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Tsakhur
08-17-2020, 06:22 AM
Sorry for asking this but I am pretty much a novice in African population genetics. I know a lot more about the basics of SE Asian genetics as I from that region myself.

I am eager to figure out the percentage of African vs West Eurasian genetic contributions/ancestries in East African populations. From my vague and layman understanding, the West Eurasian ancestry is East Africa is primarily Levant_Neolithic/SW Asian-related and the African ancestries are predominantly Nilotic, Cushitic, Bantu/Niger-Congo and some Omotic or Hadza-related stuff?

I want to know what ancient pops should I used to determine the amount of West Eurasian and African genetic proportions in East Africans especially the non-Horner ones.

Can anyone help or give me suggestions please?

I want to compare and figure out who possessed more West Eurasian ancestries: non-Horner East Africans or SE Asians. SE Asians are predominantly Dai (Southern Chinese rice-farmer)/Taiwanese Aborigines+Negrito/Hoabinhnian+South Asian (Iran Neolithic West Eurasian+AASI+some Steppe type West Eurasian)+Oceanian/Papuan+additional West Asian or European (mainly in the case of some Muslim SE Asians and Filipinos)/Han admixture (from recent Chinese migrations, specially in the case of Thailand).


Edit: yes, I am utilizing G25 for these models.

drobbah
08-17-2020, 06:55 AM
If you are using G25 for SE Africans it's best to use Natufian and also Tur_Barcin (ANF) or Levant_N since it's a combination of both.I would assume SE Africans who are Cushitic admixed excluding the Iraqw(they are cushites) probably have more West Eurasian ancestry than the average Malay or Filipino

Tsakhur
08-17-2020, 07:34 AM
If you are using G25 for SE Africans it's best to use Natufian and also Tur_Barcin (ANF) or Levant_N since it's a combination of both.I would assume SE Africans who are Cushitic admixed excluding the Iraqw(they are cushites) probably have more West Eurasian ancestry than the average Malay or Filipino

Yes I am utilizing G25. What specific Levant Neolithic population should I used: Levant_JOR_MBA, Levant_PPNB or Levant_Megiddo_IA, etc?

Also is it suitable to utilize UG_Munsa_500BP, COG_NgongoMbata, Dinka, ETH_4500_BP and Bedzan as African source populations?

Do you know if the Luo, Luhya, Bantu_Kenya and Bantu S.E., Hadza Cushitic admixed or not?

I believe your assumption is correct regarding Cushitic admixed SE Asians being more Western than the average Malay or Filipino. Nonetheless, I believe that some Thai G25 samples have similar amounts of West Eurasian ancestry to the Sengwer (are they also Cushitic mixed?).

I feel that the Indian/South Asian ancestry in SE Asia is a bit analogous to the Cushitic ancestry in non-Horner SE Africa.

Im not sure if Burma and Thailand has similar amounts of West Eurasian ancestry to Kenya and Tanzania or less, but it would be intriguing and fun to determine this.

drobbah
08-17-2020, 09:28 AM
It's probably best to use Natufian or the Neolithic Levant samples (PPNB/PPNC) the others you mentioned are not Neolithic.

Dinka,Mota,Yoruba,Ken_LSA,Taforalt and those old ZAF samples is what I usually run for these SE Africans.

Tsakhur
08-17-2020, 09:44 AM
It's probably best to use Natufian or the Neolithic Levant samples (PPNB/PPNC) the others you mentioned are not Neolithic.

Dinka,Mota,Yoruba,Ken_LSA,Taforalt and those old ZAF samples is what I usually run for these SE Africans.

I see. Thanks.

Does Ken_LSA and Tarofalt contain West Eurasian ancestry or is it "purely African"?

drobbah
08-17-2020, 09:56 AM
I see. Thanks.

Does Ken_LSA and Tarofalt contain West Eurasian ancestry or is it "purely African"?
I don't think Ken_LSA has West Eurasian ancestry but Taforalt is majority Natufian-like but has deep ANA African ancestry.Since we don't have pure ANA samples they are the next best thing

Mnemonics
08-20-2020, 08:14 PM
Ken_LSA and Mota both definitely have Eurasian ancestry. Mota has some very old and non-differentiated Eurasian-like ancestry. I'm almost entirely sure its Eurasian, because it carries proportional amounts of Neanderthal Dna while Ken_LSA has some recent pastoralist ancestry on on top of its Mota-like ancestry.

Mota can be modeled in qpAdm very well as 60-66 percent Dinka, 24-27 percent South African and 13-17 percent UstIshim.

gihanga.rwanda
08-21-2020, 06:06 PM
Ken_LSA and Mota both definitely have Eurasian ancestry. Mota has some very old and non-differentiated Eurasian-like ancestry. I'm almost entirely sure its Eurasian, because it carries proportional amounts of Neanderthal Dna while Ken_LSA has some recent pastoralist ancestry on on top of its Mota-like ancestry.

Mota can be modeled in qpAdm very well as 60-66 percent Dinka, 24-27 percent South African and 13-17 percent UstIshim.

I admit I am a bit of a novice on this subject but I think we ought to be careful about drawing too many conclusions about this “deep” Neandertal affinity in SSA (I am not talking about the obvious examples of Eurasian gene flow), particularly since we’re still learning about the nature of this affinity. Some of it may be due to pre-OOA gene flow from AMH into Neanderthals but I’ve heard rumors that the Reich lab is planning to publish some interesting findings on this subject in early 2021 if not sooner.

I am not sure if this qpAdm result is that convincing. I know it’s not recommended to mix modern and ancient populations, especially populations like Ust-Ishim due to their basal nature. Paleolithic aDNA from NE Africa is a huge gap that needs to be filled.

Mnemonics
08-22-2020, 02:05 AM
It is generally fine to mix Moderns and Ancients when using transversion snps as they are much less likely to be damaged than transition snps.

I wouldn't be so sure about it if the signal wasn't so robust. African population history is very complex and some African groups (East Africans and West Africans) share a common ancestor with Eurasians to the exclusion of other Africans (Pygmies, and San). However, using F4ratios it is pretty easy to distinguish between common pre-OOA ancestry and Eurasian ancestry.

Eurasian African X Chimp/San : Eurasian Africa Eurasian2 Chimp/San

If you use the above F4 ratio, and the Eurasians selected have similar levels of Neanderthal admixture, you can distinguish between African and Eurasian ancestry by changing the African from the most basal African groups to those closest to Eurasians. If the Eurasian affinity stays when you move past the population you are examining (phylogenetically), than it almost always reflected in Neanderthal F4Ratios.

This also works pretty well for Eurasians too.

In fact, using this method, it seems like the African affinity found in some Eurasians seems to have come, at least partially, from some very deep population because It is distinguished reasonably well by including African Hunter-Gatherer populations.

Maybe the original Iberomaurusian paper was right about them having something Hadza-like.

Tsakhur
08-24-2020, 07:30 AM
Ken_LSA and Mota both definitely have Eurasian ancestry. Mota has some very old and non-differentiated Eurasian-like ancestry. I'm almost entirely sure its Eurasian, because it carries proportional amounts of Neanderthal Dna while Ken_LSA has some recent pastoralist ancestry on on top of its Mota-like ancestry.

Mota can be modeled in qpAdm very well as 60-66 percent Dinka, 24-27 percent South African and 13-17 percent UstIshim.

Interesting. Is the Eurasian ancestry in Ken_LSA and Mota, more Eastern or Western Eurasian or is it just too ancient to be classify as one of the two categories and just its own unique branch?

How do you run qpadm or interpret the results btw? I don't know how to do it.

