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misnomer001

steppe eneolithic 3 way caucasus fail

misnomer001
Feb 19th, 2020
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  1. allsnps: YES
  2. ## qpAdm version: 1000
  3. seed: 1768756106
  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. EEHG
  12. CHG
  13. Caucasus_Eneolithic
  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 EEHG 5
  30. 2 CHG 2
  31. 3 Caucasus_Eneolithic 3
  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: 1150443 indivs: 62
  45. number of blocks for block jackknife: 552
  46. ## ncols: 1150443
  47. coverage: Steppe_Eneolithic 1017729
  48. coverage: EEHG 1052093
  49. coverage: CHG 1149558
  50. coverage: Caucasus_Eneolithic 784983
  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): 466.653
  63. numsnps used: 1150443
  64. codimension 1
  65. f4info:
  66. f4rank: 2 dof: 8 chisq: 57.196 tail: 1.64897799e-09 dofdiff: 10 chisqdiff: -57.196 taildiff: 1
  67. B:
  68. scale 1.000 1.000
  69. Morocco_Iberomaurusian -0.019 0.646
  70. Ganj_Dareh_N -0.734 -0.798
  71. PPN -0.407 1.835
  72. Pinarbasi -0.041 1.712
  73. Russia_MA1_HG 1.813 -0.406
  74. Ust_Ishim.DG 0.196 -0.362
  75. Russia_Kostenki14.SG 0.636 -0.072
  76. Russia_Shamanka_EN.SG 0.959 -0.944
  77. Brazil_LapaDoSanto_9600BP 1.550 -0.121
  78. NW_Iberia_Meso 1.498 1.200
  79. A:
  80. scale 460.156 1794.704
  81. EEHG 1.145 0.568
  82. CHG -0.953 -0.781
  83. Caucasus_Eneolithic -0.884 1.438
  84.  
  85.  
  86. full rank
  87. f4info:
  88. f4rank: 3 dof: 0 chisq: 0.000 tail: 1 dofdiff: 8 chisqdiff: 57.196 taildiff: 1.64897799e-09
  89. B:
  90. scale 411.021 402.178 430.827
  91. Morocco_Iberomaurusian 0.215 -0.055 0.255
  92. Ganj_Dareh_N -1.132 0.312 0.038
  93. PPN -0.326 -0.269 0.826
  94. Pinarbasi 0.316 -0.251 0.653
  95. Russia_MA1_HG 1.468 -1.939 -1.977
  96. Ust_Ishim.DG 0.108 -0.255 -0.460
  97. Russia_Kostenki14.SG 0.687 -0.640 -0.609
  98. Russia_Shamanka_EN.SG 0.959 -0.594 -1.055
  99. Brazil_LapaDoSanto_9600BP 1.354 -1.664 -1.553
  100. NW_Iberia_Meso 1.754 -1.552 -0.899
  101. A:
  102. scale 1.732 1.732 1.732
  103. EEHG 1.732 0.000 0.000
  104. CHG 0.000 1.732 0.000
  105. Caucasus_Eneolithic 0.000 0.000 1.732
  106.  
  107.  
  108. best coefficients: 0.452 0.471 0.077
  109. Jackknife mean: 0.452025543 0.465181311 0.082793146
  110. std. errors: 0.021 0.089 0.089
  111.  
  112. error covariance (* 1,000,000)
  113. 421 -173 -248
  114. -173 7899 -7726
  115. -248 -7726 7974
  116.  
  117.  
  118. summ: Steppe_Eneolithic 3 0.000000 0.452 0.465 0.083 421 -173 -248 7899 -7726 ...
  119. 7974
  120.  
  121. fixed pat wt dof chisq tail prob
  122. 000 0 8 57.196 1.64898e-09 0.452 0.471 0.077
  123. 001 1 9 58.468 2.64341e-09 0.455 0.545 0.000
  124. 010 1 9 101.278 8.67409e-18 0.466 0.000 0.534
  125. 100 1 9 138.293 2.32232e-25 0.000 14.975 -13.975 infeasible
  126. 011 2 10 607.632 0 1.000 0.000 0.000
  127. 101 2 10 352.276 0 0.000 1.000 0.000
  128. 110 2 10 413.083 0 0.000 0.000 1.000
  129. best pat: 000 1.64898e-09 - -
  130. best pat: 001 2.64341e-09 chi(nested): 1.272 p-value for nested model: 0.259471
  131. best pat: 101 1.31004e-69 chi(nested): 293.809 p-value for nested model: 7.35635e-66
  132.  
