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misnomer001

steppe eneolithic 4 way davidski right

misnomer001
Feb 19th, 2020
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  1. allsnps: YES
  2. ## qpAdm version: 1000
  3. seed: 1766017431
  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. 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. Russia_Shamanka_EN.SG
  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 Russia_Shamanka_EN.SG 10
  43. 14 Brazil_LapaDoSanto_9600BP 5
  44. 15 NW_Iberia_Meso 1
  45. jackknife block size: 0.050
  46. snps: 1150445 indivs: 83
  47. number of blocks for block jackknife: 552
  48. ## ncols: 1150445
  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: Russia_Shamanka_EN.SG 1149998
  63. coverage: Brazil_LapaDoSanto_9600BP 946991
  64. coverage: NW_Iberia_Meso 995773
  65. dof (jackknife): 466.655
  66. numsnps used: 1150445
  67. codimension 1
  68. f4info:
  69. f4rank: 3 dof: 7 chisq: 15.676 tail: 0.0282447359 dofdiff: 9 chisqdiff: -15.676 taildiff: 1
  70. B:
  71. scale 1.000 1.000 1.000
  72. Morocco_Iberomaurusian 0.132 0.811 -0.257
  73. Ganj_Dareh_N -0.786 -1.229 1.414
  74. PPN -0.236 1.166 1.805
  75. Pinarbasi 0.228 1.908 -0.016
  76. Russia_MA1_HG 1.760 -0.845 0.444
  77. Ust_Ishim.DG 0.321 0.265 -0.947
  78. Russia_Kostenki14.SG 0.778 0.525 -0.852
  79. Russia_Shamanka_EN.SG 0.894 -0.381 -1.339
  80. Brazil_LapaDoSanto_9600BP 1.435 -0.929 1.031
  81. NW_Iberia_Meso 1.610 0.873 -0.002
  82. A:
  83. scale 434.649 1601.532 3133.070
  84. CHG -1.037 0.059 -1.826
  85. Caucasus_Eneolithic -0.808 1.817 0.572
  86. EEHG 1.080 0.318 -0.502
  87. Geoksyur_EN -1.051 -0.771 0.292
  88.  
  89.  
  90. full rank
  91. f4info:
  92. f4rank: 4 dof: 0 chisq: 0.000 tail: 1 dofdiff: 7 chisqdiff: 15.676 taildiff: 0.0282447359
  93. B:
  94. scale 402.177 430.827 411.021 376.536
  95. Morocco_Iberomaurusian -0.055 0.255 0.215 -0.292
  96. Ganj_Dareh_N 0.312 0.038 -1.132 0.893
  97. PPN -0.269 0.826 -0.326 -0.011
  98. Pinarbasi -0.251 0.653 0.316 -0.637
  99. Russia_MA1_HG -1.939 -1.977 1.468 -1.630
  100. Ust_Ishim.DG -0.255 -0.460 0.108 -0.592
  101. Russia_Kostenki14.SG -0.640 -0.609 0.687 -0.977
  102. Russia_Shamanka_EN.SG -0.594 -1.055 0.959 -0.839
  103. Brazil_LapaDoSanto_9600BP -1.664 -1.553 1.354 -1.135
  104. NW_Iberia_Meso -1.552 -0.899 1.754 -1.660
  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: -0.029 0.105 0.481 0.443
  114. Jackknife mean: -0.025294696 0.103980074 0.481414780 0.439899842
  115. std. errors: 0.099 0.060 0.019 0.072
  116.  
  117. error covariance (* 1,000,000)
  118. 9778 -3585 -509 -5684
  119. -3585 3557 -183 211
  120. -509 -183 350 341
  121. -5684 211 341 5132
  122.  
  123.  
  124. summ: Steppe_Eneolithic 4 0.028245 -0.025 0.104 0.481 0.440 9778 -3585 -509 -5684 3557 ...
  125. -183 211 350 341 5132
  126.  
  127. fixed pat wt dof chisq tail prob
  128. 0000 0 7 15.676 0.0282447 -0.029 0.105 0.481 0.443 infeasible
  129. 0001 1 8 56.827 1.946e-09 0.469 0.080 0.451 0.000
  130. 0010 1 8 100.446 3.46022e-18 25.387 -12.741 0.000 -11.646 infeasible
  131. 0100 1 8 19.243 0.0136143 0.052 0.000 0.491 0.457
  132. 1000 1 8 15.824 0.0449696 0.000 0.094 0.480 0.426
  133. 0011 2 9 137.676 3.11194e-25 16.182 -15.182 0.000 0.000 infeasible
  134. 0101 2 9 58.122 3.07976e-09 0.546 0.000 0.454 0.000
  135. 0110 2 9 150.022 8.72835e-28 4.433 0.000 0.000 -3.433 infeasible
  136. 1001 2 9 101.406 8.17361e-18 0.000 0.535 0.465 0.000
  137. 1010 2 9 265.952 0 0.000 3.438 0.000 -2.438 infeasible
  138. 1100 2 9 19.775 0.0193511 0.000 0.000 0.497 0.503
  139. 0111 3 10 351.455 0 1.000 0.000 0.000 0.000
  140. 1011 3 10 412.241 0 0.000 1.000 0.000 0.000
  141. 1101 3 10 605.925 0 0.000 0.000 1.000 0.000
  142. 1110 3 10 748.159 0 0.000 0.000 0.000 1.000
  143. best pat: 0000 0.0282447 - -
  144. best pat: 1000 0.0449696 chi(nested): 0.148 p-value for nested model: 0.700674
  145. best pat: 1100 0.0193511 chi(nested): 3.951 p-value for nested model: 0.0468359
  146. best pat: 0111 1.95668e-69 not nested
  147.  
