Кухулин

Има общо 16 635 индивида. От тях 3 са в четири варианта, 224 са в три варианта, а 3439 са в два варианта. Ако нещо не съм объркал брояча. Скриптче: f_ind = "C:/AdmixTools/Dataset/v54.1.p1_HO_public_original.ind" t_ind = fread( f_ind, header = FALSE, col.names = c( 'ID', 'Sex', 'Population')) id_chunks = "\\.EC|\\.SG|\\.DG|\\.HO|_d|_noUDG|_all|_enhanced|_final_provisional|-ALL_DATA|_alt" t_ind$ID = str_replace_all( t_ind$ID, id_chunks, '') view( unique( t_ind[, `:=` (N = .N, Population = .SD[[1,2]]), by = ID])[order( -N)]) Ще извиняваш за дърварското изпълнение, ама не сме на конкурс за кодери

Ибаси змията. През ф2 работи. > result_f3 = f3 ("C:/AdmixTools/Dataset/v54.1.p1_HO_public", verbose = T, + "TUR_Marmara_Kumtepe_N", + "TUR_Marmara_Barcin_N", + c ("RUS_Yamnaya_Samara_EBA", + "ARM_Berkaber_KuraAraxes_EBA")) ℹ Computing from f3 from genotype data... ℹ Reading metadata... ℹ Computing block lengths for 593124 SNPs... ℹ Computing 2 f3-statistics for block 711 out of 711... ℹ Summarize across blocks... > result_f3[order(result_f3$z),] # A tibble: 2 × 8 pop1 pop2 pop3 est se z p n <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> 1 TUR_Marmara_Kumtepe_N TUR_Marmara_Barcin_N RUS_Yamnaya_Samara_EBA NA NA NA NA NA 2 TUR_Marmara_Kumtepe_N TUR_Marmara_Barcin_N ARM_Berkaber_KuraAraxes_E… NA NA NA NA NA > result_f3 = f3 ("C:/AdmixTools/Dataset/v54.1.p1_1240K_public", verbose = T, + "TUR_Marmara_Kumtepe_N", + "TUR_Marmara_Barcin_N", + c ("RUS_Yamnaya_Samara_EBA", + "ARM_Berkaber_KuraAraxes_EBA")) ℹ Computing from f3 from genotype data... ℹ Reading metadata... ℹ Computing block lengths for 1150639 SNPs... ℹ Computing 2 f3-statistics for block 713 out of 713... ℹ Summarize across blocks... > result_f3[order(result_f3$z),] # A tibble: 2 × 8 pop1 pop2 pop3 est se z p n <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> 1 TUR_Marmara_Kumtepe_N TUR_Marmara_Barcin_N RUS_Yamnaya_Samara_EBA NA NA NA NA NA 2 TUR_Marmara_Kumtepe_N TUR_Marmara_Barcin_N ARM_Berkaber_KuraAraxes_E… NA NA NA NA NA > count_snps(f2_blocks) [1] 28156 > result_f3 = f3 (f2_blocks, verbose = T, + "TUR_Marmara_Kumtepe_N", + "TUR_Marmara_Barcin_N", + c ("RUS_Yamnaya_Samara_EBA", + "ARM_Berkaber_KuraAraxes_EBA")) ℹ Computing f3-statistics > result_f3[order(result_f3$z),] # A tibble: 2 × 7 pop1 pop2 pop3 est se z p <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> 1 TUR_Marmara_Kumtepe_N TUR_Marmara_Barcin_N ARM_Berkaber_KuraAraxes_EBA 0.171 0.00163 105. 0 2 TUR_Marmara_Kumtepe_N TUR_Marmara_Barcin_N RUS_Yamnaya_Samara_EBA 0.172 0.00151 114. 0 >

Интересно. Това трябва да е през ф2-блоковете? Ще пробвам.

И двете бази ползвам, същата работа.

Покритието не е чак толкова ниско - 126к. В оригиналното изследване връткат всякакви статистики: Table S5: Key results obtained from D-statistics D(Outgroup, pop1; pop2, pop3). (Related to Figure 4A) https://ars.els-cdn.com/content/image/1-s2.0-S096098221501516X-mmc1.pdf И въпреки това базата на Райх нищо не дава: Иначе пробите от Кумтепе имат доста интересен геном, само че нещо са ги окастрили...

