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I haven't had much luck with medieval samples yet.
This is another good model:
Ireland EBA Rathlin2 + Minoan
pat wt dof chisq p f4rank Ireland_EBA.SG_rath2.SG Greece_Crete_HgCharalambos_EMBA.AG feasible best dofdiff chisqdiff p_nested
00 0 12 12.973786183094607 0.37094889791715024 1 0.7998928166849076 0.20010718331509242 TRUE NA NA NA NA
01 1 13 28.921362767488024 0.006716122080505627 0 1 NA TRUE TRUE 0 -398.4088686573338 1
10 1 13 427.3302314248218 3.732551633024282e-83 0 NA 1 TRUE TRUE NA NA NA
Same rights as previous post
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This run has a really good p-value:
Chi-squared = 4.87
pat wt dof chisq p f4rank Russia_Samara_EBA_Yamnaya.AG Turkey_Central_Catalhoyuk_N.SG Luxembourg_Mesolithic.DG_Loschbour.DG feasible best dofdiff chisqdiff p_nested
000 0 11 4.866129917986197 0.9374759112717503 2 0.44427443972017017 0.4109106704024678 0.14481488987736207 TRUE NA NA NA NA
001 1 12 22.56617198543811 0.03164309064139399 1 0.4636335952541724 0.5363664047458276 NA TRUE TRUE 0 -128.67045269679804 1
010 1 12 151.23662468223614 3.181448605685366e-26 1 0.8518076009691895 NA 0.14819239903081052 TRUE TRUE 0 128.04024231211946 0
100 1 12 23.196382370116694 0.026104235871953096 1 NA 0.7937460664741767 0.20625393352582339 TRUE TRUE NA NA NA
011 2 13 258.8652171497984 9.201495381431885e-48 0 1 NA NA TRUE NA NA NA NA
101 2 13 35.00377467190446 8.455469917767836e-4 0 NA 1 NA TRUE NA NA NA NA
110 2 13 1062.7549585939366 5.763691654010331e-219 0 NA NA 1 TRUE NA NA NA NA
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Received: 724/19 Given: 311/47 |
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Received: 1,924/2 Given: 2,881/14 |
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i found something out about illustrative's qpadm.
kind of embarassing for the illustrative crew.
they have unique datasets for each sample uploaded
not for each user
meaning if you upload a second file, you're creating a second distinct dataset
not just merging your second file with the dataset that contains your first, which is how I would engineer this system if i was in charge
this seems very stupid to me
first of all, this will cost them
because each new upload is another 3Gb of space that they have to pay for
second, people won't be able to model themselves with samples that aren't already on the dataset
and lastly, nothing stops people from uploading more and more and more shit there, continuously eating up the available space on their servers, 3GB by 3GB by 3GB
with my services you can merge as many samples with the dataset as you want (within reason, don't give me too much work like merging 5 samples with the dataset)
so if you want me to model you as your mom + kura araxes, I can
--
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Did some FST runs:
Distances in order from closest to furthest:
Code:Population FST Std. Error ---------------------------------------- Norwegian.DG -0.0049 0.00507 Czech.DG -0.0009 0.00513 English.DG 0.0008 0.00401 French.DG 0.0022 0.00308 Spanish.HO 0.0038 0.00302 Italian_Central.HO 0.0053 0.00311 Scottish.HO 0.0069 0.00339 Italian_South.HO 0.0079 0.00308 Greek_WGA.HO 0.0081 0.00311 Russian.DG 0.0094 0.00306 Basque.DG 0.0110 0.00315 Turkish.DG 0.0125 0.00386 Lebanese_Christian.HO 0.0141 0.00313 Iranian.HO 0.0143 0.00304 Tajik.HO 0.0143 0.00303 Syrian.HO 0.0155 0.00309 Assyrian.HO 0.0161 0.00315 Egyptian.HO 0.0209 0.00303 Saudi.HO 0.0245 0.00330 Balochi.HO 0.0254 0.00310 Moroccan.HO 0.0289 0.00313 GujaratiA.HO 0.0266 0.00337 Turkmen.HO 0.0237 0.00322 Uzbek.HO 0.0243 0.00308 Punjabi.HO 0.0388 0.00328 Uyghur.HO 0.0375 0.00325 Hazara.HO 0.0409 0.00318 Kalash.HO 0.0456 0.00327 Kazakh.HO 0.0488 0.00319 Kyrgyz_Kyrgyzstan.HO 0.0531 0.00337 Eritrea.HO 0.0518 0.00342 Afar_WGA.HO 0.0571 0.00330 Somali.HO 0.0755 0.00316 Mongol.HO 0.0816 0.00331 Thai.HO 0.0943 0.00333 Visayan.HO 0.1091 0.00363 Han.HO 0.1093 0.00336 Korean.HO 0.1096 0.00358 Japanese.HO 0.1104 0.00342 Vietnamese.HO 0.1108 0.00348 Quechua.HO 0.1217 0.00398 Zapotec.HO 0.1365 0.00365 Mixe.HO 0.1630 0.00376 Piapoco.HO 0.1659 0.00401 Pima.HO 0.1677 0.00385 Karitiana.HO 0.2066 0.00398 Surui.HO 0.2273 0.00426 Australian.HO 0.1816 0.00404 Papuan.HO 0.1902 0.00372 BantuKenya.HO 0.1461 0.00337 Yoruba.HO 0.1517 0.00332 Khomani.HO 0.1723 0.00346 Hadza1.HO 0.1890 0.00386 Mbuti.HO 0.2058 0.00353
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