  148. coeffs: -0.029 0.105 0.481 0.443
  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 -0.446860
  154. details: Caucasus_Eneolithic Morocco_Iberomaurusian 0.000591 1.986492
  155. details: EEHG Morocco_Iberomaurusian 0.000523 1.877666
  156. details: Geoksyur_EN Morocco_Iberomaurusian -0.000774 -3.360034
  157. dscore: Morocco_Iberomaurusian f4: -0.000025 Z: -0.119598
  158.  
  159. details: CHG Ganj_Dareh_N 0.000775 2.445763
  160. details: Caucasus_Eneolithic Ganj_Dareh_N 0.000089 0.282089
  161. details: EEHG Ganj_Dareh_N -0.002754 -10.058152
  162. details: Geoksyur_EN Ganj_Dareh_N 0.002372 9.499312
  163. dscore: Ganj_Dareh_N f4: -0.000289 Z: -1.328066
  164.  
  165. details: CHG PPN -0.000668 -2.253923
  166. details: Caucasus_Eneolithic PPN 0.001917 5.914295
  167. details: EEHG PPN -0.000794 -3.078869
  168. details: Geoksyur_EN PPN -0.000030 -0.124529
  169. dscore: PPN f4: -0.000176 Z: -0.845127
  170.  
  171. details: CHG Pinarbasi -0.000623 -1.673686
  172. details: Caucasus_Eneolithic Pinarbasi 0.001516 3.749767
  173. details: EEHG Pinarbasi 0.000769 2.351479
  174. details: Geoksyur_EN Pinarbasi -0.001692 -5.580564
  175. dscore: Pinarbasi f4: -0.000202 Z: -0.774458
  176.  
  177. details: CHG Russia_MA1_HG -0.004822 -11.774815
  178. details: Caucasus_Eneolithic Russia_MA1_HG -0.004589 -11.713569
  179. details: EEHG Russia_MA1_HG 0.003571 10.093238
  180. details: Geoksyur_EN Russia_MA1_HG -0.004329 -13.552925
  181. dscore: Russia_MA1_HG f4: -0.000539 Z: -1.925002
  182.  
  183. details: CHG Ust_Ishim.DG -0.000634 -1.681630
  184. details: Caucasus_Eneolithic Ust_Ishim.DG -0.001067 -2.861634
  185. details: EEHG Ust_Ishim.DG 0.000263 0.792423
  186. details: Geoksyur_EN Ust_Ishim.DG -0.001572 -5.605876
  187. dscore: Ust_Ishim.DG f4: -0.000663 Z: -2.637906
  188.  
  189. details: CHG Russia_Kostenki14.SG -0.001592 -3.948478
  190. details: Caucasus_Eneolithic Russia_Kostenki14.SG -0.001414 -3.518116
  191. details: EEHG Russia_Kostenki14.SG 0.001671 4.518977
  192. details: Geoksyur_EN Russia_Kostenki14.SG -0.002595 -8.764904
  193. dscore: Russia_Kostenki14.SG f4: -0.000446 Z: -1.665017
  194.  
  195. details: CHG Russia_Shamanka_EN.SG -0.001477 -4.789068
  196. details: Caucasus_Eneolithic Russia_Shamanka_EN.SG -0.002449 -7.725297
  197. details: EEHG Russia_Shamanka_EN.SG 0.002333 8.245187
  198. details: Geoksyur_EN Russia_Shamanka_EN.SG -0.002228 -8.733653
  199. dscore: Russia_Shamanka_EN.SG f4: -0.000077 Z: -0.344421
  200.  
  201. details: CHG Brazil_LapaDoSanto_9600BP -0.004137 -12.004784
  202. details: Caucasus_Eneolithic Brazil_LapaDoSanto_9600BP -0.003605 -9.866669
  203. details: EEHG Brazil_LapaDoSanto_9600BP 0.003294 10.765457
  204. details: Geoksyur_EN Brazil_LapaDoSanto_9600BP -0.003014 -11.446497
  205. dscore: Brazil_LapaDoSanto_9600BP f4: -0.000007 Z: -0.028146
  206.  
  207. details: CHG NW_Iberia_Meso -0.003858 -9.310296
  208. details: Caucasus_Eneolithic NW_Iberia_Meso -0.002086 -4.766879
  209. details: EEHG NW_Iberia_Meso 0.004267 11.491234
  210. details: Geoksyur_EN NW_Iberia_Meso -0.004410 -14.486322
  211. dscore: NW_Iberia_Meso f4: -0.000005 Z: -0.018645
  212.  