@tantin, би ли проверил как се държи при теб образецът "kum6_noUDG.SG", (популация "Turkey_Kumtepe_N.SG")?

Тц-тц, мърлява работа. Почна да ми пищи скрипта, отварям анотацията - някакви мешаници по средата на файла. I21276 в ексел. Тия хора са го писали на ръка и после изобщо не са го проверявали. Харвард, разбираш ли. Пфф...

Да, така го тълкувам. Тоест, в този случай на кпАдм не може да се има доверие. Макар че п-стойностите на Ряховец са добри, за разлика от българските. Но ф4 бие всичко, поне на този етап от статистическото ми познание > result_qpadm_Ryahovets$popdrop[1,] # A tibble: 1 × 16 pat wt dof chisq p f4rank CHG EHG Levant_PPN SRB_Iron_Gates_HG TUR_Marmara_Barcin_N feasible best dofdiff <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> 1 00000 0 5 8.40 0.135 4 0.307 0.200 0.0356 0.0994 0.357 TRUE NA NA # ℹ 2 more variables: chisqdiff <dbl>, p_nested <dbl> > result_qpadm_Bulgarian$popdrop[1,] # A tibble: 1 × 16 pat wt dof chisq p f4rank CHG EHG Levant_PPN SRB_Iron_Gates_HG TUR_Marmara_Barcin_N feasible best dofdiff <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> <lgl> <dbl> 1 00000 0 5 19.1 0.00185 4 0.278 0.150 0.0268 0.120 0.426 TRUE NA NA # ℹ 2 more variables: chisqdiff <dbl>, p_nested <dbl> >

