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misnomer001

3 way steppe eneolithic kolyma right pop

misnomer001
Feb 19th, 2020
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  1. allsnps: YES
  2. ## qpAdm version: 1000
  3. seed: 1858895974
  4. read 1073741824 bytes
  5. read 1350149235 bytes
  6. packed geno read OK
  7. end of inpack
  8.  
  9. left pops:
  10. Steppe_Eneolithic
  11. Caucasus_Eneolithic
  12. EEHG
  13. Geoksyur_EN
  14.  
  15. right pops:
  16. Shum_Laka
  17. Morocco_Iberomaurusian
  18. Ganj_Dareh_N
  19. PPN
  20. Pinarbasi
  21. Russia_MA1_HG
  22. Ust_Ishim.DG
  23. Russia_Kostenki14.SG
  24. Kolyma_River
  25. Brazil_LapaDoSanto_9600BP
  26. NW_Iberia_Meso
  27.  
  28. 0 Steppe_Eneolithic 3
  29. 1 Caucasus_Eneolithic 3
  30. 2 EEHG 5
  31. 3 Geoksyur_EN 21
  32. 4 Shum_Laka 4
  33. 5 Morocco_Iberomaurusian 6
  34. 6 Ganj_Dareh_N 8
  35. 7 PPN 11
  36. 8 Pinarbasi 1
  37. 9 Russia_MA1_HG 1
  38. 10 Ust_Ishim.DG 1
  39. 11 Russia_Kostenki14.SG 1
  40. 12 Kolyma_River 1
  41. 13 Brazil_LapaDoSanto_9600BP 5
  42. 14 NW_Iberia_Meso 1
  43. jackknife block size: 0.050
  44. snps: 1150372 indivs: 72
  45. number of blocks for block jackknife: 552
  46. ## ncols: 1150372
  47. coverage: Steppe_Eneolithic 1017729
  48. coverage: Caucasus_Eneolithic 784983
  49. coverage: EEHG 1052093
  50. coverage: Geoksyur_EN 1018577
  51. coverage: Shum_Laka 1082796
  52. coverage: Morocco_Iberomaurusian 1101342
  53. coverage: Ganj_Dareh_N 1057358
  54. coverage: PPN 847771
  55. coverage: Pinarbasi 892975
  56. coverage: Russia_MA1_HG 805960
  57. coverage: Ust_Ishim.DG 1062044
  58. coverage: Russia_Kostenki14.SG 1048972
  59. coverage: Kolyma_River 1094978
  60. coverage: Brazil_LapaDoSanto_9600BP 946991
  61. coverage: NW_Iberia_Meso 995773
  62. dof (jackknife): 466.369
  63. numsnps used: 1150372
  64. codimension 1
  65. f4info:
  66. f4rank: 2 dof: 8 chisq: 17.833 tail: 0.0225178121 dofdiff: 10 chisqdiff: -17.833 taildiff: 1
  67. B:
  68. scale 1.000 1.000
  69. Morocco_Iberomaurusian 0.143 0.801
  70. Ganj_Dareh_N -0.828 -1.205
  71. PPN -0.338 1.300
  72. Pinarbasi 0.204 1.941
  73. Russia_MA1_HG 1.641 -0.685
  74. Ust_Ishim.DG 0.357 0.201
  75. Russia_Kostenki14.SG 0.780 0.490
  76. Kolyma_River 1.318 -0.371
  77. Brazil_LapaDoSanto_9600BP 1.299 -0.793
  78. NW_Iberia_Meso 1.512 0.966
  79. A:
  80. scale 415.701 1396.811
  81. Caucasus_Eneolithic -0.843 1.573
  82. EEHG 1.101 0.308
  83. Geoksyur_EN -1.038 -0.657
  84.  
  85.  
  86. full rank
  87. f4info:
  88. f4rank: 3 dof: 0 chisq: 0.000 tail: 1 dofdiff: 8 chisqdiff: 17.833 taildiff: 0.0225178121
  89. B:
  90. scale 417.877 385.323 366.018
  91. Morocco_Iberomaurusian 0.247 0.201 -0.283
  92. Ganj_Dareh_N 0.037 -1.061 0.868
  93. PPN 0.801 -0.306 -0.011
  94. Pinarbasi 0.633 0.296 -0.619
  95. Russia_MA1_HG -1.918 1.376 -1.585
  96. Ust_Ishim.DG -0.446 0.101 -0.576
  97. Russia_Kostenki14.SG -0.591 0.644 -0.950
  98. Kolyma_River -1.280 1.421 -1.103
  99. Brazil_LapaDoSanto_9600BP -1.507 1.269 -1.103
  100. NW_Iberia_Meso -0.872 1.644 -1.614
  101. A:
  102. scale 1.732 1.732 1.732
  103. Caucasus_Eneolithic 1.732 0.000 0.000
  104. EEHG 0.000 1.732 0.000
  105. Geoksyur_EN 0.000 0.000 1.732
  106.  
