewhere like Visayas or Mindanao) but she has the fourth highest South Asian I have seen among Pinoys. Also much lower than the first two though.
Admix Results (sorted):
# Population Percent
1 SE-Asian 55.24
2 NE-Asian 31.69
3 S-Indian 6.15
4 Papuan 3.1
5 Baloch 1.75
6 Caucasian 1.09
7 Pygmy 0.47
8 Mediterranean 0.29
9 W-African 0.22
Single Population Sharing:
# Population (source) Distance
1 lahu (hgdp) 7.72
2 vietnamese (xing) 8.51
3 kinh (1000genomes) 8.51
4 dai-chinese (1000genomes) 14.58
5 dai (hgdp) 16.48
6 khmer-cambodian (xing) 17.21
7 thai (xing) 21.06
8 cambodian (hgdp) 26.25
9 singapore-malay (sgvp) 29.18
10 burmanese (chaubey) 30.39
11 miao (hgdp) 33.31
12 garo (chaubey) 33.46
13 khasi (chaubey) 34.75
14 singapore-chinese (sgvp) 35.3
15 she (hgdp) 37.57
16 chinese (xing) 37.78
17 han-chinese-south (1000genomes) 38.89
18 han (hgdp) 39.24
19 chinese-american (hapmap) 42.7
20 iban (xing) 42.71
Spoiler!
5. Also not sure where in the Phils she is from. Fifth highest South Asian I have seen among Pinoys.
Admix Results (sorted):
# Population Percent
1 SE-Asian 60.85
2 NE-Asian 27.53
3 S-Indian 5.17
4 Papuan 2.39
5 Baloch 1.39
6 Beringian 0.92
7 SW-Asian 0.65
8 American 0.43
9 Mediterranean 0.32
10 Pygmy 0.21
11 San 0.1
12 E-African 0.05
Spoiler!
6. Also don't know which region of the Philippines she is from.
Admix Results (sorted):
# Population Percent
1 SE-Asian 60.26
2 NE-Asian 27.28
3 S-Indian 4.55
4 Papuan 3.06
5 Siberian 1.67
6 Caucasian 1.59
7 Baloch 1.26
8 E-African 0.3
9 San 0.03
Spoiler!
7. I also don't know where in the Phils he is originally from.
Admix Results (sorted):
# Population Percent
1 SE-Asian 58.38
2 NE-Asian 31.82
3 S-Indian 3.46
4 Papuan 2.73
5 Baloch 1.34
6 Mediterranean 0.76
7 American 0.55
8 Beringian 0.39
9 San 0.25
10 Caucasian 0.19
11 Pygmy 0.09
12 SW-Asian 0.03
Spoiler!
8. Im also not certain about the origin of this Philippine individual.
Admix Results (sorted):
# Population Percent
1 SE-Asian 54.82
2 NE-Asian 35.29
3 S-Indian 3.52
4 Papuan 3.23
5 Caucasian 1.72
6 American 0.71
7 Siberian 0.3
8 SW-Asian 0.19
9 San 0.12
10 Pygmy 0.09
Single Population Sharing:
# Population (source) Distance
1 lahu (hgdp) 4.93
2 vietnamese (xing) 5.41
3 kinh (1000genomes) 7.63
4 dai-chinese (1000genomes) 14.95
5 dai (hgdp) 17.21
6 khmer-cambodian (xing) 21.02
7 thai (xing) 25.06
8 cambodian (hgdp) 29.64
9 miao (hgdp) 29.98
10 burmanese (chaubey) 30.06
11 singapore-chinese (sgvp) 31.99
12 singapore-malay (sgvp) 32.55
13 garo (chaubey) 32.96
14 she (hgdp) 34.29
15 chinese (xing) 34.54
16 han-chinese-south (1000genomes) 35.64
17 han (hgdp) 36.01
18 khasi (chaubey) 36.99
19 chinese-american (hapmap) 39.52
20 tujia (hgdp) 39.67
Spoiler!
9. He is originally from Manila so probably ethnic Tagalog.
Admix Results (sorted):
# Population Percent
1 SE-Asian 59.92
2 NE-Asian 28.6
3 S-Indian 3.18
4 Papuan 2.2
5 Baloch 2.03
6 Mediterranean 1.33
7 Siberian 1.1
8 Caucasian 1.08
9 Beringian 0.44
10 SW-Asian 0.12
Spoiler!