  133. coeffs: 0.452 0.471 0.077
  134.  
  135. ## dscore:: f_4(Base, Fit, Rbase, right2)
  136. ## genstat:: f_4(Base, Fit, right1, right2)
  137.  
  138. details: EEHG Morocco_Iberomaurusian 0.000523 1.879704
  139. details: CHG Morocco_Iberomaurusian -0.000136 -0.447316
  140. details: Caucasus_Eneolithic Morocco_Iberomaurusian 0.000591 1.988331
  141. dscore: Morocco_Iberomaurusian f4: 0.000218 Z: 0.984505
  142.  
  143. details: EEHG Ganj_Dareh_N -0.002754 -10.068287
  144. details: CHG Ganj_Dareh_N 0.000775 2.447782
  145. details: Caucasus_Eneolithic Ganj_Dareh_N 0.000089 0.282303
  146. dscore: Ganj_Dareh_N f4: -0.000873 Z: -3.792286
  147.  
  148. details: EEHG PPN -0.000794 -3.082315
  149. details: CHG PPN -0.000668 -2.256032
  150. details: Caucasus_Eneolithic PPN 0.001917 5.918775
  151. dscore: PPN f4: -0.000525 Z: -2.492105
  152.  
  153. details: EEHG Pinarbasi 0.000769 2.353247
  154. details: CHG Pinarbasi -0.000623 -1.674722
  155. details: Caucasus_Eneolithic Pinarbasi 0.001516 3.751803
  156. dscore: Pinarbasi f4: 0.000172 Z: 0.628053
  157.  
  158. details: EEHG Russia_MA1_HG 0.003571 10.100103
  159. details: CHG Russia_MA1_HG -0.004822 -11.781407
  160. details: Caucasus_Eneolithic Russia_MA1_HG -0.004589 -11.720184
  161. dscore: Russia_MA1_HG f4: -0.001012 Z: -3.489310
  162.  
  163. details: EEHG Ust_Ishim.DG 0.000263 0.792941
  164. details: CHG Ust_Ishim.DG -0.000634 -1.682620
  165. details: Caucasus_Eneolithic Ust_Ishim.DG -0.001067 -2.863308
  166. dscore: Ust_Ishim.DG f4: -0.000262 Z: -0.954859
  167.  
  168. details: EEHG Russia_Kostenki14.SG 0.001671 4.521520
  169. details: CHG Russia_Kostenki14.SG -0.001592 -3.950836
  170. details: Caucasus_Eneolithic Russia_Kostenki14.SG -0.001413 -3.520105
  171. dscore: Russia_Kostenki14.SG f4: -0.000104 Z: -0.350102
  172.  
  173. details: EEHG Russia_Shamanka_EN.SG 0.002333 8.253117
  174. details: CHG Russia_Shamanka_EN.SG -0.001477 -4.793534
  175. details: Caucasus_Eneolithic Russia_Shamanka_EN.SG -0.002449 -7.731286
  176. dscore: Russia_Shamanka_EN.SG f4: 0.000169 Z: 0.731345
  177.  
  178. details: EEHG Brazil_LapaDoSanto_9600BP 0.003294 10.775102
  179. details: CHG Brazil_LapaDoSanto_9600BP -0.004137 -12.013943
  180. details: Caucasus_Eneolithic Brazil_LapaDoSanto_9600BP -0.003605 -9.872459
  181. dscore: Brazil_LapaDoSanto_9600BP f4: -0.000738 Z: -2.914391
  182.  
  183. details: EEHG NW_Iberia_Meso 0.004267 11.498946
  184. details: CHG NW_Iberia_Meso -0.003858 -9.315978
  185. details: Caucasus_Eneolithic NW_Iberia_Meso -0.002086 -4.769305
  186. dscore: NW_Iberia_Meso f4: -0.000050 Z: -0.165158
  187.  
