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misnomer001

steppe eneolithic geoksyur pass davidski right

misnomer001
Feb 19th, 2020
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  1. allsnps: YES
  2. ## qpAdm version: 1000
  3. seed: 1991705454
  4. read 1073741824 bytes
  5. read 1339052118 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. Russia_Shamanka_EN.SG
  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 Russia_Shamanka_EN.SG 10
  41. 13 Brazil_LapaDoSanto_9600BP 5
  42. 14 NW_Iberia_Meso 1
  43. jackknife block size: 0.050
  44. snps: 1150444 indivs: 81
  45. number of blocks for block jackknife: 552
  46. ## ncols: 1150444
  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: Russia_Shamanka_EN.SG 1149998
  60. coverage: Brazil_LapaDoSanto_9600BP 946991
  61. coverage: NW_Iberia_Meso 995773
  62. dof (jackknife): 466.137
  63. numsnps used: 1150444
  64. codimension 1
  65. f4info:
  66. f4rank: 2 dof: 8 chisq: 15.743 tail: 0.0462155867 dofdiff: 10 chisqdiff: -15.743 taildiff: 1
  67. B:
  68. scale 1.000 1.000
  69. Morocco_Iberomaurusian 0.144 0.808
  70. Ganj_Dareh_N -0.861 -1.171
  71. PPN -0.349 1.298
  72. Pinarbasi 0.220 1.935
  73. Russia_MA1_HG 1.715 -0.718
  74. Ust_Ishim.DG 0.375 0.219
  75. Russia_Kostenki14.SG 0.819 0.504
  76. Russia_Shamanka_EN.SG 0.966 -0.425
  77. Brazil_LapaDoSanto_9600BP 1.361 -0.778
  78. NW_Iberia_Meso 1.591 0.972
  79. A:
  80. scale 434.476 1391.522
  81. Caucasus_Eneolithic -0.840 1.570
  82. EEHG 1.093 0.291
  83. Geoksyur_EN -1.049 -0.672
  84.  
  85.  
  86. full rank
  87. f4info:
  88. f4rank: 3 dof: 0 chisq: 0.000 tail: 1 dofdiff: 8 chisqdiff: 15.743 taildiff: 0.0462155867
  89. B:
  90. scale 430.827 411.021 376.536
  91. Morocco_Iberomaurusian 0.255 0.215 -0.292
  92. Ganj_Dareh_N 0.038 -1.132 0.893
  93. PPN 0.826 -0.326 -0.011
  94. Pinarbasi 0.653 0.316 -0.637
  95. Russia_MA1_HG -1.977 1.468 -1.630
  96. Ust_Ishim.DG -0.460 0.108 -0.592
  97. Russia_Kostenki14.SG -0.609 0.687 -0.977
  98. Russia_Shamanka_EN.SG -1.055 0.959 -0.839
  99. Brazil_LapaDoSanto_9600BP -1.553 1.354 -1.135
  100. NW_Iberia_Meso -0.899 1.754 -1.660
  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: 0.093 0.481 0.426
  109. Jackknife mean: 0.094206486 0.480576192 0.425217322
  110. std. errors: 0.047 0.018 0.042
  111.  
  112. error covariance (* 1,000,000)
  113. 2217 -368 -1849
  114. -368 323 45
  115. -1849 45 1804
  116.  
  117.  
  118. summ: Steppe_Eneolithic 3 0.046216 0.094 0.481 0.425 2217 -368 -1849 323 45 ...
  119. 1804
  120.  
  121. fixed pat wt dof chisq tail prob
  122. 000 0 8 15.743 0.0462156 0.093 0.481 0.426
  123. 001 1 9 101.499 7.82597e-18 0.535 0.465 0.000
  124. 010 1 9 268.363 0 3.430 0.000 -2.430 infeasible
  125. 100 1 9 19.719 0.0197262 0.000 0.497 0.503
  126. 011 2 10 413.449 0 1.000 0.000 0.000
  127. 101 2 10 608.678 0 0.000 1.000 0.000
  128. 110 2 10 752.627 0 0.000 0.000 1.000
  129. best pat: 000 0.0462156 - -
  130. best pat: 100 0.0197262 chi(nested): 3.977 p-value for nested model: 0.0461356
  131. best pat: 011 1.28994e-82 not nested
  132.  