10. Also not sure where in the Philippines where she is from.
Admix Results (sorted):
# Population Percent
1 SE-Asian 58.16
2 NE-Asian 33.4
3 S-Indian 3.09
4 Siberian 1.5
5 Baloch 1.42
6 Papuan 1.12
7 Mediterranean 0.66
8 American 0.4
9 E-African 0.19
10 Beringian 0.05
11 Pygmy 0.01
Spoiler!
11. Also don't know her whereabouts in the Philippines.
Admix Results (sorted):
# Population Percent
1 SE-Asian 56.49
2 NE-Asian 32.67
3 S-Indian 2.92
4 Papuan 2.27
5 Baloch 1.72
6 Siberian 1.25
7 American 0.89
8 Pygmy 0.56
[B]9 SW-Asian 0.49
[/B]10 Caucasian 0.35
11 NE-Euro 0.29
12 San 0.11
Spoiler!
12. Don't know about the background of this Pinoy.
Admix Results (sorted):
# Population Percent
1 SE-Asian 56.63
2 NE-Asian 35.72
3 S-Indian 2.96
4 Papuan 2.74
5 NE-Euro 0.68
6 Baloch 0.55
7 Beringian 0.51
8 Caucasian 0.21
Spoiler!
13. This individual is originally from Morong in Rizal which is in Luzon. Not sure about the ethnicity but he is probably Tagalog.
Admix Results (sorted):
# Population Percent
1 SE-Asian 57.83
2 NE-Asian 28.95
3 Papuan 3.4
4 Baloch 2.82
5 S-Indian 2.78
6 NE-Euro 1.33
7 Mediterranean 0.99
8 E-African 0.81
9 SW-Asian 0.73
10 Pygmy 0.34
Spoiler!
14. Not sure where in the Philippines he is originally from.
Admix Results (sorted):
# Population Percent
1 SE-Asian 57.31
2 NE-Asian 30.36
3 Papuan 4.23
4 S-Indian 2.36
5 Baloch 1.18
6 Caucasian 1.17
7 Beringian 0.95
8 American 0.84
9 SW-Asian 0.61
10 Siberian 0.48
11 NE-Euro 0.34
12 Pygmy 0.1
13 San 0.07
Spoiler!
15. Also don't know her origin or whereabouts in the Phils.
Admix Results (sorted):
# Population Percent
1 SE-Asian 60.47
2 NE-Asian 29.8
3 Papuan 3.24
4 S-Indian 2.37
5 Beringian 0.96
6 SW-Asian 0.93
7 Baloch 0.74
8 Caucasian 0.73
9 American 0.52
10 San 0.13
11 Siberian 0.1
Spoiler!
There are probably some more Pino results that show signals of Indian admixture. I will post them later if I have time. Thoughts?
Last edited by Maguzanci; 11-27-2020 at 10:17 AM.
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Btw here is the Vizayan individual (unfortunately there is only Vizayan sample in the G25 dataset) that I briefly mentioned. Isn't it peculiar that the individual scores more Steppe than Spanish along with the AASI? Some type of North Indian-like admixture because the Steppe is higher than the Iran_N?
Target: Vizayan:GS000019970
Distance: 1.5678% / 0.01567765
75.4 Igorot
10.4 MYS_LN
4.8 S_AASI_Sim(Hakkipikki)
3.8 Papuan
2.4 Yamnaya_RUS_Samara
1.4 Han_Zhejiang
1.2 Spanish_Extremadura
0.6 TKM_Gonur1_BA
Compare to the Luzon individual (unfortunately also only one sample on G25) who have AASI but no Iran_N or Steppe, only very negligible Spanish signal.
Target: Luzon
Distance: 1.0948% / 0.01094789
49.0 TWN_Hanben
41.8 Igorot
4.8 MYS_LN
3.2 AASI_related_Sim
0.8 Papuan
0.4 Spanish_Extremadura
Or the Igorot tribe from Luzon who are basically pure Austronesian.
Target: Igorot
Distance: 3.1485% / 0.03148490
100.0 TWN_Hanben
I use three simulated AASI samples btw: the ones by Matt and Traject and another one by DMXX which he used the Hakkipikki to simulate them.
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Bump. Thoughts please? Opinions?
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It's interesting they have some Baloch. I mean "Baloch" component should have been proper West Eurasian. Dunno if they really got South Asian admixture. Do Onge or any Andamanese kit show up Baloch? Any1 knows any Onge, Jarawa or Andamanese kit?
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Sorry can you explain on the bolded part? Why aren't you sure if they really have South Asian admixture?
Here are some Andamanese results: they do show minor Baloch but I think its noise as they should not have any West Eurasian. Nevertheless, I still think the Baloch that the Philipino individuals are scoring is genuine as they also show signs of other West Eurasian such as Caucasian, NE Euro and SW Asian.