Mnemonics
08-24-2020, 06:51 PM
Mota's eurasian seems to be entirely undifferentiated, which may indicate that that the Bab el Mendab crossing theory for OOA is still potentially viable. Ken_LSA seems like it has some West Eurasian admixture on top of the older layer of Eurasian.

Running admixtools is fairly simple, you just need a Linux OS or a virtual machine to get it running. You might need to download some libraries if you want build it from source, but the simplest way to get it running is download it via conda. The Admixtools documentation on Github shows the formats for preparing the parameter files. You can also download the 1240K/HO data from the Reich Labs site.
I would also recommend downloading Plink to trim your dataset to a more manageable size.

Tsakhur
08-24-2020, 06:56 PM
Mota's eurasian seems to be entirely undifferentiated, which may indicate that that the Bab el Mendab crossing theory for OOA is still potentially viable. Ken_LSA seems like it has some West Eurasian admixture on top of the older layer of Eurasian.

Running admixtools is fairly simple, you just need a Linux OS or a virtual machine to get it running. You might need to download some libraries if you want build it from source, but the simplest way to get it running is download it via conda. The Admixtools documentation on Github shows the formats for preparing the parameter files. You can also download the 1240K/HO data from the Reich Labs site.
I would also recommend downloading Plink to trim your dataset to a more manageable size.

I see.

Thank you but I don't even know how to interpret formal stats like qpadm, f3, d-stats. Would be great to learn from someone here. :)

Mnemonics
09-01-2020, 05:55 PM
I have been trying to replicate my successful qpadm models for Mota-like populations using G25.

The Hadza are basically identical to Mota so I can use them as a modern proxy to account for ancient dna damage.

Models with ZAF_2000BP
39339

Models with Khomani_San

39340

Look at those tight distances. It seems like there was a very ancient back migration that hit East/South-East Africa from after the OOA-bottleneck and post Neanderthal Admixture.

TuaMan
09-02-2020, 07:35 PM
It is generally fine to mix Moderns and Ancients when using transversion snps as they are much less likely to be damaged than transition snps.

I wouldn't be so sure about it if the signal wasn't so robust. African population history is very complex and some African groups (East Africans and West Africans) share a common ancestor with Eurasians to the exclusion of other Africans (Pygmies, and San). However, using F4ratios it is pretty easy to distinguish between common pre-OOA ancestry and Eurasian ancestry.

Eurasian African X Chimp/San : Eurasian Africa Eurasian2 Chimp/San

If you use the above F4 ratio, and the Eurasians selected have similar levels of Neanderthal admixture, you can distinguish between African and Eurasian ancestry by changing the African from the most basal African groups to those closest to Eurasians. If the Eurasian affinity stays when you move past the population you are examining (phylogenetically), than it almost always reflected in Neanderthal F4Ratios.

This also works pretty well for Eurasians too.

In fact, using this method, it seems like the African affinity found in some Eurasians seems to have come, at least partially, from some very deep population because It is distinguished reasonably well by including African Hunter-Gatherer populations.

Maybe the original Iberomaurusian paper was right about them having something Hadza-like.

Would you mind posting some of the log files from these F4-ratios?

Mnemonics
09-03-2020, 05:39 PM
Would you mind posting some of the log files from these F4-ratios?

I'll get them up as soon as I get home.

drobbah
09-03-2020, 09:16 PM
West Eurasian ancestry for Northern East Africans (Horners):