Съвременните българи в тази схема (без DG, само HO): result_qpadm_Ryahovets = qpadm( + data = "C:/AdmixTools/Dataset/v54.1.p1_HO_public", + left = c( + "CHG", + "EHG", + "Levant_PPN", + "SRB_Iron_Gates_HG", + "TUR_Marmara_Barcin_N" + ), + right = c( + "Mbuti.DG", + "IRN_Ganj_Dareh_N", + "ISR_Natufian_EpiP", + "MAR_Taforalt_EpiP", + "Mesopotamia", + "RUS_AfontovaGora3", + "RUS_MA1_HG", + "TUR_C_Boncuklu_PPN", + "TUR_Pinarbasi_EpiP", + "WHG" + ), + target = "Bulgarian.HO", + allsnps = T + ) ℹ Reading metadata... ℹ Computing block lengths for 593124 SNPs... ℹ Computing 45 f4-statistics for block 711 out of 711... ℹ "allsnps = TRUE" uses different SNPs for each f4-statistic Number of SNPs used for each f4-statistic: pop1 pop2 pop3 pop4 n 1 Bulgarian.HO CHG Mbuti.DG IRN_Ganj_Dareh_N 553696 2 Bulgarian.HO CHG Mbuti.DG ISR_Natufian_EpiP 283702 3 Bulgarian.HO CHG Mbuti.DG MAR_Taforalt_EpiP 568148 4 Bulgarian.HO CHG Mbuti.DG Mesopotamia 453740 5 Bulgarian.HO CHG Mbuti.DG RUS_AfontovaGora3 161230 6 Bulgarian.HO CHG Mbuti.DG RUS_MA1_HG 420191 7 Bulgarian.HO CHG Mbuti.DG TUR_C_Boncuklu_PPN 555185 8 Bulgarian.HO CHG Mbuti.DG TUR_Pinarbasi_EpiP 449535 9 Bulgarian.HO CHG Mbuti.DG WHG 584521 10 Bulgarian.HO EHG Mbuti.DG IRN_Ganj_Dareh_N 549660 11 Bulgarian.HO EHG Mbuti.DG ISR_Natufian_EpiP 282184 12 Bulgarian.HO EHG Mbuti.DG MAR_Taforalt_EpiP 563758 13 Bulgarian.HO EHG Mbuti.DG Mesopotamia 450916 14 Bulgarian.HO EHG Mbuti.DG RUS_AfontovaGora3 160712 15 Bulgarian.HO EHG Mbuti.DG RUS_MA1_HG 416320 16 Bulgarian.HO EHG Mbuti.DG TUR_C_Boncuklu_PPN 550777 17 Bulgarian.HO EHG Mbuti.DG TUR_Pinarbasi_EpiP 446604 18 Bulgarian.HO EHG Mbuti.DG WHG 578703 19 Bulgarian.HO Levant_PPN Mbuti.DG IRN_Ganj_Dareh_N 432847 20 Bulgarian.HO Levant_PPN Mbuti.DG ISR_Natufian_EpiP 248859 21 Bulgarian.HO Levant_PPN Mbuti.DG MAR_Taforalt_EpiP 434644 22 Bulgarian.HO Levant_PPN Mbuti.DG Mesopotamia 374734 23 Bulgarian.HO Levant_PPN Mbuti.DG RUS_AfontovaGora3 140991 24 Bulgarian.HO Levant_PPN Mbuti.DG RUS_MA1_HG 320639 25 Bulgarian.HO Levant_PPN Mbuti.DG TUR_C_Boncuklu_PPN 427232 26 Bulgarian.HO Levant_PPN Mbuti.DG TUR_Pinarbasi_EpiP 363077 27 Bulgarian.HO Levant_PPN Mbuti.DG WHG 439042 28 Bulgarian.HO SRB_Iron_Gates_HG Mbuti.DG IRN_Ganj_Dareh_N 553867 29 Bulgarian.HO SRB_Iron_Gates_HG Mbuti.DG ISR_Natufian_EpiP 283864 30 Bulgarian.HO SRB_Iron_Gates_HG Mbuti.DG MAR_Taforalt_EpiP 567946 31 Bulgarian.HO SRB_Iron_Gates_HG Mbuti.DG Mesopotamia 453937 32 Bulgarian.HO SRB_Iron_Gates_HG Mbuti.DG RUS_AfontovaGora3 161338 33 Bulgarian.HO SRB_Iron_Gates_HG Mbuti.DG RUS_MA1_HG 419583 34 Bulgarian.HO SRB_Iron_Gates_HG Mbuti.DG TUR_C_Boncuklu_PPN 554983 35 Bulgarian.HO SRB_Iron_Gates_HG Mbuti.DG TUR_Pinarbasi_EpiP 449633 36 Bulgarian.HO SRB_Iron_Gates_HG Mbuti.DG WHG 583556 37 Bulgarian.HO TUR_Marmara_Barcin_N Mbuti.DG IRN_Ganj_Dareh_N 554233 38 Bulgarian.HO TUR_Marmara_Barcin_N Mbuti.DG ISR_Natufian_EpiP 283906 39 Bulgarian.HO TUR_Marmara_Barcin_N Mbuti.DG MAR_Taforalt_EpiP 568728 40 Bulgarian.HO TUR_Marmara_Barcin_N Mbuti.DG Mesopotamia 454131 41 Bulgarian.HO TUR_Marmara_Barcin_N Mbuti.DG RUS_AfontovaGora3 161369 42 Bulgarian.HO TUR_Marmara_Barcin_N Mbuti.DG RUS_MA1_HG 420575 43 Bulgarian.HO TUR_Marmara_Barcin_N Mbuti.DG TUR_C_Boncuklu_PPN 555730 44 Bulgarian.HO TUR_Marmara_Barcin_N Mbuti.DG TUR_Pinarbasi_EpiP 449932 45 Bulgarian.HO TUR_Marmara_Barcin_N Mbuti.DG WHG 585160 ℹ Computing admixture weights... ℹ Computing standard errors... ℹ Computing number of admixture waves... warning: solve(): system is singular (rcond: 2.48874e-17); attempting approx solution warning: solve(): system is singular (rcond: 7.78132e-18); attempting approx solution warning: solve(): system is singular (rcond: 8.62477e-19); attempting approx solution > result_qpadm_Ryahovets$weights # A tibble: 5 × 5 target left weight se z <chr> <chr> <dbl> <dbl> <dbl> 1 Bulgarian.HO CHG 0.278 0.0158 17.6 2 Bulgarian.HO EHG 0.150 0.0145 10.4 3 Bulgarian.HO Levant_PPN 0.0268 0.0209 1.28 4 Bulgarian.HO SRB_Iron_Gates_HG 0.120 0.0106 11.3 5 Bulgarian.HO TUR_Marmara_Barcin_N 0.426 0.0225 18.9 > ф4: f4( + "C:/AdmixTools/Dataset/v54.1.p1_HO_public", + "Bulgarian.HO", + "Mbuti.DG", + "EHG", + "CHG" + ) ℹ Getting population combinations... ℹ 1 population combinations found ℹ Computing from f4 from genotype data... ℹ Reading metadata... ℹ Computing block lengths for 593124 SNPs... ℹ Computing 1 f4-statistics for block 711 out of 711... ℹ Summarize across blocks... # A tibble: 1 × 9 pop1 pop2 pop3 pop4 est se z p n <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> 1 Bulgarian.HO Mbuti.DG EHG CHG 0.00176 0.000340 5.17 0.000000229 578104 >

