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misnomer001

kolyma right pop steppe eneolithic

misnomer001
Feb 19th, 2020
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  1. allsnps: YES
  2. ## qpAdm version: 1000
  3. seed: 1861356748
  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. CHG
  12. Caucasus_Eneolithic
  13. EEHG
  14. Geoksyur_EN
  15.  
  16. right pops:
  17. Shum_Laka
  18. Morocco_Iberomaurusian
  19. Ganj_Dareh_N
  20. PPN
  21. Pinarbasi
  22. Russia_MA1_HG
  23. Ust_Ishim.DG
  24. Russia_Kostenki14.SG
  25. Kolyma_River
  26. Brazil_LapaDoSanto_9600BP
  27. NW_Iberia_Meso
  28.  
  29. 0 Steppe_Eneolithic 3
  30. 1 CHG 2
  31. 2 Caucasus_Eneolithic 3
  32. 3 EEHG 5
  33. 4 Geoksyur_EN 21
  34. 5 Shum_Laka 4
  35. 6 Morocco_Iberomaurusian 6
  36. 7 Ganj_Dareh_N 8
  37. 8 PPN 11
  38. 9 Pinarbasi 1
  39. 10 Russia_MA1_HG 1
  40. 11 Ust_Ishim.DG 1
  41. 12 Russia_Kostenki14.SG 1
  42. 13 Kolyma_River 1
  43. 14 Brazil_LapaDoSanto_9600BP 5
  44. 15 NW_Iberia_Meso 1
  45. jackknife block size: 0.050
  46. snps: 1150421 indivs: 74
  47. number of blocks for block jackknife: 552
  48. ## ncols: 1150421
  49. coverage: Steppe_Eneolithic 1017729
  50. coverage: CHG 1149558
  51. coverage: Caucasus_Eneolithic 784983
  52. coverage: EEHG 1052093
  53. coverage: Geoksyur_EN 1018577
  54. coverage: Shum_Laka 1082796
  55. coverage: Morocco_Iberomaurusian 1101342
  56. coverage: Ganj_Dareh_N 1057358
  57. coverage: PPN 847771
  58. coverage: Pinarbasi 892975
  59. coverage: Russia_MA1_HG 805960
  60. coverage: Ust_Ishim.DG 1062044
  61. coverage: Russia_Kostenki14.SG 1048972
  62. coverage: Kolyma_River 1094978
  63. coverage: Brazil_LapaDoSanto_9600BP 946991
  64. coverage: NW_Iberia_Meso 995773
  65. dof (jackknife): 466.859
  66. numsnps used: 1150421
  67. codimension 1
  68. f4info:
  69. f4rank: 3 dof: 7 chisq: 17.822 tail: 0.0128004123 dofdiff: 9 chisqdiff: -17.822 taildiff: 1
  70. B:
  71. scale 1.000 1.000 1.000
  72. Morocco_Iberomaurusian 0.126 0.814 -0.268
  73. Ganj_Dareh_N -0.749 -1.293 1.500
  74. PPN -0.232 1.057 1.990
  75. Pinarbasi 0.203 1.888 0.067
  76. Russia_MA1_HG 1.679 -0.857 0.120
  77. Ust_Ishim.DG 0.298 0.308 -1.072
  78. Russia_Kostenki14.SG 0.734 0.536 -0.977
  79. Kolyma_River 1.290 -0.375 -0.875
  80. Brazil_LapaDoSanto_9600BP 1.376 -1.023 0.901
  81. NW_Iberia_Meso 1.524 0.824 -0.132
  82. A:
  83. scale 416.347 1589.111 3255.716
  84. CHG -1.056 0.093 -1.725
  85. Caucasus_Eneolithic -0.776 1.803 0.896
  86. EEHG 1.101 0.379 -0.341
  87. Geoksyur_EN -1.035 -0.771 0.327
  88.  
  89.  