The Tigrays of Ethiopia

https://i.imgur.com/5WIhd7L.jpg


The Amharas of Ethiopia

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


The Agaws & Jews of Ethiopia

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


The Afars of Ethiopia,Eritrea & Djibouti

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


The Oromos of Ethiopia & Kenya

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


The Somalis of Somalia/Somaliland,Djibouti,Ethiopia & Kenya

https://i.imgur.com/v2Bsnlm.png


The Wolayta & Aris of Ethiopia
https://i.imgur.com/5zTbH1X.png



Source samples
Levant_PPNB:BAJ001,0.05805,0.164516,-0.029415,-0.133077,0.022158,-0.060519,-0.015276,-0.017538,0.089786,0.02278,0.018512,-0.025178,0.052031,0.004954,0.000136,-0.000133,-0.012386,-0.00152,-0.008422,0.017133,-0.003244,0.005935,0.000616,-0.013134,0
Levant_PPNB:I0867,0.072847,0.17264,-0.030924,-0.147935,0.034468,-0.068607,-0.016451,-0.011999,0.072606,0.048839,0.010555,-0.013038,0.029583,-0.008257,-0.024837,0.007425,0.020861,-0.008615,-0.004651,0.023886,-0.00025,0.004328,0,-0.005302,-0.006826
Levant_PPNB:I1704,0.073985,0.159438,-0.034318,-0.128232,0.037238,-0.072512,-0.018801,-0.017307,0.076492,0.033167,0.016401,-0.007343,0.032854,0.013762,-0.02348,0.00358,0.013169,-0.001014,-0.002011,0.017133,0.005989,0.004328,0.010106,-0.003374,0
Levant_PPNB:I1707,0.067156,0.140143,-0.041483,-0.137276,0.032929,-0.063029,-0.006345,-0.017768,0.069947,0.036812,0.031991,-0.014237,0.032111,0.008945,-0.018594,-0.001326,0.003129,-0.004687,0.003142,0.009254,-0.009858,0.013849,0.000123,0.004579,-0.002275
Levant_PPNB:I1710,0.092197,0.182795,-0.021873,-0.134046,0.0397,-0.058009,-0.01034,-0.00923,0.061971,0.038452,0.016564,-0.015586,0.032111,-0.006606,-0.042073,0.020949,0.024251,0.009248,-0.01169,0.026638,-0.001622,0.007296,-0.006409,-0.011206,-0.0097
Levant_PPNC:I1699,0.067156,0.168578,-0.023004,-0.150842,0.028621,-0.071954,-0.013866,-0.017999,0.077719,0.037905,0.006496,-0.013188,0.032705,-0.000275,-0.014929,0.008486,-0.000913,-0.007728,-0.013575,0.012381,-0.009982,0.01014,0.002958,0.003012,-0.001916
Yamnaya_RUS_Samara,0.1255849,0.089028,0.0426986,0. 1153479,-0.0287232,0.0450564,0.0036033,-0.0025642,-0.0559032,-0.0728943,0.0018222,3.32e-05,-0.0026924,-0.0233041,0.0366141,0.0157633,-0.0012316,-0.0017879,-0.0038408,0.0137704,-0.0031749,0.0007557,0.0110649,0.0186102,-0.004537
Yamnaya_UKR,0.119514,0.0873355,0.0452545,0.1106285 ,-0.028313,0.042531,0.00846,-0.003461,-0.0521535,-0.0707985,0.0002435,0.004421,-0.0043115,-0.0202305,0.0323015,0.0107395,-0.0002605,-0.011529,-0.005531,0.002376,-0.0028075,0.0004325,-0.009367,0.0192795,0.0031135
Sudanese:SUDANESE1,-0.574807,0.057885,-0.001886,-0.011305,-0.005539,-0.000837,-0.017391,0.018692,0.084468,-0.097679,-0.016888,0.02278,-0.03776,0.000963,0.006515,-0.01538,0.025425,-0.010769,0.020866,-0.022886,-0.001123,0.00136,-0.003081,-0.000964,0.00491
Sudanese:SUDANESE10,-0.581636,0.053823,0.003771,-0.001615,0.003077,0.001394,-0.011751,0.013846,0.084264,-0.095127,-0.020786,0.020382,-0.037165,-0.003991,0.010586,-0.021877,0.020079,-0.009882,0.021997,-0.015132,0,0.005812,-0.005916,-0.00241,0.001557
Sudanese:SUDANESE12,-0.575945,0.049761,0.001508,-0.010013,0.000923,-0.00251,-0.014101,0.013384,0.089581,-0.107337,-0.020948,0.020831,-0.044896,0.003165,0.009636,-0.01843,0.02034,-0.008488,0.018855,-0.021635,-0.000624,0.003462,-0.007025,-0.004217,0.002036
Sudanese:SUDANESE14,-0.578221,0.055854,0.003017,-0.007752,-0.008925,0.004741,-0.014571,0.023307,0.070765,-0.08802,-0.019974,0.019782,-0.041774,-0.004542,0.006243,-0.010872,0.022426,-0.013556,0.018352,-0.017008,-0.001996,0.004575,-0.001972,-0.000602,0.007185
Sudanese:SUDANESE15,-0.580498,0.05687,0.001131,-0.001292,-0.001846,-0.003068,-0.00893,0.013384,0.074856,-0.093669,-0.019811,0.026077,-0.038206,0.005367,0.013708,-0.015911,0.011213,-0.012415,0.017095,-0.021885,-0.004866,0.003462,-0.00456,-0.00012,0.006945
Sudanese:SUDANESE18,-0.583913,0.053823,0.003394,-0.003876,-0.001231,-0.00753,-0.015746,0.014307,0.076696,-0.096038,-0.020299,0.02293,-0.046382,-0.000275,0.007465,-0.012331,0.018384,-0.014189,0.017975,-0.015507,0.00025,0.005688,-0.004067,-0.004579,0.003353
Sudanese:SUDANESE2,-0.57936,0.057885,0.006788,-0.009367,-0.003077,-0.00251,-0.022326,0.02723,0.06013,-0.077086,-0.012991,0.020232,-0.025272,0.001101,0.010043,-0.018297,0.014473,-0.011275,0.023003,-0.014007,0.000499,0.004575,-0.001972,-0.009037,0.00934
Sudanese:SUDANESE3,-0.604401,0.054839,0.015462,0.010013,-0.00277,0.003068,-0.005405,0.011538,0.021066,-0.035172,-0.004547,0.013488,-0.014717,-0.000275,0.005972,-0.010077,0.011995,-0.003041,0.005656,-0.012881,-0.000125,0.008285,-0.000986,-0.003494,-0.000599
Sudanese:SUDANESE4,-0.588465,0.053823,-0.000377,-0.002907,-0.003693,-0.001673,-0.00423,0.008077,0.072401,-0.088385,-0.024196,0.029674,-0.03999,0.001376,0.00665,-0.018032,0.02034,-0.013049,0.021871,-0.017008,-0.001373,-0.001731,-0.001109,-0.004097,0.003952
Sudanese:SUDANESE5,-0.57253,0.054839,0.007165,-0.008075,-0.004308,-0.005857,-0.013161,0.014538,0.089172,-0.104421,-0.02241,0.025927,-0.042517,-0.001514,0.009772,-0.011138,0.02021,-0.013809,0.024134,-0.024262,-0.000374,0.010263,-0.004683,-0.003735,0.005987
Sudanese:SUDANESE6,-0.575945,0.050776,0.004148,-0.007752,-0.002154,-0.004183,-0.015511,0.010846,0.087536,-0.105515,-0.018188,0.029973,-0.042517,-0.003716,0.007465,-0.017502,0.017732,-0.016089,0.024008,-0.022761,0.000499,0.002349,-0.002095,-0.005302,0.005269
Sudanese:SUDANESE7,-0.571392,0.046714,-0.007165,-0.007429,-0.005232,-0.002789,-0.00799,0.018922,0.0904,-0.108977,-0.018512,0.020831,-0.047125,0.000688,0.013165,-0.023734,0.021644,-0.012035,0.026145,-0.023261,-0.000998,0.004822,-0.000986,-0.001687,0.003712
Sudanese:SUDANESE8,-0.586189,0.060932,0.009428,0.00646,-0.003385,-0.002789,0.00423,0.004846,0.056653,-0.078179,-0.02582,0.018284,-0.033746,-0.00234,0.001086,-0.016043,0.011604,-0.013302,0.021369,-0.014507,0.00287,0.005564,-0.00456,-0.006025,-0.001676
Sudanese:SUDANESE9,-0.587327,0.053823,0.007165,0.000646,-0.001231,0.001952,0.0094,-0.003231,0.059312,-0.072712,-0.019649,0.02218,-0.027651,-0.003441,0.00095,-0.008088,0.018254,-0.009882,0.013324,-0.016758,-0.002371,0.003586,-0.005669,-0.00241,0
ETH_4500BP,-0.511066,0.043668,0.000754,0.000969,-0.00277,-0.011435,0.050997,-0.045229,0.089172,-0.087838,-0.012991,-0.002997,-0.031219,0.000688,0.02158,-0.029965,0.027772,0.039273,0.00176,-0.009004,0.000374,0.006183,-0.003451,-0.00241,-0.000838