Jarawa
Admix Results (sorted):
# Population Percent
1 S-Indian 47.32
2 SE-Asian 23.92
3 Papuan 12.98
4 Siberian 4.76
5 NE-Asian 4.33
6 E-African 2.38
7 Beringian 1.95
8 American 1.19
9 Baloch 0.79
10 San 0.27
11 NE-Euro 0.1
Single Population Sharing:
# Population (source) Distance
1 onge (reich) 8.49
2 great-andamanese (reich) 11.4
3 juang (chaubey) 20.49
4 bonda (chaubey) 21.2
5 kharia (chaubey) 22.65
6 savara (chaubey) 23.19
7 ho (chaubey) 23.9
8 sahariya (reich) 23.99
9 kharia (reich) 24.04
10 santhal (reich) 27.55
11 asur (chaubey) 27.8
12 khasi (chaubey) 27.89
13 gond (metspalu) 30.25
14 nihali (metspalu) 30.71
15 satnami (reich) 31.93
16 tharu (reich) 32.63
17 bengali (harappa) 32.88
18 chenchu (reich) 34.17
19 sri-lankan (harappa) 36.95
20 kurumba (reich) 37.03
Mixed Mode Population Sharing:
# Primary Population (source) Secondary Population (source) Distance
1 91% onge (reich) + 9% samoan (xing) @ 5.71
2 91% onge (reich) + 9% tongan (xing) @ 5.72
3 92.8% onge (reich) + 7.2% iban (xing) @ 6.38
4 91.5% onge (reich) + 8.5% singapore-malay (sgvp) @ 6.62
5 92% onge (reich) + 8% cambodian (hgdp) @ 6.91
6 91.3% onge (reich) + 8.7% thai (xing) @ 7.13
7 92.6% onge (reich) + 7.4% khmer-cambodian (xing) @ 7.45
8 95.6% onge (reich) + 4.4% melanesian (hgdp) @ 7.5
9 95.3% onge (reich) + 4.7% dai (hgdp) @ 7.83
10 88.4% great-andamanese (reich) + 11.6% tongan (xing) @ 7.83
11 95.6% onge (reich) + 4.4% dai-chinese (1000genomes) @ 7.92
12 96.3% onge (reich) + 3.7% aus (reich) @ 7.93
13 97% onge (reich) + 3% nganassan (rasmussen) @ 7.94
14 97.5% onge (reich) + 2.5% papuan (hgdp) @ 7.97
15 61.6% paniya (chaubey) + 38.4% tongan (xing) @ 7.99
16 96.5% onge (reich) + 3.5% ket (rasmussen) @ 8.04
17 88.7% great-andamanese (reich) + 11.3% samoan (xing) @ 8.06
18 96.5% onge (reich) + 3.5% selkup (rasmussen) @ 8.06
19 97.1% onge (reich) + 2.9% koryak (rasmussen) @ 8.08
20 96.3% onge (reich) + 3.7% kinh (1000genomes) @ 8.13
Andamanese:
Admix Results (sorted):
# Population Percent
1 S-Indian 46.64
2 SE-Asian 23.74
3 Papuan 13.01
4 Siberian 5.83
5 NE-Asian 4.54
6 E-African 1.91
7 American 1.22
8 Baloch 0.94
9 NE-Euro 0.65
10 Pygmy 0.63
11 Beringian 0.47
12 SW-Asian 0.28
13 San 0.14
Single Population Sharing:
# Population (source) Distance
1 onge (reich) 8.72
2 great-andamanese (reich) 11.28
3 juang (chaubey) 21.09
4 bonda (chaubey) 21.81
5 kharia (chaubey) 23.28
6 savara (chaubey) 23.73
7 sahariya (reich) 24.37
8 ho (chaubey) 24.54
9 kharia (reich) 24.69
10 khasi (chaubey) 27.37
11 santhal (reich) 28.15
12 asur (chaubey) 28.38
13 gond (metspalu) 30.55
14 nihali (metspalu) 31.13
15 satnami (reich) 32.15
16 tharu (reich) 32.71
17 bengali (harappa) 32.72
18 chenchu (reich) 34.42
19 sri-lankan (harappa) 36.85
20 chenchu (metspalu) 37.21
Mixed Mode Population Sharing:
# Primary Population (source) Secondary Population (source) Distance
1 90.6% onge (reich) + 9.4% tongan (xing) @ 5.75
2 90.6% onge (reich) + 9.4% samoan (xing) @ 5.76
3 92.6% onge (reich) + 7.4% iban (xing) @ 6.53
4 91.2% onge (reich) + 8.8% singapore-malay (sgvp) @ 6.72
5 91.6% onge (reich) + 8.4% cambodian (hgdp) @ 7.01
6 90.7% onge (reich) + 9.3% thai (xing) @ 7.2
7 88.1% great-andamanese (reich) + 11.9% tongan (xing) @ 7.41
8 92.1% onge (reich) + 7.9% khmer-cambodian (xing) @ 7.55
9 95.3% onge (reich) + 4.7% melanesian (hgdp) @ 7.59
10 88.4% great-andamanese (reich) + 11.6% samoan (xing) @ 7.67
11 95.8% onge (reich) + 4.2% nganassan (rasmussen) @ 7.67