  90. full rank
  91. f4info:
  92. f4rank: 4 dof: 0 chisq: 0.000 tail: 1 dofdiff: 7 chisqdiff: 17.822 taildiff: 0.0128004123
  93. B:
  94. scale 386.308 417.877 385.323 366.018
  95. Morocco_Iberomaurusian -0.052 0.247 0.201 -0.283
  96. Ganj_Dareh_N 0.299 0.037 -1.061 0.868
  97. PPN -0.258 0.801 -0.306 -0.011
  98. Pinarbasi -0.241 0.633 0.296 -0.619
  99. Russia_MA1_HG -1.863 -1.918 1.376 -1.585
  100. Ust_Ishim.DG -0.245 -0.446 0.101 -0.576
  101. Russia_Kostenki14.SG -0.615 -0.591 0.644 -0.950
  102. Kolyma_River -1.049 -1.280 1.421 -1.103
  103. Brazil_LapaDoSanto_9600BP -1.598 -1.507 1.269 -1.103
  104. NW_Iberia_Meso -1.491 -0.872 1.644 -1.614
  105. A:
  106. scale 2.000 2.000 2.000 2.000
  107. CHG 2.000 0.000 0.000 0.000
  108. Caucasus_Eneolithic 0.000 2.000 0.000 0.000
  109. EEHG 0.000 0.000 2.000 0.000
  110. Geoksyur_EN 0.000 0.000 0.000 2.000
  111.  
  112.  
  113. best coefficients: 0.026 0.078 0.475 0.420
  114. Jackknife mean: 0.046231337 0.070237808 0.475044000 0.408486855
  115. std. errors: 0.156 0.077 0.019 0.098
  116.  
  117. error covariance (* 1,000,000)
  118. 24477 -9609 -990 -13878
  119. -9609 5954 24 3631
  120. -990 24 350 615
  121. -13878 3631 615 9632
  122.  
  123.  
  124. summ: Steppe_Eneolithic 4 0.012800 0.046 0.070 0.475 0.408 24477 -9609 -990 -13878 5954 ...
  125. 24 3631 350 615 9632
  126.  
  127. fixed pat wt dof chisq tail prob
  128. 0000 0 7 17.822 0.0128004 0.026 0.078 0.475 0.420
  129. 0001 1 8 44.648 4.2912e-07 0.588 -0.040 0.452 0.000 infeasible
  130. 0010 1 8 66.606 2.32058e-11 22.718 -11.296 0.000 -10.422 infeasible
  131. 0100 1 8 19.437 0.0126878 0.118 0.000 0.480 0.402
  132. 1000 1 8 17.866 0.0222503 0.000 0.088 0.477 0.435
  133. 0011 2 9 106.765 6.68976e-19 10.882 -9.882 0.000 0.000 infeasible
  134. 0101 2 9 44.933 9.49192e-07 0.550 0.000 0.450 0.000
  135. 0110 2 9 124.894 1.3273e-22 4.746 0.000 0.000 -3.746 infeasible
  136. 1001 2 9 105.728 1.08631e-18 0.000 0.544 0.456 0.000
  137. 1010 2 9 260.930 0 0.000 3.443 0.000 -2.443 infeasible
  138. 1100 2 9 21.444 0.0108181 0.000 0.000 0.492 0.508
  139. 0111 3 10 344.164 0 1.000 0.000 0.000 0.000
  140. 1011 3 10 405.648 0 0.000 1.000 0.000 0.000
  141. 1101 3 10 637.877 0 0.000 0.000 1.000 0.000
  142. 1110 3 10 768.764 0 0.000 0.000 0.000 1.000
  143. best pat: 0000 0.0128004 - -
  144. best pat: 1000 0.0222503 chi(nested): 0.045 p-value for nested model: 0.832635
  145. best pat: 1100 0.0108181 chi(nested): 3.578 p-value for nested model: 0.0585625
  146. best pat: 0111 6.89537e-68 not nested
  147.  
  148. coeffs: 0.026 0.078 0.475 0.420
  149.  
  150. ## dscore:: f_4(Base, Fit, Rbase, right2)
  151. ## genstat:: f_4(Base, Fit, right1, right2)
  152.  
  153. details: CHG Morocco_Iberomaurusian -0.000136 -0.446791
  154. details: Caucasus_Eneolithic Morocco_Iberomaurusian 0.000591 1.986061
  155. details: EEHG Morocco_Iberomaurusian 0.000523 1.877461
  156. details: Geoksyur_EN Morocco_Iberomaurusian -0.000774 -3.359392
  157. dscore: Morocco_Iberomaurusian f4: -0.000034 Z: -0.162057
  158.  