  188. gendstat: Shum_Laka Morocco_Iberomaurusian 0.985
  189. gendstat: Shum_Laka Ganj_Dareh_N -3.792
  190. gendstat: Shum_Laka PPN -2.492
  191. gendstat: Shum_Laka Pinarbasi 0.628
  192. gendstat: Shum_Laka Russia_MA1_HG -3.489
  193. gendstat: Shum_Laka Ust_Ishim.DG -0.955
  194. gendstat: Shum_Laka Russia_Kostenki14.SG -0.350
  195. gendstat: Shum_Laka Russia_Shamanka_EN.SG 0.731
  196. gendstat: Shum_Laka Brazil_LapaDoSanto_9600BP -2.914
  197. gendstat: Shum_Laka NW_Iberia_Meso -0.165
  198. gendstat: Morocco_Iberomaurusian Ganj_Dareh_N -4.091
  199. gendstat: Morocco_Iberomaurusian PPN -3.044
  200. gendstat: Morocco_Iberomaurusian Pinarbasi -0.155
  201. gendstat: Morocco_Iberomaurusian Russia_MA1_HG -3.929
  202. gendstat: Morocco_Iberomaurusian Ust_Ishim.DG -1.582
  203. gendstat: Morocco_Iberomaurusian Russia_Kostenki14.SG -1.035
  204. gendstat: Morocco_Iberomaurusian Russia_Shamanka_EN.SG -0.201
  205. gendstat: Morocco_Iberomaurusian Brazil_LapaDoSanto_9600BP -3.441
  206. gendstat: Morocco_Iberomaurusian NW_Iberia_Meso -0.815
  207. gendstat: Ganj_Dareh_N PPN 1.541
  208. gendstat: Ganj_Dareh_N Pinarbasi 3.616
  209. gendstat: Ganj_Dareh_N Russia_MA1_HG -0.463
  210. gendstat: Ganj_Dareh_N Ust_Ishim.DG 2.112
  211. gendstat: Ganj_Dareh_N Russia_Kostenki14.SG 2.603
  212. gendstat: Ganj_Dareh_N Russia_Shamanka_EN.SG 4.532
  213. gendstat: Ganj_Dareh_N Brazil_LapaDoSanto_9600BP 0.498
  214. gendstat: Ganj_Dareh_N NW_Iberia_Meso 2.557
  215. gendstat: PPN Pinarbasi 2.665
  216. gendstat: PPN Russia_MA1_HG -1.628
  217. gendstat: PPN Ust_Ishim.DG 0.907
  218. gendstat: PPN Russia_Kostenki14.SG 1.458
  219. gendstat: PPN Russia_Shamanka_EN.SG 2.886
  220. gendstat: PPN Brazil_LapaDoSanto_9600BP -0.794
  221. gendstat: PPN NW_Iberia_Meso 1.575
  222. gendstat: Pinarbasi Russia_MA1_HG -3.465
  223. gendstat: Pinarbasi Ust_Ishim.DG -1.276
  224. gendstat: Pinarbasi Russia_Kostenki14.SG -0.846
  225. gendstat: Pinarbasi Russia_Shamanka_EN.SG -0.010
  226. gendstat: Pinarbasi Brazil_LapaDoSanto_9600BP -2.829
  227. gendstat: Pinarbasi NW_Iberia_Meso -0.656
  228. gendstat: Russia_MA1_HG Ust_Ishim.DG 2.152
  229. gendstat: Russia_MA1_HG Russia_Kostenki14.SG 2.667
  230. gendstat: Russia_MA1_HG Russia_Shamanka_EN.SG 4.304
  231. gendstat: Russia_MA1_HG Brazil_LapaDoSanto_9600BP 0.939
  232. gendstat: Russia_MA1_HG NW_Iberia_Meso 2.644
  233. gendstat: Ust_Ishim.DG Russia_Kostenki14.SG 0.461
  234. gendstat: Ust_Ishim.DG Russia_Shamanka_EN.SG 1.547
  235. gendstat: Ust_Ishim.DG Brazil_LapaDoSanto_9600BP -1.497
  236. gendstat: Ust_Ishim.DG NW_Iberia_Meso 0.606
  237. gendstat: Russia_Kostenki14.SG Russia_Shamanka_EN.SG 1.007
  238. gendstat: Russia_Kostenki14.SG Brazil_LapaDoSanto_9600BP -2.154
  239. gendstat: Russia_Kostenki14.SG NW_Iberia_Meso 0.158
  240. gendstat: Russia_Shamanka_EN.SG Brazil_LapaDoSanto_9600BP -4.250
  241. gendstat: Russia_Shamanka_EN.SG NW_Iberia_Meso -0.721
  242. gendstat: Brazil_LapaDoSanto_9600BP NW_Iberia_Meso 2.101
  243.  
  244. ##end of qpAdm: 232.462 seconds cpu 1293.636 Mbytes in use
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