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Legend_9813

India_Jews

Legend_9813
Mar 12th, 2023 (edited)
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  1. MODEL 1
  2. target = 'India_BeneIsrael_Jew'
  3. right = c('Mbuti.DG', 'EHG', 'CHG', 'WSHG', 'Iran_GanjDareh_N', 'Turkey_N', 'Levant_PPN', 'Israel_Natufian', 'Mongolia_North_N', 'Serbia_IronGates_Mesolithic', 'China_Tianyuan', 'Dai.DG', 'Iraq_Nemrik9_PPN', 'Turkey_Catalhoyuk_N_Ceramic.SG')
  4. left = c('ONG.SG', 'Turkmenistan_Gonur_BA_2', 'Russia_Srubnaya_Alakul.SG', 'Lebanon_ERoman.SG')
  5. qpadm(prefix, left, right, target, allsnps = TRUE)
  6.  
  7. $weights
  8. # A tibble: 4 × 5
  9. target left weight se z
  10. <chr> <chr> <dbl> <dbl> <dbl>
  11. 1 India_BeneIsrael_Jew ONG.SG 0.201 0.0161 12.5
  12. 2 India_BeneIsrael_Jew Turkmenistan_Gonur_BA_2 0.379 0.0311 12.2
  13. 3 India_BeneIsrael_Jew Russia_Srubnaya_Alakul.SG 0.0719 0.0214 3.35
  14. 4 India_BeneIsrael_Jew Lebanon_ERoman.SG 0.348 0.0229 15.2
  15.  
  16. $rankdrop
  17. # A tibble: 4 × 7
  18. f4rank dof chisq p dofdiff chisqdiff p_nested
  19. <int> <int> <dbl> <dbl> <int> <dbl> <dbl>
  20. 1 3 10 14.0 1.71e- 1 12 531. 4.70e-106
  21. 2 2 22 545. 2.43e-101 14 2243. 0
  22. 3 1 36 2789. 0 16 5374. 0
  23. 4 0 52 8163. 0 NA NA NA
  24.  
  25. $popdrop
  26. # A tibble: 15 × 15
  27. pat wt dof chisq p f4rank ONG.SG Turkmenistan_Gonur_BA_2 Russia_Srubna…¹ Leban…² feasi…³ best dofdiff chisq…⁴ p_nes…⁵
  28. <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
  29. 1 0000 0 10 14.0 1.71e- 1 3 0.201 0.379 0.0719 0.348 TRUE NA NA NA NA
  30. 2 0001 1 11 199. 9.64e- 37 2 0.00683 0.904 0.0887 NA TRUE TRUE 0 169. 0
  31. 3 0010 1 11 30.3 1.41e- 3 2 0.185 0.433 NA 0.382 TRUE TRUE 0 -197. 1
  32. 4 0100 1 11 227. 1.77e- 42 2 0.352 NA 0.128 0.520 TRUE TRUE 0 106. 0
  33. 5 1000 1 11 121. 1.16e- 20 2 NA 0.743 -0.0170 0.274 FALSE TRUE NA NA NA
  34. 6 0011 2 12 218. 6.75e- 40 1 -0.0505 1.05 NA NA FALSE NA NA NA NA
  35. 7 0101 2 12 1264. 2.50e-263 1 0.427 NA 0.573 NA TRUE NA NA NA NA
  36. 8 0110 2 12 326. 2.00e- 62 1 0.361 NA NA 0.639 TRUE NA NA NA NA
  37. 9 1001 2 12 221. 1.21e- 40 1 NA 0.916 0.0844 NA TRUE NA NA NA NA
  38. 10 1010 2 12 132. 2.82e- 22 1 NA 0.751 NA 0.249 TRUE NA NA NA NA
  39. 11 1100 2 12 1486. 3.99e-311 1 NA NA -0.0341 1.03 FALSE NA NA NA NA
  40. 12 0111 3 13 2706. 0 0 1 NA NA NA TRUE NA NA NA NA
  41. 13 1011 3 13 243. 1.99e- 44 0 NA 1 NA NA TRUE NA NA NA NA
  42. 14 1101 3 13 3872. 0 0 NA NA 1 NA TRUE NA NA NA NA
  43. 15 1110 3 13 2141. 0 0 NA NA NA 1 TRUE NA NA NA NA
  44. # … with abbreviated variable names ¹​Russia_Srubnaya_Alakul.SG, ²​Lebanon_ERoman.SG, ³​feasible, ⁴​chisqdiff, ⁵​p_nested
  45.  