Dinka:Dinka1,-0.574807,0.045699,0,-0.007429,-0.00277,0.002231,-0.020211,0.020538,0.086105,-0.09859,-0.016076,0.027575,-0.039395,-0.001239,0.011808,-0.02559,0.01343,-0.013049,0.028911,-0.024262,0.003993,0.001237,0.008011,0.005422,0.009 939
Dinka:Dinka2,-0.578221,0.053823,-0.003771,-0.008075,-0.010156,-0.003347,-0.014806,0.020768,0.084264,-0.096585,-0.028256,0.025627,-0.036273,-0.003578,0.005836,-0.021745,0.03064,-0.007728,0.021871,-0.025512,-0.001248,0.002968,-0.000493,-0.000843,0.010059
Dinka:Dinka3,-0.578221,0.051792,0.004148,-0.008398,-0.003077,-0.001952,-0.020681,0.021461,0.076492,-0.095856,-0.01494,0.018583,-0.036719,0.001927,0.014115,-0.022142,0.008736,-0.007221,0.023128,-0.021635,0.005241,0.006183,-0.000493,-0.00482,0.012334
MAR_EN,-0.1735805,0.0919055,-0.0258325,-0.083657,0.0283125,-0.0596825,-0.079316,0.021461,0.1500185,0.0043735,0.0222475,-0.0264515,0.075148,-0.0461725,0.069353,-0.03381,0.0171455,-0.05549,-0.1487635,0.0340785,-0.038245,-0.118212,0.0826995,-0.009941,0.021615
MAR_LN,0.021626,0.148267,0.003394,-0.095285,0.047393,-0.054384,-0.027731,0.008769,0.083855,0.054124,0.020136,0.001 798,0.002973,-0.028901,0.004343,0.009944,0.032726,-0.014062,-0.033938,-5e-04,-0.018343,-0.02201,0.011709,-0.009881,-0.004191
MAR_Taforalt,-0.189857,0.0814452,-0.0242866,-0.085595,0.027636,-0.0552202,-0.0705968,0.0184146,0.155397,0.003499,0.0209156,-0.0318316,0.0747168,-0.0513334,0.0711988,-0.0363032,0.0052676,-0.066106,-0.1424162,0.0389938,-0.0376836,-0.1255322,0.0730118,-0.0137606,0.0164534
KEN_LSA:I8808,-0.522448,0.044683,-0.010936,0.006137,0.004308,-0.006414,0.085309,-0.06692,0.076287,-0.06925,-0.011367,0.010491,-0.033003,0.000138,0.00855,-0.014983,0.021383,0.038513,-0.002137,-0.005253,-0.007612,-0.002968,0.002342,0.004699,-0.000718
Yoruba:HGDP00944,-0.628304,0.061947,0.021496,0.01615,-0.001539,0.003347,-0.042067,0.049152,-0.050108,0.030616,-0.000974,0.003897,0.023191,-0.006468,0.00475,-0.004773,0.005737,-0.007601,0.00729,-0.002876,0.004991,0.000495,-0.006409,0.002771,-0.005029
Yoruba:NA18486,-0.627165,0.060932,0.019987,0.01615,0.001539,0.0178 49,-0.043947,0.043152,-0.050722,0.029522,0.006008,0.001199,0.01888,-0.00055,0.011672,-0.012729,0.00665,0.002027,0.008296,-0.007629,0.004617,0.007172,-0.000863,-0.003253,0.004191
Yoruba:NA18487,-0.627165,0.066009,0.021496,0.015181,0.002462,0.012 55,-0.050292,0.05169,-0.046836,0.031891,0.005359,-0.003447,0.027651,0.00234,0.015472,-0.011005,0.006258,-0.002027,0.005028,0.001751,-0.001622,-0.000124,-0.000986,0.001205,0.002155
Yoruba:NA18488,-0.63058,0.067025,0.020742,0.01615,0.001846,0.01506 ,-0.047002,0.050998,-0.052563,0.035172,0.004384,0.004946,0.025124,0.001 376,0.013843,-0.007027,0.009909,0.004307,0.007668,-0.002126,-0.000374,0.000742,-0.001972,-0.002048,-0.002994
Yoruba:NA18489,-0.627165,0.062963,0.021119,0.016796,0.001539,0.012 271,-0.048647,0.044537,-0.044177,0.035536,0.002598,-0.002248,0.019475,0.002202,0.01045,-0.011403,-0.00013,0.002027,0.008296,-0.006503,0.001996,0.003091,-0.00037,-0.005663,0.003832
Yoruba:NA18498,-0.627165,0.063978,0.026398,0.017765,-0.001231,0.009761,-0.040187,0.049613,-0.043973,0.03991,0.004709,-0.002548,0.023934,0.004817,0.015201,-0.011933,0.00678,-0.000127,0.004274,-0.001876,0.00574,0.007914,-0.001356,0.000361,0.000599
Yoruba:NA18499,-0.63058,0.057885,0.019987,0.011951,-0.001539,0.016176,-0.046297,0.044075,-0.048472,0.03098,0.003735,-0.001948,0.026016,0,0.016151,-0.011403,0.006128,-0.000253,0.002011,-0.004502,0.001248,0.002226,-0.000493,0.000723,-0.001557
Yoruba:NA18501,-0.631718,0.059916,0.020742,0.018088,-0.000615,0.016455,-0.037837,0.046383,-0.048063,0.029704,0.004872,0.002398,0.019921,0.003 028,0.013979,-0.020021,0.005737,0.001267,0.005782,-0.004252,0.006239,0.001855,-0.003821,0.001325,-0.000479
Yoruba:NA18504,-0.636271,0.061947,0.024136,0.017119,-0.001231,0.012271,-0.040187,0.047767,-0.049086,0.032802,0.007307,0.001499,0.019921,0.000 688,0.010043,-0.006364,0.012256,0.00266,0.00729,-0.004752,-0.002121,0.00136,-0.000863,0.001325,-0.00012
Yoruba:NA18505,-0.636271,0.062963,0.02489,0.016473,0.002154,0.0083 67,-0.043477,0.052152,-0.052972,0.033714,0.008119,0.003297,0.025124,-0.001927,0.011265,-0.007425,0.007823,-0.000507,0.003394,-0.001251,-0.000873,-0.001237,-0.003081,-0.000964,0.002395
Yoruba:NA18507,-0.628304,0.061947,0.02225,0.021964,0.002154,0.0131 08,-0.048647,0.045921,-0.050722,0.030616,0.004709,0.001649,0.02438,0.0049 54,0.014929,-0.001591,0.010691,0.003167,0.006913,0.001126,-0.002745,0.001978,0.000863,-0.000964,-0.007664
Levant_Natufian:I1072,0.021626,0.151314,-0.036204,-0.141475,0.034776,-0.082831,-0.032196,-0.010384,0.128032,0.012028,0.037837,-0.024878,0.085629,0.002615,0.007872,-0.008088,-0.020601,-0.008742,-0.026019,0.040269,0.007112,0.003462,0.007025,0.002 289,0.000599
Yemenite_Al_Bayda:Y070,0.033009,0.144205,-0.060716,-0.109821,-0.008309,-0.044065,-0.015746,-0.011076,0.055017,-0.002369,0.018675,-0.029973,0.048761,0.003441,-0.0019,0.019225,-0.029467,0.007221,0.002891,0.018384,0.013102,0.015 457,-0.014913,-0.004699,-0.006347
Yemenite_Al_Bayda:Y086,0.036423,0.129988,-0.054682,-0.109175,-0.016926,-0.05522,-0.014336,-0.009461,0.053994,-0.016766,0.001624,-0.020382,0.052031,0.001239,0.013843,0.028639,-0.014081,0.005954,-0.002388,0.012131,0.011105,0.010263,-0.001849,-0.002048,-0.000718
Yemenite_Al_Bayda:Y089,0.045529,0.144205,-0.063733,-0.099484,-0.012925,-0.04769,-0.014571,-0.003692,0.060335,-0.007836,0.01023,-0.027426,0.048909,0.007432,0.004343,0.022805,-0.010561,0.002787,0.005405,0.019885,0.010482,0.010 881,-0.003204,-0.00012,-0.005868
Yemenite_Al_Bayda:Y092,0.036423,0.132019,-0.065619,-0.113374,-0.009848,-0.051316,-0.017156,-0.018692,0.056244,0.001276,0.012666,-0.030573,0.048612,0.002202,0.013165,0.021082,-0.026468,0.010769,0.001508,0.021385,0.012603,0.025 472,-0.009983,0.00964,-0.000359
Yemenite_Al_Bayda:Y097,0.034147,0.141159,-0.061848,-0.105945,-0.006463,-0.05271,-0.011281,-0.009692,0.05604,-0.007472,0.011367,-0.03357,0.051883,0.004542,-0.000407,0.022142,-0.021513,0.012035,0.001508,0.018509,0.00549,0.0202 79,-0.009983,0.005181,-0.005029
Yemenite_Al_Bayda:Y100,0.046667,0.140143,-0.06939,-0.106591,-0.006463,-0.039881,-0.005875,-0.008307,0.043155,-0.002734,0.011205,-0.030873,0.055302,0.00578,0.009229,0.031291,-0.008736,0.004181,-0.003897,0.017258,0.005865,0.014715,-0.004683,-0.001205,-0.004191