  159. details: CHG Ganj_Dareh_N 0.000775 2.445485
  160. details: Caucasus_Eneolithic Ganj_Dareh_N 0.000089 0.282069
  161. details: EEHG Ganj_Dareh_N -0.002754 -10.057046
  162. details: Geoksyur_EN Ganj_Dareh_N 0.002372 9.497584
  163. dscore: Ganj_Dareh_N f4: -0.000286 Z: -1.328676
  164.  
  165. details: CHG PPN -0.000668 -2.253690
  166. details: Caucasus_Eneolithic PPN 0.001917 5.914370
  167. details: EEHG PPN -0.000794 -3.078179
  168. details: Geoksyur_EN PPN -0.000030 -0.124511
  169. dscore: PPN f4: -0.000257 Z: -1.262322
  170.  
  171. details: CHG Pinarbasi -0.000623 -1.673334
  172. details: Caucasus_Eneolithic Pinarbasi 0.001516 3.749137
  173. details: EEHG Pinarbasi 0.000769 2.351088
  174. details: Geoksyur_EN Pinarbasi -0.001692 -5.578917
  175. dscore: Pinarbasi f4: -0.000243 Z: -0.942921
  176.  
  177. details: CHG Russia_MA1_HG -0.004822 -11.774946
  178. details: Caucasus_Eneolithic Russia_MA1_HG -0.004589 -11.714633
  179. details: EEHG Russia_MA1_HG 0.003571 10.092977
  180. details: Geoksyur_EN Russia_MA1_HG -0.004329 -13.553580
  181. dscore: Russia_MA1_HG f4: -0.000607 Z: -2.198737
  182.  
  183. details: CHG Ust_Ishim.DG -0.000634 -1.681319
  184. details: Caucasus_Eneolithic Ust_Ishim.DG -0.001067 -2.861186
  185. details: EEHG Ust_Ishim.DG 0.000263 0.792387
  186. details: Geoksyur_EN Ust_Ishim.DG -0.001572 -5.604888
  187. dscore: Ust_Ishim.DG f4: -0.000636 Z: -2.552190
  188.  
  189. details: CHG Russia_Kostenki14.SG -0.001592 -3.948663
  190. details: Caucasus_Eneolithic Russia_Kostenki14.SG -0.001414 -3.518169
  191. details: EEHG Russia_Kostenki14.SG 0.001671 4.518691
  192. details: Geoksyur_EN Russia_Kostenki14.SG -0.002595 -8.766143
  193. dscore: Russia_Kostenki14.SG f4: -0.000448 Z: -1.683235
  194.  
  195. details: CHG Kolyma_River -0.002714 -6.893322
  196. details: Caucasus_Eneolithic Kolyma_River -0.003064 -7.937666
  197. details: EEHG Kolyma_River 0.003688 9.743123
  198. details: Geoksyur_EN Kolyma_River -0.003013 -10.377606
  199. dscore: Kolyma_River f4: 0.000177 Z: 0.654063
  200.  
  201. details: CHG Brazil_LapaDoSanto_9600BP -0.004137 -12.002542
  202. details: Caucasus_Eneolithic Brazil_LapaDoSanto_9600BP -0.003605 -9.865825
  203. details: EEHG Brazil_LapaDoSanto_9600BP 0.003294 10.764582
  204. details: Geoksyur_EN Brazil_LapaDoSanto_9600BP -0.003014 -11.444041
  205. dscore: Brazil_LapaDoSanto_9600BP f4: -0.000091 Z: -0.388204
  206.  
  207. details: CHG NW_Iberia_Meso -0.003858 -9.310636
  208. details: Caucasus_Eneolithic NW_Iberia_Meso -0.002086 -4.766873
  209. details: EEHG NW_Iberia_Meso 0.004267 11.491944
  210. details: Geoksyur_EN NW_Iberia_Meso -0.004410 -14.489993
  211. dscore: NW_Iberia_Meso f4: -0.000088 Z: -0.324486
  212.  