  46. MODEL 2
  47. target = 'India_Cochin_Jew'
  48. right = c('Mbuti.DG', 'EHG', 'CHG', 'WSHG', 'Iran_GanjDareh_N', 'Turkey_N', 'Levant_PPN', 'Israel_Natufian', 'Mongolia_North_N', 'Serbia_IronGates_Mesolithic', 'China_Tianyuan', 'Dai.DG', 'Iraq_Nemrik9_PPN', 'Turkey_Catalhoyuk_N_Ceramic.SG')
  49. left = c('ONG.SG', 'Turkmenistan_Gonur_BA_2', 'Russia_Srubnaya_Alakul.SG', 'Italy_Pompeii_Roman.SG')
  50. qpadm(prefix, left, right, target, allsnps = TRUE)
  51.  
  52. $weights
  53. # A tibble: 4 × 5
  54. target left weight se z
  55. <chr> <chr> <dbl> <dbl> <dbl>
  56. 1 India_Cochin_Jew Onge.DG 0.269 0.0176 15.3
  57. 2 India_Cochin_Jew Turkmenistan_Gonur_BA_2 0.502 0.0334 15.0
  58. 3 India_Cochin_Jew Russia_Srubnaya_Alakul.SG 0.0586 0.0237 2.47
  59. 4 India_Cochin_Jew Italy_Pompeii_Roman.SG 0.170 0.0239 7.13
  60.  
  61. $rankdrop
  62. # A tibble: 4 × 7
  63. f4rank dof chisq p dofdiff chisqdiff p_nested
  64. <int> <int> <dbl> <dbl> <int> <dbl> <dbl>
  65. 1 3 10 17.0 7.36e- 2 12 446. 6.26e- 88
  66. 2 2 22 463. 3.39e- 84 14 955. 8.11e-195
  67. 3 1 36 1418. 1.08e-274 16 4893. 0
  68. 4 0 52 6311. 0 NA NA NA
  69.  
  70. $popdrop
  71. # A tibble: 15 × 15
  72. pat wt dof chisq p f4rank Onge.DG Turkmenistan_Gonur_BA_2 Russia_Srubna…¹ Italy_…² feasi…³ best dofdiff chisq…⁴ p_nes…⁵
  73. <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> <dbl> <dbl>
  74. 1 0000 0 10 17.0 7.36e- 2 3 0.269 0.502 0.0586 1.70e-1 TRUE NA NA NA NA
  75. 2 0001 1 11 67.8 3.15e- 10 2 0.220 0.657 0.123 NA TRUE TRUE 0 43.0 0
  76. 3 0010 1 11 24.8 9.79e- 3 2 0.261 0.541 NA 1.98e-1 TRUE TRUE 0 -270. 1
  77. 4 0100 1 11 295. 1.03e- 56 2 0.461 NA 0.0706 4.68e-1 TRUE TRUE 0 149. 0
  78. 5 1000 1 11 146. 9.64e- 26 2 NA 0.993 -0.0373 4.38e-2 FALSE TRUE NA NA NA
  79. 6 0011 2 12 102. 2.24e- 16 1 0.165 0.835 NA NA TRUE NA NA NA NA
  80. 7 0101 2 12 638. 7.06e-129 1 0.550 NA 0.450 NA TRUE NA NA NA NA
  81. 8 0110 2 12 334. 4.15e- 64 1 0.464 NA NA 5.36e-1 TRUE NA NA NA NA
  82. 9 1001 2 12 151. 2.91e- 26 1 NA 1.01 -0.00978 NA FALSE NA NA NA NA
  83. 10 1010 2 12 159. 8.43e- 28 1 NA 1.00 NA -9.64e-4 FALSE NA NA NA NA
  84. 11 1100 2 12 603. 2.78e-121 1 NA NA -2.53 3.53e+0 FALSE NA NA NA NA
  85. 12 0111 3 13 1662. 0 0 1 NA NA NA TRUE NA NA NA NA
  86. 13 1011 3 13 162. 8.64e- 28 0 NA 1 NA NA TRUE NA NA NA NA
  87. 14 1101 3 13 3882. 0 0 NA NA 1 NA TRUE NA NA NA NA
  88. 15 1110 3 13 1123. 8.21e-232 0 NA NA NA 1 e+0 TRUE NA NA NA NA
  89. # … with abbreviated variable names ¹​Russia_Srubnaya_Alakul.SG, ²​Italy_Pompeii_Roman.SG, ³​feasible, ⁴​chisqdiff, ⁵​p_nested
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