Michalis Moriopoulos
09-03-2020, 09:31 PM
I have wondered if the San/ZAF 2000 signal in Mota, Kenya LSA, Hadza, etc. was actually Ghost Modern ancestry best proxied by ZAF 2000 rather than actual Southern African gene flow, but I'm not sure if or how this can be known. There does seem to have been a cline from Mota to ZAF 2000 anyway (Malawi samples) so it certainly makes sense if it's real Southern African HG ancestry.

Mnemonics
09-03-2020, 10:28 PM
Here are some of the F4Ratios with a variety of pairs of Eurasians.

39388

TuaMan
09-04-2020, 02:47 AM
Here are some of the F4Ratios with a variety of pairs of Eurasians.

39388

Pulling these two tests from your file:

result: UstIshim Mende Mota Chimp : UstIshim Mende Iberia_HG Chimp 0.210780 0.012997 16.218 1036796
result: UstIshim Mende Kenya_LSA Chimp : UstIshim Mende Iberia_HG Chimp 0.176014 0.015939 11.043 829506

If I'm interpreting it right, the alpha number means Mota and Kenya_LSA are about 21% and 17% UstIshim like (the rest being Mende-like), and the strongly positive Z scores make these admixtures roughly good enough fits?

How exactly does the calculation of alpha work in these tests? If I were to run a one off f4 test of your numerator UstIshim Mende Mota Chimp, I think it would be significantly postive (meaning Mota shares more alleles with UstIshim then he does with Mende - at least, I believe I've seen similar results with Dstats), but not to the extent of the Iberia_HG and UstIshim sharing in your denominator. Ergo, the bigger raw stat in the denominator dominates the ratio, and when dividing the numerator the alpha represents the amount of UstIshim like admixture in Mota?

Mnemonics
09-04-2020, 04:35 AM
The actual math involved in calculating the alpha is roughly inline with your description, you can get a clearer description of the principles involved from reading this general overview of the use of F Statistics,
particularly the bit that shows how the alpha is calculated https://www.genetics.org/content/202/4/1485.

But it is very important to remember that F4 ratios just like F-stats capture affinities, which can be a result of admixture or simply due to phylogenetic relationships. A prime example of this is Dinka, which shows a sizable affinity to UstIshim relative to Mende, but this is unlikely to be a consequence of post OOA Eurasian admixture as it has slightly less Neanderthal admixture than is in Yoruba.

An F4 ratio can tell you that Mota shares 17-21% more alleles with UstIshim but it cannot directly tell you that that affinity is due to admixture, qpadm works much better for that as rotating population into the left and right lists allows better analysis of the plausibility of admixture through null hypothesis testing. Also, the Z-scores of an F4 test do not describe the fit of a model, but are instead a measure of the significance of the relationship.

Typically a Z-score greater than 3 or less than -3 indicates that the affinity is real.

However, the design nature of an F4 ratio test means that you will probably never see a result with a significant percentage without a highly negative or positive Z-Score.

Angoliga
09-04-2020, 03:42 PM
Pulling these two tests from your file:

result: UstIshim Mende Mota Chimp : UstIshim Mende Iberia_HG Chimp 0.210780 0.012997 16.218 1036796
result: UstIshim Mende Kenya_LSA Chimp : UstIshim Mende Iberia_HG Chimp 0.176014 0.015939 11.043 829506

If I'm interpreting it right, the alpha number means Mota and Kenya_LSA are about 21% and 17% UstIshim like (the rest being Mende-like), and the strongly positive Z scores make these admixtures roughly good enough fits?

How exactly does the calculation of alpha work in these tests? If I were to run a one off f4 test of your numerator UstIshim Mende Mota Chimp, I think it would be significantly postive (meaning Mota shares more alleles with UstIshim then he does with Mende - at least, I believe I've seen similar results with Dstats), but not to the extent of the Iberia_HG and UstIshim sharing in your denominator. Ergo, the bigger raw stat in the denominator dominates the ratio, and when dividing the numerator the alpha represents the amount of UstIshim like admixture in Mota?

Would it be possible to run these models with Yoruba instead of Mende?

Among modern West-African samples, Mende were found to have the highest amount of archaic_HG-like affinities in deep-layer G25 runs.
I'm curious how much these fstat results would differ with a West-African reference exhibiting more modern-SSA/less archaic.

TuaMan
09-04-2020, 04:31 PM
But it is very important to remember that F4 ratios just like F-stats capture affinities, which can be a result of admixture or simply due to phylogenetic relationships. A prime example of this is Dinka, which shows a sizable affinity to UstIshim relative to Mende, but this is unlikely to be a consequence of post OOA Eurasian admixture as it has slightly less Neanderthal admixture than is in Yoruba.

What's your interpretation of the below Dstats if Dinka doesn't have post-OOA admixture?

Chimp.REF Dinka.DG China_Tianyuan Russia_Ust_Ishim.DG -0.0034 -0.602 38044 38302 800554
Chimp.REF Dinka.DG Indian_GreatAndaman_100BP.SG Russia_Ust_Ishim.DG -0.0234 -4.657 46872 49114 1007370
Chimp.REF Dinka.DG Japan_Jomon.SG Russia_Ust_Ishim.DG -0.0196 -3.748 37098 38581 796250
Chimp.REF Dinka.DG Yana_UP.SG Russia_Ust_Ishim.DG -0.0115 -2.513 48433 49565 1020895
Chimp.REF Dinka.DG Anatolia_Epipaleolithic Russia_Ust_Ishim.DG -0.0207 -4.027 36315 37852 759826
Chimp.REF Dinka.DG Jordan_PPNB Russia_Ust_Ishim.DG -0.0232 -4.173 16429 17210 338709
Chimp.REF Dinka.DG Iran_GanjDareh_N Russia_Ust_Ishim.DG -0.0248 -5.707 45401 47705 944076
Chimp.REF Dinka.DG Russia_Kostenki14.SG Russia_Ust_Ishim.DG -0.0134 -2.598 44179 45377 933815
Chimp.REF Dinka.DG DevilsCave_N.SG Russia_Ust_Ishim.DG -0.0193 -4.316 48418 50327 1020610

Mnemonics
09-04-2020, 09:05 PM
Would it be possible to run these models with Yoruba instead of Mende?

Among modern West-African samples, Mende were found to have the highest amount of archaic_HG-like affinities in deep-layer G25 runs.
I'm curious how much these fstat results would differ with a West-African reference exhibiting more modern-SSA/less archaic.

Running this with Mende produces results roughly similar to Yoruba, however I deliberately choose Mende for its archaic ancestry, after all Eurasians have Neanderthal ancestry which can increase attraction to Chimp which could skew the results. By using an African population with Archaic ancestry you can limit the effects of Archaic ancestry on the alpha.

There are a few plausible explanations for those F4 ratios for Dinka.

1. Dinka has ancestry from the African ancestors of Eurasians who lacked Neanderthal admixture. This would mean that Dinka are potentially substantially admixed with Basal Eurasian or ANA-like ancestry.

2. West Africans have ancestry from a group deeper in the tree. This deep ancestry could be Ghost Modern admixture or ZAF_2000BP like admixture.

3.Dinka-Like groups could have contributed to OOA populations differentially to West Africans. Meaning that the OOA population was just closer East Africans phylogenetically.

My personal opinion is that it is probably a mix of 2 or more of these possibilities.

Dinka works fairly well as a proxy for the Neanderthal diluting ancestry in Basal Eurasian rich populations using qpadm (even with Iberomaurusians in the right pops list), and it seems like West Africans definitely have more Basal ancestry than Dinka. So, I can't say which of these factors is primarily responsible for the stat without more ancient African samples.

Mnemonics
09-05-2020, 06:39 AM
What's your interpretation of the below Dstats if Dinka doesn't have post-OOA admixture?

Chimp.REF Dinka.DG China_Tianyuan Russia_Ust_Ishim.DG -0.0034 -0.602 38044 38302 800554
Chimp.REF Dinka.DG Indian_GreatAndaman_100BP.SG Russia_Ust_Ishim.DG -0.0234 -4.657 46872 49114 1007370
Chimp.REF Dinka.DG Japan_Jomon.SG Russia_Ust_Ishim.DG -0.0196 -3.748 37098 38581 796250
Chimp.REF Dinka.DG Yana_UP.SG Russia_Ust_Ishim.DG -0.0115 -2.513 48433 49565 1020895
Chimp.REF Dinka.DG Anatolia_Epipaleolithic Russia_Ust_Ishim.DG -0.0207 -4.027 36315 37852 759826
Chimp.REF Dinka.DG Jordan_PPNB Russia_Ust_Ishim.DG -0.0232 -4.173 16429 17210 338709
Chimp.REF Dinka.DG Iran_GanjDareh_N Russia_Ust_Ishim.DG -0.0248 -5.707 45401 47705 944076
Chimp.REF Dinka.DG Russia_Kostenki14.SG Russia_Ust_Ishim.DG -0.0134 -2.598 44179 45377 933815
Chimp.REF Dinka.DG DevilsCave_N.SG Russia_Ust_Ishim.DG -0.0193 -4.316 48418 50327 1020610

Those D stats are roughly inline with Dinka having about the same amount of Eurasian admixture as Yoruba. Which is significantly less than the additional 13% increased affinity that the F4 Ratios indicate.