  107.  
  108. best coefficients: 0.088 0.477 0.435
  109. Jackknife mean: 0.089001971 0.477080681 0.433917348
  110. std. errors: 0.047 0.018 0.042
  111.  
  112. error covariance (* 1,000,000)
  113. 2223 -372 -1851
  114. -372 315 57
  115. -1851 57 1794
  116.  
  117.  
  118. summ: Steppe_Eneolithic 3 0.022518 0.089 0.477 0.434 2223 -372 -1851 315 57 ...
  119. 1794
  120.  
  121. fixed pat wt dof chisq tail prob
  122. 000 0 8 17.833 0.0225178 0.088 0.477 0.435
  123. 001 1 9 105.957 9.76236e-19 0.544 0.456 0.000
  124. 010 1 9 263.421 0 3.454 0.000 -2.454 infeasible
  125. 100 1 9 21.389 0.0110305 0.000 0.493 0.507
  126. 011 2 10 406.886 0 1.000 0.000 0.000
  127. 101 2 10 640.962 0 0.000 1.000 0.000
  128. 110 2 10 773.547 0 0.000 0.000 1.000
  129. best pat: 000 0.0225178 - -
  130. best pat: 100 0.0110305 chi(nested): 3.557 p-value for nested model: 0.0593102
  131. best pat: 011 3.22148e-81 not nested
  132.  
  133. coeffs: 0.088 0.477 0.435
  134.  
  135. ## dscore:: f_4(Base, Fit, Rbase, right2)
  136. ## genstat:: f_4(Base, Fit, right1, right2)
  137.  
  138. details: Caucasus_Eneolithic Morocco_Iberomaurusian 0.000591 1.988708
  139. details: EEHG Morocco_Iberomaurusian 0.000523 1.879872
  140. details: Geoksyur_EN Morocco_Iberomaurusian -0.000774 -3.365838
  141. dscore: Morocco_Iberomaurusian f4: -0.000035 Z: -0.165798
  142.  
  143. details: Caucasus_Eneolithic Ganj_Dareh_N 0.000089 0.282355
  144. details: EEHG Ganj_Dareh_N -0.002754 -10.071309
  145. details: Geoksyur_EN Ganj_Dareh_N 0.002372 9.514067
  146. dscore: Ganj_Dareh_N f4: -0.000275 Z: -1.276322
  147.  
  148. details: Caucasus_Eneolithic PPN 0.001917 5.919701
  149. details: EEHG PPN -0.000794 -3.083660
  150. details: Geoksyur_EN PPN -0.000030 -0.124736
  151. dscore: PPN f4: -0.000223 Z: -1.084555
  152.  
  153. details: Caucasus_Eneolithic Pinarbasi 0.001516 3.752805
  154. details: EEHG Pinarbasi 0.000769 2.353692
  155. details: Geoksyur_EN Pinarbasi -0.001692 -5.586188
  156. dscore: Pinarbasi f4: -0.000235 Z: -0.906664
  157.  
  158. details: Caucasus_Eneolithic Russia_MA1_HG -0.004589 -11.719184
  159. details: EEHG Russia_MA1_HG 0.003571 10.098986
  160. details: Geoksyur_EN Russia_MA1_HG -0.004329 -13.563885
  161. dscore: Russia_MA1_HG f4: -0.000582 Z: -2.095766
  162.  
  163. details: Caucasus_Eneolithic Ust_Ishim.DG -0.001067 -2.863488
  164. details: EEHG Ust_Ishim.DG 0.000263 0.793005
  165. details: Geoksyur_EN Ust_Ishim.DG -0.001572 -5.611751
  166. dscore: Ust_Ishim.DG f4: -0.000652 Z: -2.609183
  167.  
  168. details: Caucasus_Eneolithic Russia_Kostenki14.SG -0.001414 -3.520536
  169. details: EEHG Russia_Kostenki14.SG 0.001671 4.520924
  170. details: Geoksyur_EN Russia_Kostenki14.SG -0.002595 -8.773108
  171. dscore: Russia_Kostenki14.SG f4: -0.000455 Z: -1.705106
  172.  
  173. details: Caucasus_Eneolithic Kolyma_River -0.003064 -7.945379
  174. details: EEHG Kolyma_River 0.003688 9.747814
  175. details: Geoksyur_EN Kolyma_River -0.003013 -10.389614
  176. dscore: Kolyma_River f4: 0.000181 Z: 0.665683
  177.  
  178. details: Caucasus_Eneolithic Brazil_LapaDoSanto_9600BP -0.003605 -9.873689
  179. details: EEHG Brazil_LapaDoSanto_9600BP 0.003294 10.777616
  180. details: Geoksyur_EN Brazil_LapaDoSanto_9600BP -0.003014 -11.464454
  181. dscore: Brazil_LapaDoSanto_9600BP f4: -0.000056 Z: -0.237189
  182.  