12 95.1% onge (reich) + 4.9% ket (rasmussen) @ 7.84
13 95.1% onge (reich) + 4.9% selkup (rasmussen) @ 7.89
14 94.9% onge (reich) + 5.1% dai (hgdp) @ 7.94
15 95.7% onge (reich) + 4.3% dolgan (rasmussen) @ 7.95
16 96.1% onge (reich) + 3.9% evenki (rasmussen) @ 7.95
17 95.1% onge (reich) + 4.9% dai-chinese (1000genomes) @ 8.03
18 95.4% onge (reich) + 4.6% yukaghir (rasmussen) @ 8.04
19 96.1% onge (reich) + 3.9% yakut (hgdp) @ 8.05
20 95.9% onge (reich) + 4.1% aus (reich) @ 8.06
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Some of these calculator components are misleading. I thought some Onge could score Baloch as well but it seems Baloch is proper West Eurasian component. So, I guess Filipinos got some South Asian admixes as well over their ENA/AASI like admix. Something very low Baloch high AASI folks must have been widespread who supplied the South Asian admixes to Nepalese Tibeto-Burmese as well some SE-Asians like your Filipinos as they seem to score Gond or Sahariya like admix.
They model very well with AASI shifted South Asians like Roopkund_A which is closest to Punjabi Lahore.
Target: Magar
Distance: 1.2147% / 0.01214686
48.6 NPL_Chokhopani_2700BP
17.4 NPL_Mebrak_2125BP
16.0 IND_Roopkund_A
15.4 NPL_Samdzong_1500BP
2.6 LAO_LN_BA
Distance to: IND_Roopkund_A
0.01493702 Punjabi_Lahore
0.01885884 Kol
0.01938178 Gujarati
0.02084556 Kanjar
0.02526577 Iyer
0.02540338 Kamboj_o
0.02699501 Dharkar
0.03154340 Brahmin_West_Bengal
0.03188724 Velamas
0.03274470 Kshatriya
0.03309667 Brahmin_Tamil_Nadu
0.03986770 Uttar_Pradesh
0.04346055 Yadava
0.04591306 Brahmin_Uttar_Pradesh
0.04699254 Dusadh
0.04820678 Piramalai
0.04948427 Kurumba
0.05073985 Maratha
0.05187266 PAK_Saidu_Sharif_H_o
0.05304287 Bengali_Bangladesh
0.05664121 Chamar
0.06174465 Gupta
0.06381643 PAK_Katelai_LBA
0.06434351 Chenchu
0.06488818 Brahmin_Gujarat
Last edited by Kaazi; 11-27-2020 at 05:33 PM.
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Yes its very misleading. Would be great if I can get these Philipino gedmatch kit users to get G25 done just to be sure .
Nepalese Tibeto-Burmans also have high AASI and very low Baloch? True, but Gond or Sahariya are basically adivasi tribals and I don't think there were such tribals among Indian traders and settlers in SE Asia as the tribals seem pretty isolated from the mainstream society. So it's really strange if they received the South Asian from a Gond or Sahariya-like populaiton.
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SE Asians and Andamanese share very old Ancestral South Eurasian. If you are looking for evidence of more recent S Asian admixture into Filipinos Gedmatch is not the right tool. G25 is the worst tool in the world for ancestry from the last 2000 years even much worse than Gedmatch because it does not cluster on more recent derived alleles.
The best tool for you to do this besides IBD is to have your Filipino subject genotyped WGS such as by Dante Labs because Dante genotypes only derived alleles (they don't report positions for which you are reference (ancestral) x2)
For example a Kurdish relative of mine did 23andme and Dante WGS. When he used his Dante WGS data at Gedmatch the results were significantly different and they showed alot more Asian admixture (last 2000 years) than his 23andme results at Gedmatch.
Muzh ba staso la tyaro tsakha ra wubaasu
[IMG][/IMG]
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