Kale
09-09-2020, 04:07 AM
Somewhat on topic. Here's a PCA generated by making a matrix of F3 outgroup stats (outgroup being Neanderthal).

39463
Cline from South_Africa_2000BP.SG > San/JuHoan > Malawi ancients (the 9000BP one is definitely misdated) > Kenya_PastoralN
Another from a West-Africanish cluster > Dinka > Masai > Kenya_PastoralN > Israel_Peki'in_CA
Pygmy & ShumLaka cluster
...Then Mota out in no-mans land.

maroco
11-22-2020, 07:49 PM
West Eurasian ancestry for Northern East Africans (Horners):


The Tigrays of Ethiopia

https://i.imgur.com/5WIhd7L.jpg


The Amharas of Ethiopia

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


The Agaws & Jews of Ethiopia

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


The Afars of Ethiopia,Eritrea & Djibouti

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


The Oromos of Ethiopia & Kenya

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


The Somalis of Somalia/Somaliland,Djibouti,Ethiopia & Kenya

https://i.imgur.com/v2Bsnlm.png


The Wolayta & Aris of Ethiopia
https://i.imgur.com/5zTbH1X.png



Source samples
Levant_PPNB:BAJ001,0.05805,0.164516,-0.029415,-0.133077,0.022158,-0.060519,-0.015276,-0.017538,0.089786,0.02278,0.018512,-0.025178,0.052031,0.004954,0.000136,-0.000133,-0.012386,-0.00152,-0.008422,0.017133,-0.003244,0.005935,0.000616,-0.013134,0
Levant_PPNB:I0867,0.072847,0.17264,-0.030924,-0.147935,0.034468,-0.068607,-0.016451,-0.011999,0.072606,0.048839,0.010555,-0.013038,0.029583,-0.008257,-0.024837,0.007425,0.020861,-0.008615,-0.004651,0.023886,-0.00025,0.004328,0,-0.005302,-0.006826
Levant_PPNB:I1704,0.073985,0.159438,-0.034318,-0.128232,0.037238,-0.072512,-0.018801,-0.017307,0.076492,0.033167,0.016401,-0.007343,0.032854,0.013762,-0.02348,0.00358,0.013169,-0.001014,-0.002011,0.017133,0.005989,0.004328,0.010106,-0.003374,0
Levant_PPNB:I1707,0.067156,0.140143,-0.041483,-0.137276,0.032929,-0.063029,-0.006345,-0.017768,0.069947,0.036812,0.031991,-0.014237,0.032111,0.008945,-0.018594,-0.001326,0.003129,-0.004687,0.003142,0.009254,-0.009858,0.013849,0.000123,0.004579,-0.002275
Levant_PPNB:I1710,0.092197,0.182795,-0.021873,-0.134046,0.0397,-0.058009,-0.01034,-0.00923,0.061971,0.038452,0.016564,-0.015586,0.032111,-0.006606,-0.042073,0.020949,0.024251,0.009248,-0.01169,0.026638,-0.001622,0.007296,-0.006409,-0.011206,-0.0097
Levant_PPNC:I1699,0.067156,0.168578,-0.023004,-0.150842,0.028621,-0.071954,-0.013866,-0.017999,0.077719,0.037905,0.006496,-0.013188,0.032705,-0.000275,-0.014929,0.008486,-0.000913,-0.007728,-0.013575,0.012381,-0.009982,0.01014,0.002958,0.003012,-0.001916
Yamnaya_RUS_Samara,0.1255849,0.089028,0.0426986,0. 1153479,-0.0287232,0.0450564,0.0036033,-0.0025642,-0.0559032,-0.0728943,0.0018222,3.32e-05,-0.0026924,-0.0233041,0.0366141,0.0157633,-0.0012316,-0.0017879,-0.0038408,0.0137704,-0.0031749,0.0007557,0.0110649,0.0186102,-0.004537
Yamnaya_UKR,0.119514,0.0873355,0.0452545,0.1106285 ,-0.028313,0.042531,0.00846,-0.003461,-0.0521535,-0.0707985,0.0002435,0.004421,-0.0043115,-0.0202305,0.0323015,0.0107395,-0.0002605,-0.011529,-0.005531,0.002376,-0.0028075,0.0004325,-0.009367,0.0192795,0.0031135
Sudanese:SUDANESE1,-0.574807,0.057885,-0.001886,-0.011305,-0.005539,-0.000837,-0.017391,0.018692,0.084468,-0.097679,-0.016888,0.02278,-0.03776,0.000963,0.006515,-0.01538,0.025425,-0.010769,0.020866,-0.022886,-0.001123,0.00136,-0.003081,-0.000964,0.00491
Sudanese:SUDANESE10,-0.581636,0.053823,0.003771,-0.001615,0.003077,0.001394,-0.011751,0.013846,0.084264,-0.095127,-0.020786,0.020382,-0.037165,-0.003991,0.010586,-0.021877,0.020079,-0.009882,0.021997,-0.015132,0,0.005812,-0.005916,-0.00241,0.001557
Sudanese:SUDANESE12,-0.575945,0.049761,0.001508,-0.010013,0.000923,-0.00251,-0.014101,0.013384,0.089581,-0.107337,-0.020948,0.020831,-0.044896,0.003165,0.009636,-0.01843,0.02034,-0.008488,0.018855,-0.021635,-0.000624,0.003462,-0.007025,-0.004217,0.002036
Sudanese:SUDANESE14,-0.578221,0.055854,0.003017,-0.007752,-0.008925,0.004741,-0.014571,0.023307,0.070765,-0.08802,-0.019974,0.019782,-0.041774,-0.004542,0.006243,-0.010872,0.022426,-0.013556,0.018352,-0.017008,-0.001996,0.004575,-0.001972,-0.000602,0.007185
Sudanese:SUDANESE15,-0.580498,0.05687,0.001131,-0.001292,-0.001846,-0.003068,-0.00893,0.013384,0.074856,-0.093669,-0.019811,0.026077,-0.038206,0.005367,0.013708,-0.015911,0.011213,-0.012415,0.017095,-0.021885,-0.004866,0.003462,-0.00456,-0.00012,0.006945
Sudanese:SUDANESE18,-0.583913,0.053823,0.003394,-0.003876,-0.001231,-0.00753,-0.015746,0.014307,0.076696,-0.096038,-0.020299,0.02293,-0.046382,-0.000275,0.007465,-0.012331,0.018384,-0.014189,0.017975,-0.015507,0.00025,0.005688,-0.004067,-0.004579,0.003353
Sudanese:SUDANESE2,-0.57936,0.057885,0.006788,-0.009367,-0.003077,-0.00251,-0.022326,0.02723,0.06013,-0.077086,-0.012991,0.020232,-0.025272,0.001101,0.010043,-0.018297,0.014473,-0.011275,0.023003,-0.014007,0.000499,0.004575,-0.001972,-0.009037,0.00934
Sudanese:SUDANESE3,-0.604401,0.054839,0.015462,0.010013,-0.00277,0.003068,-0.005405,0.011538,0.021066,-0.035172,-0.004547,0.013488,-0.014717,-0.000275,0.005972,-0.010077,0.011995,-0.003041,0.005656,-0.012881,-0.000125,0.008285,-0.000986,-0.003494,-0.000599
Sudanese:SUDANESE4,-0.588465,0.053823,-0.000377,-0.002907,-0.003693,-0.001673,-0.00423,0.008077,0.072401,-0.088385,-0.024196,0.029674,-0.03999,0.001376,0.00665,-0.018032,0.02034,-0.013049,0.021871,-0.017008,-0.001373,-0.001731,-0.001109,-0.004097,0.003952
Sudanese:SUDANESE5,-0.57253,0.054839,0.007165,-0.008075,-0.004308,-0.005857,-0.013161,0.014538,0.089172,-0.104421,-0.02241,0.025927,-0.042517,-0.001514,0.009772,-0.011138,0.02021,-0.013809,0.024134,-0.024262,-0.000374,0.010263,-0.004683,-0.003735,0.005987
Sudanese:SUDANESE6,-0.575945,0.050776,0.004148,-0.007752,-0.002154,-0.004183,-0.015511,0.010846,0.087536,-0.105515,-0.018188,0.029973,-0.042517,-0.003716,0.007465,-0.017502,0.017732,-0.016089,0.024008,-0.022761,0.000499,0.002349,-0.002095,-0.005302,0.005269
Sudanese:SUDANESE7,-0.571392,0.046714,-0.007165,-0.007429,-0.005232,-0.002789,-0.00799,0.018922,0.0904,-0.108977,-0.018512,0.020831,-0.047125,0.000688,0.013165,-0.023734,0.021644,-0.012035,0.026145,-0.023261,-0.000998,0.004822,-0.000986,-0.001687,0.003712
Sudanese:SUDANESE8,-0.586189,0.060932,0.009428,0.00646,-0.003385,-0.002789,0.00423,0.004846,0.056653,-0.078179,-0.02582,0.018284,-0.033746,-0.00234,0.001086,-0.016043,0.011604,-0.013302,0.021369,-0.014507,0.00287,0.005564,-0.00456,-0.006025,-0.001676
Sudanese:SUDANESE9,-0.587327,0.053823,0.007165,0.000646,-0.001231,0.001952,0.0094,-0.003231,0.059312,-0.072712,-0.019649,0.02218,-0.027651,-0.003441,0.00095,-0.008088,0.018254,-0.009882,0.013324,-0.016758,-0.002371,0.003586,-0.005669,-0.00241,0