  183. details: Caucasus_Eneolithic NW_Iberia_Meso -0.002086 -4.768842
  184. details: EEHG NW_Iberia_Meso 0.004267 11.497324
  185. details: Geoksyur_EN NW_Iberia_Meso -0.004410 -14.499767
  186. dscore: NW_Iberia_Meso f4: -0.000064 Z: -0.234756
  187.  
  188. gendstat: Shum_Laka Morocco_Iberomaurusian -0.166
  189. gendstat: Shum_Laka Ganj_Dareh_N -1.276
  190. gendstat: Shum_Laka PPN -1.085
  191. gendstat: Shum_Laka Pinarbasi -0.907
  192. gendstat: Shum_Laka Russia_MA1_HG -2.096
  193. gendstat: Shum_Laka Ust_Ishim.DG -2.609
  194. gendstat: Shum_Laka Russia_Kostenki14.SG -1.705
  195. gendstat: Shum_Laka Kolyma_River 0.666
  196. gendstat: Shum_Laka Brazil_LapaDoSanto_9600BP -0.237
  197. gendstat: Shum_Laka NW_Iberia_Meso -0.235
  198. gendstat: Morocco_Iberomaurusian Ganj_Dareh_N -0.978
  199. gendstat: Morocco_Iberomaurusian PPN -0.816
  200. gendstat: Morocco_Iberomaurusian Pinarbasi -0.720
  201. gendstat: Morocco_Iberomaurusian Russia_MA1_HG -1.821
  202. gendstat: Morocco_Iberomaurusian Ust_Ishim.DG -2.235
  203. gendstat: Morocco_Iberomaurusian Russia_Kostenki14.SG -1.512
  204. gendstat: Morocco_Iberomaurusian Kolyma_River 0.740
  205. gendstat: Morocco_Iberomaurusian Brazil_LapaDoSanto_9600BP -0.079
  206. gendstat: Morocco_Iberomaurusian NW_Iberia_Meso -0.097
  207. gendstat: Ganj_Dareh_N PPN 0.245
  208. gendstat: Ganj_Dareh_N Pinarbasi 0.151
  209. gendstat: Ganj_Dareh_N Russia_MA1_HG -1.053
  210. gendstat: Ganj_Dareh_N Ust_Ishim.DG -1.390
  211. gendstat: Ganj_Dareh_N Russia_Kostenki14.SG -0.656
  212. gendstat: Ganj_Dareh_N Kolyma_River 1.689
  213. gendstat: Ganj_Dareh_N Brazil_LapaDoSanto_9600BP 0.864
  214. gendstat: Ganj_Dareh_N NW_Iberia_Meso 0.719
  215. gendstat: PPN Pinarbasi -0.047
  216. gendstat: PPN Russia_MA1_HG -1.221
  217. gendstat: PPN Ust_Ishim.DG -1.531
  218. gendstat: PPN Russia_Kostenki14.SG -0.860
  219. gendstat: PPN Kolyma_River 1.380
  220. gendstat: PPN Brazil_LapaDoSanto_9600BP 0.667
  221. gendstat: PPN NW_Iberia_Meso 0.586
  222. gendstat: Pinarbasi Russia_MA1_HG -1.060
  223. gendstat: Pinarbasi Ust_Ishim.DG -1.298
  224. gendstat: Pinarbasi Russia_Kostenki14.SG -0.725
  225. gendstat: Pinarbasi Kolyma_River 1.306
  226. gendstat: Pinarbasi Brazil_LapaDoSanto_9600BP 0.592
  227. gendstat: Pinarbasi NW_Iberia_Meso 0.552
  228. gendstat: Russia_MA1_HG Ust_Ishim.DG -0.208
  229. gendstat: Russia_MA1_HG Russia_Kostenki14.SG 0.398
  230. gendstat: Russia_MA1_HG Kolyma_River 2.493
  231. gendstat: Russia_MA1_HG Brazil_LapaDoSanto_9600BP 1.946
  232. gendstat: Russia_MA1_HG NW_Iberia_Meso 1.503
  233. gendstat: Ust_Ishim.DG Russia_Kostenki14.SG 0.623
  234. gendstat: Ust_Ishim.DG Kolyma_River 2.672
  235. gendstat: Ust_Ishim.DG Brazil_LapaDoSanto_9600BP 2.039
  236. gendstat: Ust_Ishim.DG NW_Iberia_Meso 1.845
  237. gendstat: Russia_Kostenki14.SG Kolyma_River 2.090
  238. gendstat: Russia_Kostenki14.SG Brazil_LapaDoSanto_9600BP 1.445
  239. gendstat: Russia_Kostenki14.SG NW_Iberia_Meso 1.265
  240. gendstat: Kolyma_River Brazil_LapaDoSanto_9600BP -0.968
  241. gendstat: Kolyma_River NW_Iberia_Meso -0.751
  242. gendstat: Brazil_LapaDoSanto_9600BP NW_Iberia_Meso -0.027
  243.  
  244. ##end of qpAdm: 235.396 seconds cpu 1293.599 Mbytes in use
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