  133. coeffs: 0.093 0.481 0.426
  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 1.988994
  139. details: EEHG Morocco_Iberomaurusian 0.000523 1.879870
  140. details: Geoksyur_EN Morocco_Iberomaurusian -0.000774 -3.366027
  141. dscore: Morocco_Iberomaurusian f4: -0.000023 Z: -0.111008
  142.  
  143. details: Caucasus_Eneolithic Ganj_Dareh_N 0.000089 0.282354
  144. details: EEHG Ganj_Dareh_N -0.002754 -10.071309
  145. details: Geoksyur_EN Ganj_Dareh_N 0.002372 9.514656
  146. dscore: Ganj_Dareh_N f4: -0.000305 Z: -1.414323
  147.  
  148. details: Caucasus_Eneolithic PPN 0.001917 5.919139
  149. details: EEHG PPN -0.000794 -3.084020
  150. details: Geoksyur_EN PPN -0.000030 -0.124734
  151. dscore: PPN f4: -0.000215 Z: -1.048736
  152.  
  153. details: Caucasus_Eneolithic Pinarbasi 0.001516 3.753303
  154. details: EEHG Pinarbasi 0.000769 2.353942
  155. details: Geoksyur_EN Pinarbasi -0.001692 -5.587423
  156. dscore: Pinarbasi f4: -0.000209 Z: -0.809322
  157.  
  158. details: Caucasus_Eneolithic Russia_MA1_HG -0.004589 -11.717253
  159. details: EEHG Russia_MA1_HG 0.003571 10.098559
  160. details: Geoksyur_EN Russia_MA1_HG -0.004329 -13.561937
  161. dscore: Russia_MA1_HG f4: -0.000556 Z: -2.000574
  162.  
  163. details: Caucasus_Eneolithic Ust_Ishim.DG -0.001067 -2.863805
  164. details: EEHG Ust_Ishim.DG 0.000263 0.792977
  165. details: Geoksyur_EN Ust_Ishim.DG -0.001572 -5.612266
  166. dscore: Ust_Ishim.DG f4: -0.000643 Z: -2.572522
  167.  
  168. details: Caucasus_Eneolithic Russia_Kostenki14.SG -0.001414 -3.520300
  169. details: EEHG Russia_Kostenki14.SG 0.001671 4.520938
  170. details: Geoksyur_EN Russia_Kostenki14.SG -0.002595 -8.770788
  171. dscore: Russia_Kostenki14.SG f4: -0.000433 Z: -1.624565
  172.  
  173. details: Caucasus_Eneolithic Russia_Shamanka_EN.SG -0.002449 -7.732224
  174. details: EEHG Russia_Shamanka_EN.SG 0.002333 8.254817
  175. details: Geoksyur_EN Russia_Shamanka_EN.SG -0.002228 -8.745829
  176. dscore: Russia_Shamanka_EN.SG f4: -0.000056 Z: -0.252596
  177.  
  178. details: Caucasus_Eneolithic Brazil_LapaDoSanto_9600BP -0.003605 -9.874043
  179. details: EEHG Brazil_LapaDoSanto_9600BP 0.003294 10.777573
  180. details: Geoksyur_EN Brazil_LapaDoSanto_9600BP -0.003014 -11.465786
  181. dscore: Brazil_LapaDoSanto_9600BP f4: -0.000036 Z: -0.155466
  182.  
  183. details: Caucasus_Eneolithic NW_Iberia_Meso -0.002086 -4.768621
  184. details: EEHG NW_Iberia_Meso 0.004267 11.495828
  185. details: Geoksyur_EN NW_Iberia_Meso -0.004410 -14.494294
  186. dscore: NW_Iberia_Meso f4: -0.000021 Z: -0.078747
  187.  