ETH_4500BP,-0.511066,0.043668,0.000754,0.000969,-0.00277,-0.011435,0.050997,-0.045229,0.089172,-0.087838,-0.012991,-0.002997,-0.031219,0.000688,0.02158,-0.029965,0.027772,0.039273,0.00176,-0.009004,0.000374,0.006183,-0.003451,-0.00241,-0.000838
Dinka:Dinka1,-0.574807,0.045699,0,-0.007429,-0.00277,0.002231,-0.020211,0.020538,0.086105,-0.09859,-0.016076,0.027575,-0.039395,-0.001239,0.011808,-0.02559,0.01343,-0.013049,0.028911,-0.024262,0.003993,0.001237,0.008011,0.005422,0.009 939
Dinka:Dinka2,-0.578221,0.053823,-0.003771,-0.008075,-0.010156,-0.003347,-0.014806,0.020768,0.084264,-0.096585,-0.028256,0.025627,-0.036273,-0.003578,0.005836,-0.021745,0.03064,-0.007728,0.021871,-0.025512,-0.001248,0.002968,-0.000493,-0.000843,0.010059
Dinka:Dinka3,-0.578221,0.051792,0.004148,-0.008398,-0.003077,-0.001952,-0.020681,0.021461,0.076492,-0.095856,-0.01494,0.018583,-0.036719,0.001927,0.014115,-0.022142,0.008736,-0.007221,0.023128,-0.021635,0.005241,0.006183,-0.000493,-0.00482,0.012334
MAR_EN,-0.1735805,0.0919055,-0.0258325,-0.083657,0.0283125,-0.0596825,-0.079316,0.021461,0.1500185,0.0043735,0.0222475,-0.0264515,0.075148,-0.0461725,0.069353,-0.03381,0.0171455,-0.05549,-0.1487635,0.0340785,-0.038245,-0.118212,0.0826995,-0.009941,0.021615
MAR_LN,0.021626,0.148267,0.003394,-0.095285,0.047393,-0.054384,-0.027731,0.008769,0.083855,0.054124,0.020136,0.001 798,0.002973,-0.028901,0.004343,0.009944,0.032726,-0.014062,-0.033938,-5e-04,-0.018343,-0.02201,0.011709,-0.009881,-0.004191
MAR_Taforalt,-0.189857,0.0814452,-0.0242866,-0.085595,0.027636,-0.0552202,-0.0705968,0.0184146,0.155397,0.003499,0.0209156,-0.0318316,0.0747168,-0.0513334,0.0711988,-0.0363032,0.0052676,-0.066106,-0.1424162,0.0389938,-0.0376836,-0.1255322,0.0730118,-0.0137606,0.0164534
KEN_LSA:I8808,-0.522448,0.044683,-0.010936,0.006137,0.004308,-0.006414,0.085309,-0.06692,0.076287,-0.06925,-0.011367,0.010491,-0.033003,0.000138,0.00855,-0.014983,0.021383,0.038513,-0.002137,-0.005253,-0.007612,-0.002968,0.002342,0.004699,-0.000718
Yoruba:HGDP00944,-0.628304,0.061947,0.021496,0.01615,-0.001539,0.003347,-0.042067,0.049152,-0.050108,0.030616,-0.000974,0.003897,0.023191,-0.006468,0.00475,-0.004773,0.005737,-0.007601,0.00729,-0.002876,0.004991,0.000495,-0.006409,0.002771,-0.005029
Yoruba:NA18486,-0.627165,0.060932,0.019987,0.01615,0.001539,0.0178 49,-0.043947,0.043152,-0.050722,0.029522,0.006008,0.001199,0.01888,-0.00055,0.011672,-0.012729,0.00665,0.002027,0.008296,-0.007629,0.004617,0.007172,-0.000863,-0.003253,0.004191
Yoruba:NA18487,-0.627165,0.066009,0.021496,0.015181,0.002462,0.012 55,-0.050292,0.05169,-0.046836,0.031891,0.005359,-0.003447,0.027651,0.00234,0.015472,-0.011005,0.006258,-0.002027,0.005028,0.001751,-0.001622,-0.000124,-0.000986,0.001205,0.002155
Yoruba:NA18488,-0.63058,0.067025,0.020742,0.01615,0.001846,0.01506 ,-0.047002,0.050998,-0.052563,0.035172,0.004384,0.004946,0.025124,0.001 376,0.013843,-0.007027,0.009909,0.004307,0.007668,-0.002126,-0.000374,0.000742,-0.001972,-0.002048,-0.002994
Yoruba:NA18489,-0.627165,0.062963,0.021119,0.016796,0.001539,0.012 271,-0.048647,0.044537,-0.044177,0.035536,0.002598,-0.002248,0.019475,0.002202,0.01045,-0.011403,-0.00013,0.002027,0.008296,-0.006503,0.001996,0.003091,-0.00037,-0.005663,0.003832
Yoruba:NA18498,-0.627165,0.063978,0.026398,0.017765,-0.001231,0.009761,-0.040187,0.049613,-0.043973,0.03991,0.004709,-0.002548,0.023934,0.004817,0.015201,-0.011933,0.00678,-0.000127,0.004274,-0.001876,0.00574,0.007914,-0.001356,0.000361,0.000599
Yoruba:NA18499,-0.63058,0.057885,0.019987,0.011951,-0.001539,0.016176,-0.046297,0.044075,-0.048472,0.03098,0.003735,-0.001948,0.026016,0,0.016151,-0.011403,0.006128,-0.000253,0.002011,-0.004502,0.001248,0.002226,-0.000493,0.000723,-0.001557
Yoruba:NA18501,-0.631718,0.059916,0.020742,0.018088,-0.000615,0.016455,-0.037837,0.046383,-0.048063,0.029704,0.004872,0.002398,0.019921,0.003 028,0.013979,-0.020021,0.005737,0.001267,0.005782,-0.004252,0.006239,0.001855,-0.003821,0.001325,-0.000479
Yoruba:NA18504,-0.636271,0.061947,0.024136,0.017119,-0.001231,0.012271,-0.040187,0.047767,-0.049086,0.032802,0.007307,0.001499,0.019921,0.000 688,0.010043,-0.006364,0.012256,0.00266,0.00729,-0.004752,-0.002121,0.00136,-0.000863,0.001325,-0.00012
Yoruba:NA18505,-0.636271,0.062963,0.02489,0.016473,0.002154,0.0083 67,-0.043477,0.052152,-0.052972,0.033714,0.008119,0.003297,0.025124,-0.001927,0.011265,-0.007425,0.007823,-0.000507,0.003394,-0.001251,-0.000873,-0.001237,-0.003081,-0.000964,0.002395
Yoruba:NA18507,-0.628304,0.061947,0.02225,0.021964,0.002154,0.0131 08,-0.048647,0.045921,-0.050722,0.030616,0.004709,0.001649,0.02438,0.0049 54,0.014929,-0.001591,0.010691,0.003167,0.006913,0.001126,-0.002745,0.001978,0.000863,-0.000964,-0.007664
Levant_Natufian:I1072,0.021626,0.151314,-0.036204,-0.141475,0.034776,-0.082831,-0.032196,-0.010384,0.128032,0.012028,0.037837,-0.024878,0.085629,0.002615,0.007872,-0.008088,-0.020601,-0.008742,-0.026019,0.040269,0.007112,0.003462,0.007025,0.002 289,0.000599
Yemenite_Al_Bayda:Y070,0.033009,0.144205,-0.060716,-0.109821,-0.008309,-0.044065,-0.015746,-0.011076,0.055017,-0.002369,0.018675,-0.029973,0.048761,0.003441,-0.0019,0.019225,-0.029467,0.007221,0.002891,0.018384,0.013102,0.015 457,-0.014913,-0.004699,-0.006347
Yemenite_Al_Bayda:Y086,0.036423,0.129988,-0.054682,-0.109175,-0.016926,-0.05522,-0.014336,-0.009461,0.053994,-0.016766,0.001624,-0.020382,0.052031,0.001239,0.013843,0.028639,-0.014081,0.005954,-0.002388,0.012131,0.011105,0.010263,-0.001849,-0.002048,-0.000718
Yemenite_Al_Bayda:Y089,0.045529,0.144205,-0.063733,-0.099484,-0.012925,-0.04769,-0.014571,-0.003692,0.060335,-0.007836,0.01023,-0.027426,0.048909,0.007432,0.004343,0.022805,-0.010561,0.002787,0.005405,0.019885,0.010482,0.010 881,-0.003204,-0.00012,-0.005868
Yemenite_Al_Bayda:Y092,0.036423,0.132019,-0.065619,-0.113374,-0.009848,-0.051316,-0.017156,-0.018692,0.056244,0.001276,0.012666,-0.030573,0.048612,0.002202,0.013165,0.021082,-0.026468,0.010769,0.001508,0.021385,0.012603,0.025 472,-0.009983,0.00964,-0.000359
Yemenite_Al_Bayda:Y097,0.034147,0.141159,-0.061848,-0.105945,-0.006463,-0.05271,-0.011281,-0.009692,0.05604,-0.007472,0.011367,-0.03357,0.051883,0.004542,-0.000407,0.022142,-0.021513,0.012035,0.001508,0.018509,0.00549,0.0202 79,-0.009983,0.005181,-0.005029
Yemenite_Al_Bayda:Y100,0.046667,0.140143,-0.06939,-0.106591,-0.006463,-0.039881,-0.005875,-0.008307,0.043155,-0.002734,0.011205,-0.030873,0.055302,0.00578,0.009229,0.031291,-0.008736,0.004181,-0.003897,0.017258,0.005865,0.014715,-0.004683,-0.001205,-0.004191