  213. gendstat: Shum_Laka Morocco_Iberomaurusian -0.162
  214. gendstat: Shum_Laka Ganj_Dareh_N -1.329
  215. gendstat: Shum_Laka PPN -1.262
  216. gendstat: Shum_Laka Pinarbasi -0.943
  217. gendstat: Shum_Laka Russia_MA1_HG -2.199
  218. gendstat: Shum_Laka Ust_Ishim.DG -2.552
  219. gendstat: Shum_Laka Russia_Kostenki14.SG -1.683
  220. gendstat: Shum_Laka Kolyma_River 0.654
  221. gendstat: Shum_Laka Brazil_LapaDoSanto_9600BP -0.388
  222. gendstat: Shum_Laka NW_Iberia_Meso -0.324
  223. gendstat: Morocco_Iberomaurusian Ganj_Dareh_N -1.026
  224. gendstat: Morocco_Iberomaurusian PPN -0.975
  225. gendstat: Morocco_Iberomaurusian Pinarbasi -0.756
  226. gendstat: Morocco_Iberomaurusian Russia_MA1_HG -1.919
  227. gendstat: Morocco_Iberomaurusian Ust_Ishim.DG -2.185
  228. gendstat: Morocco_Iberomaurusian Russia_Kostenki14.SG -1.493
  229. gendstat: Morocco_Iberomaurusian Kolyma_River 0.726
  230. gendstat: Morocco_Iberomaurusian Brazil_LapaDoSanto_9600BP -0.218
  231. gendstat: Morocco_Iberomaurusian NW_Iberia_Meso -0.183
  232. gendstat: Ganj_Dareh_N PPN 0.132
  233. gendstat: Ganj_Dareh_N Pinarbasi 0.159
  234. gendstat: Ganj_Dareh_N Russia_MA1_HG -1.109
  235. gendstat: Ganj_Dareh_N Ust_Ishim.DG -1.297
  236. gendstat: Ganj_Dareh_N Russia_Kostenki14.SG -0.595
  237. gendstat: Ganj_Dareh_N Kolyma_River 1.718
  238. gendstat: Ganj_Dareh_N Brazil_LapaDoSanto_9600BP 0.769
  239. gendstat: Ganj_Dareh_N NW_Iberia_Meso 0.673
  240. gendstat: PPN Pinarbasi 0.059
  241. gendstat: PPN Russia_MA1_HG -1.195
  242. gendstat: PPN Ust_Ishim.DG -1.358
  243. gendstat: PPN Russia_Kostenki14.SG -0.710
  244. gendstat: PPN Kolyma_River 1.491
  245. gendstat: PPN Brazil_LapaDoSanto_9600BP 0.667
  246. gendstat: PPN NW_Iberia_Meso 0.626
  247. gendstat: Pinarbasi Russia_MA1_HG -1.116
  248. gendstat: Pinarbasi Ust_Ishim.DG -1.228
  249. gendstat: Pinarbasi Russia_Kostenki14.SG -0.679
  250. gendstat: Pinarbasi Kolyma_River 1.325
  251. gendstat: Pinarbasi Brazil_LapaDoSanto_9600BP 0.504
  252. gendstat: Pinarbasi NW_Iberia_Meso 0.501
  253. gendstat: Russia_MA1_HG Ust_Ishim.DG -0.086
  254. gendstat: Russia_MA1_HG Russia_Kostenki14.SG 0.499
  255. gendstat: Russia_MA1_HG Kolyma_River 2.572
  256. gendstat: Russia_MA1_HG Brazil_LapaDoSanto_9600BP 1.913
  257. gendstat: Russia_MA1_HG NW_Iberia_Meso 1.512
  258. gendstat: Ust_Ishim.DG Russia_Kostenki14.SG 0.594
  259. gendstat: Ust_Ishim.DG Kolyma_River 2.613
  260. gendstat: Ust_Ishim.DG Brazil_LapaDoSanto_9600BP 1.869
  261. gendstat: Ust_Ishim.DG NW_Iberia_Meso 1.722
  262. gendstat: Russia_Kostenki14.SG Kolyma_River 2.066
  263. gendstat: Russia_Kostenki14.SG Brazil_LapaDoSanto_9600BP 1.299
  264. gendstat: Russia_Kostenki14.SG NW_Iberia_Meso 1.168
  265. gendstat: Kolyma_River Brazil_LapaDoSanto_9600BP -1.098
  266. gendstat: Kolyma_River NW_Iberia_Meso -0.817
  267. gendstat: Brazil_LapaDoSanto_9600BP NW_Iberia_Meso 0.009
  268.  
  269. ##end of qpAdm: 246.875 seconds cpu 1349.120 Mbytes in use
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