  213. gendstat: Shum_Laka Morocco_Iberomaurusian -0.120
  214. gendstat: Shum_Laka Ganj_Dareh_N -1.328
  215. gendstat: Shum_Laka PPN -0.845
  216. gendstat: Shum_Laka Pinarbasi -0.774
  217. gendstat: Shum_Laka Russia_MA1_HG -1.925
  218. gendstat: Shum_Laka Ust_Ishim.DG -2.638
  219. gendstat: Shum_Laka Russia_Kostenki14.SG -1.665
  220. gendstat: Shum_Laka Russia_Shamanka_EN.SG -0.344
  221. gendstat: Shum_Laka Brazil_LapaDoSanto_9600BP -0.028
  222. gendstat: Shum_Laka NW_Iberia_Meso -0.019
  223. gendstat: Morocco_Iberomaurusian Ganj_Dareh_N -1.064
  224. gendstat: Morocco_Iberomaurusian PPN -0.647
  225. gendstat: Morocco_Iberomaurusian Pinarbasi -0.632
  226. gendstat: Morocco_Iberomaurusian Russia_MA1_HG -1.694
  227. gendstat: Morocco_Iberomaurusian Ust_Ishim.DG -2.296
  228. gendstat: Morocco_Iberomaurusian Russia_Kostenki14.SG -1.509
  229. gendstat: Morocco_Iberomaurusian Russia_Shamanka_EN.SG -0.224
  230. gendstat: Morocco_Iberomaurusian Brazil_LapaDoSanto_9600BP 0.072
  231. gendstat: Morocco_Iberomaurusian NW_Iberia_Meso 0.068
  232. gendstat: Ganj_Dareh_N PPN 0.521
  233. gendstat: Ganj_Dareh_N Pinarbasi 0.316
  234. gendstat: Ganj_Dareh_N Russia_MA1_HG -0.852
  235. gendstat: Ganj_Dareh_N Ust_Ishim.DG -1.372
  236. gendstat: Ganj_Dareh_N Russia_Kostenki14.SG -0.572
  237. gendstat: Ganj_Dareh_N Russia_Shamanka_EN.SG 0.975
  238. gendstat: Ganj_Dareh_N Brazil_LapaDoSanto_9600BP 1.099
  239. gendstat: Ganj_Dareh_N NW_Iberia_Meso 0.957
  240. gendstat: PPN Pinarbasi -0.105
  241. gendstat: PPN Russia_MA1_HG -1.223
  242. gendstat: PPN Ust_Ishim.DG -1.722
  243. gendstat: PPN Russia_Kostenki14.SG -0.993
  244. gendstat: PPN Russia_Shamanka_EN.SG 0.427
  245. gendstat: PPN Brazil_LapaDoSanto_9600BP 0.668
  246. gendstat: PPN NW_Iberia_Meso 0.625
  247. gendstat: Pinarbasi Russia_MA1_HG -1.020
  248. gendstat: Pinarbasi Ust_Ishim.DG -1.422
  249. gendstat: Pinarbasi Russia_Kostenki14.SG -0.797
  250. gendstat: Pinarbasi Russia_Shamanka_EN.SG 0.448
  251. gendstat: Pinarbasi Brazil_LapaDoSanto_9600BP 0.643
  252. gendstat: Pinarbasi NW_Iberia_Meso 0.633
  253. gendstat: Russia_MA1_HG Ust_Ishim.DG -0.365
  254. gendstat: Russia_MA1_HG Russia_Kostenki14.SG 0.289
  255. gendstat: Russia_MA1_HG Russia_Shamanka_EN.SG 1.746
  256. gendstat: Russia_MA1_HG Brazil_LapaDoSanto_9600BP 1.956
  257. gendstat: Russia_MA1_HG NW_Iberia_Meso 1.535
  258. gendstat: Ust_Ishim.DG Russia_Kostenki14.SG 0.681
  259. gendstat: Ust_Ishim.DG Russia_Shamanka_EN.SG 2.215
  260. gendstat: Ust_Ishim.DG Brazil_LapaDoSanto_9600BP 2.229
  261. gendstat: Ust_Ishim.DG NW_Iberia_Meso 2.052
  262. gendstat: Russia_Kostenki14.SG Russia_Shamanka_EN.SG 1.483
  263. gendstat: Russia_Kostenki14.SG Brazil_LapaDoSanto_9600BP 1.575
  264. gendstat: Russia_Kostenki14.SG NW_Iberia_Meso 1.417
  265. gendstat: Russia_Shamanka_EN.SG Brazil_LapaDoSanto_9600BP 0.369
  266. gendstat: Russia_Shamanka_EN.SG NW_Iberia_Meso 0.259
  267. gendstat: Brazil_LapaDoSanto_9600BP NW_Iberia_Meso 0.005
  268.  
  269. ##end of qpAdm: 231.664 seconds cpu 1349.128 Mbytes in use
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