  188. gendstat: Shum_Laka Morocco_Iberomaurusian -0.111
  189. gendstat: Shum_Laka Ganj_Dareh_N -1.414
  190. gendstat: Shum_Laka PPN -1.049
  191. gendstat: Shum_Laka Pinarbasi -0.809
  192. gendstat: Shum_Laka Russia_MA1_HG -2.001
  193. gendstat: Shum_Laka Ust_Ishim.DG -2.573
  194. gendstat: Shum_Laka Russia_Kostenki14.SG -1.625
  195. gendstat: Shum_Laka Russia_Shamanka_EN.SG -0.253
  196. gendstat: Shum_Laka Brazil_LapaDoSanto_9600BP -0.155
  197. gendstat: Shum_Laka NW_Iberia_Meso -0.079
  198. gendstat: Morocco_Iberomaurusian Ganj_Dareh_N -1.146
  199. gendstat: Morocco_Iberomaurusian PPN -0.835
  200. gendstat: Morocco_Iberomaurusian Pinarbasi -0.671
  201. gendstat: Morocco_Iberomaurusian Russia_MA1_HG -1.772
  202. gendstat: Morocco_Iberomaurusian Ust_Ishim.DG -2.243
  203. gendstat: Morocco_Iberomaurusian Russia_Kostenki14.SG -1.477
  204. gendstat: Morocco_Iberomaurusian Russia_Shamanka_EN.SG -0.143
  205. gendstat: Morocco_Iberomaurusian Brazil_LapaDoSanto_9600BP -0.050
  206. gendstat: Morocco_Iberomaurusian NW_Iberia_Meso 0.007
  207. gendstat: Ganj_Dareh_N PPN 0.418
  208. gendstat: Ganj_Dareh_N Pinarbasi 0.353
  209. gendstat: Ganj_Dareh_N Russia_MA1_HG -0.860
  210. gendstat: Ganj_Dareh_N Ust_Ishim.DG -1.247
  211. gendstat: Ganj_Dareh_N Russia_Kostenki14.SG -0.470
  212. gendstat: Ganj_Dareh_N Russia_Shamanka_EN.SG 1.157
  213. gendstat: Ganj_Dareh_N Brazil_LapaDoSanto_9600BP 1.055
  214. gendstat: Ganj_Dareh_N NW_Iberia_Meso 0.963
  215. gendstat: PPN Pinarbasi 0.024
  216. gendstat: PPN Russia_MA1_HG -1.156
  217. gendstat: PPN Ust_Ishim.DG -1.525
  218. gendstat: PPN Russia_Kostenki14.SG -0.808
  219. gendstat: PPN Russia_Shamanka_EN.SG 0.697
  220. gendstat: PPN Brazil_LapaDoSanto_9600BP 0.713
  221. gendstat: PPN NW_Iberia_Meso 0.715
  222. gendstat: Pinarbasi Russia_MA1_HG -1.057
  223. gendstat: Pinarbasi Ust_Ishim.DG -1.348
  224. gendstat: Pinarbasi Russia_Kostenki14.SG -0.738
  225. gendstat: Pinarbasi Russia_Shamanka_EN.SG 0.553
  226. gendstat: Pinarbasi Brazil_LapaDoSanto_9600BP 0.572
  227. gendstat: Pinarbasi NW_Iberia_Meso 0.607
  228. gendstat: Russia_MA1_HG Ust_Ishim.DG -0.259
  229. gendstat: Russia_MA1_HG Russia_Kostenki14.SG 0.382
  230. gendstat: Russia_MA1_HG Russia_Shamanka_EN.SG 1.904
  231. gendstat: Russia_MA1_HG Brazil_LapaDoSanto_9600BP 1.919
  232. gendstat: Russia_MA1_HG NW_Iberia_Meso 1.548
  233. gendstat: Ust_Ishim.DG Russia_Kostenki14.SG 0.660
  234. gendstat: Ust_Ishim.DG Russia_Shamanka_EN.SG 2.232
  235. gendstat: Ust_Ishim.DG Brazil_LapaDoSanto_9600BP 2.072
  236. gendstat: Ust_Ishim.DG NW_Iberia_Meso 1.948
  237. gendstat: Russia_Kostenki14.SG Russia_Shamanka_EN.SG 1.528
  238. gendstat: Russia_Kostenki14.SG Brazil_LapaDoSanto_9600BP 1.436
  239. gendstat: Russia_Kostenki14.SG NW_Iberia_Meso 1.333
  240. gendstat: Russia_Shamanka_EN.SG Brazil_LapaDoSanto_9600BP 0.104
  241. gendstat: Russia_Shamanka_EN.SG NW_Iberia_Meso 0.125
  242. gendstat: Brazil_LapaDoSanto_9600BP NW_Iberia_Meso 0.050
  243.  
  244. ##end of qpAdm: 227.699 seconds cpu 1293.636 Mbytes in use
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