I found your model interesting I just replaced yoruba for west african simulated

Distance: 1.3066% / 0.01306628
20.0 MAR_LN
15.5 Yemenite_Al_Bayda
15.1 MAR_EN
13.6 Levant_PPNB
11.8 West_African_(simulated)
10.3 Yamnaya_UKR
10.2 Levant_PPNC
3.5 MAR_Taforalt

maroco
11-22-2020, 08:03 PM
Running this with Mende produces results roughly similar to Yoruba, however I deliberately choose Mende for its archaic ancestry, after all Eurasians have Neanderthal ancestry which can increase attraction to Chimp which could skew the results. By using an African population with Archaic ancestry you can limit the effects of Archaic ancestry on the alpha.

There are a few plausible explanations for those F4 ratios for Dinka.

1. Dinka has ancestry from the African ancestors of Eurasians who lacked Neanderthal admixture. This would mean that Dinka are potentially substantially admixed with Basal Eurasian or ANA-like ancestry.

2. West Africans have ancestry from a group deeper in the tree. This deep ancestry could be Ghost Modern admixture or ZAF_2000BP like admixture.

3.Dinka-Like groups could have contributed to OOA populations differentially to West Africans. Meaning that the OOA population was just closer East Africans phylogenetically.

My personal opinion is that it is probably a mix of 2 or more of these possibilities.

Dinka works fairly well as a proxy for the Neanderthal diluting ancestry in Basal Eurasian rich populations using qpadm (even with Iberomaurusians in the right pops list), and it seems like West Africans definitely have more Basal ancestry than Dinka. So, I can't say which of these factors is primarily responsible for the stat without more ancient African samples.
From what I know west Africans have ana admixture, it’s why I tend to avoid using modern west african samples in ancient models. Shum_Laka Seems to be the best sample to use in ancients these samples don’t seem to have ana admixture

Distance: 0.0005% / 0.00000503
Target: Yoruba
87.5 West_African_(simulated)
12.5 ANA_(simulated)

ThaYamamoto
11-25-2020, 03:55 PM
Somewhat on topic. Here's a PCA generated by making a matrix of F3 outgroup stats (outgroup being Neanderthal).

39463
Cline from South_Africa_2000BP.SG > San/JuHoan > Malawi ancients (the 9000BP one is definitely misdated) > Kenya_PastoralN
Another from a West-Africanish cluster > Dinka > Masai > Kenya_PastoralN > Israel_Peki'in_CA
Pygmy & ShumLaka cluster
...Then Mota out in no-mans land.

This makes sense as I'm increasingly viewing Dinka as a west-African-like group. Where are the original AEA and donor sources for HoAs and when will we find them I wonder.

Mnemonics
01-08-2021, 03:13 AM
I have had a bit more free time to have a closer look at some other samples. What ever the paleo-Eurasian like ancestry found in Mota and Ken_LSA is it seems to be present all over South-East Africa if the Malawi ancients are representative. It even seems to be the source of the minor Eurasian in Shum Laka, which seems to have a decent chunk of SEA hunter-gatherer like ancestry. This ancestry seems to be what is responsible for the attraction between ancient Iranian populations and the Malawi samples.