Напредваме, дами и господа Смених датасета с по-леката версия, изкарах Мбути на първа линия и ето го резултатът: result_qpadm_Ryahovets = qpadm( + data = "C:/AdmixTools/Dataset/v54.1.p1_HO_public", + left = c( + "CHG", + "EHG", + "Levant_PPN", + "SRB_Iron_Gates_HG", + "TUR_Marmara_Barcin_N" + ), + right = c( + "Mbuti.DG", + "IRN_Ganj_Dareh_N", + "ISR_Natufian_EpiP", + "MAR_Taforalt_EpiP", + "Mesopotamia", + "RUS_AfontovaGora3", + "RUS_MA1_HG", + "TUR_C_Boncuklu_PPN", + "TUR_Pinarbasi_EpiP", + "WHG" + ), + target = "BGR_Ryahovets_Mdv", + allsnps = T + ) ℹ Reading metadata... ℹ Computing block lengths for 593124 SNPs... ℹ Computing 45 f4-statistics for block 711 out of 711... ℹ "allsnps = TRUE" uses different SNPs for each f4-statistic Number of SNPs used for each f4-statistic: pop1 pop2 pop3 pop4 n 1 BGR_Ryahovets_Mdv CHG Mbuti.DG IRN_Ganj_Dareh_N 425316 2 BGR_Ryahovets_Mdv CHG Mbuti.DG ISR_Natufian_EpiP 237370 3 BGR_Ryahovets_Mdv CHG Mbuti.DG MAR_Taforalt_EpiP 427613 4 BGR_Ryahovets_Mdv CHG Mbuti.DG Mesopotamia 363195 5 BGR_Ryahovets_Mdv CHG Mbuti.DG RUS_AfontovaGora3 137111 6 BGR_Ryahovets_Mdv CHG Mbuti.DG RUS_MA1_HG 315090 7 BGR_Ryahovets_Mdv CHG Mbuti.DG TUR_C_Boncuklu_PPN 420116 8 BGR_Ryahovets_Mdv CHG Mbuti.DG TUR_Pinarbasi_EpiP 355376 9 BGR_Ryahovets_Mdv CHG Mbuti.DG WHG 431999 10 BGR_Ryahovets_Mdv EHG Mbuti.DG IRN_Ganj_Dareh_N 423252 11 BGR_Ryahovets_Mdv EHG Mbuti.DG ISR_Natufian_EpiP 236421 12 BGR_Ryahovets_Mdv EHG Mbuti.DG MAR_Taforalt_EpiP 425594 13 BGR_Ryahovets_Mdv EHG Mbuti.DG Mesopotamia 361593 14 BGR_Ryahovets_Mdv EHG Mbuti.DG RUS_AfontovaGora3 136766 15 BGR_Ryahovets_Mdv EHG Mbuti.DG RUS_MA1_HG 313485 16 BGR_Ryahovets_Mdv EHG Mbuti.DG TUR_C_Boncuklu_PPN 418080 17 BGR_Ryahovets_Mdv EHG Mbuti.DG TUR_Pinarbasi_EpiP 353800 18 BGR_Ryahovets_Mdv EHG Mbuti.DG WHG 429725 19 BGR_Ryahovets_Mdv Levant_PPN Mbuti.DG IRN_Ganj_Dareh_N 359420 20 BGR_Ryahovets_Mdv Levant_PPN Mbuti.DG ISR_Natufian_EpiP 216151 21 BGR_Ryahovets_Mdv Levant_PPN Mbuti.DG MAR_Taforalt_EpiP 359387 22 BGR_Ryahovets_Mdv Levant_PPN Mbuti.DG Mesopotamia 317689 23 BGR_Ryahovets_Mdv Levant_PPN Mbuti.DG RUS_AfontovaGora3 124359 24 BGR_Ryahovets_Mdv Levant_PPN Mbuti.DG RUS_MA1_HG 265619 25 BGR_Ryahovets_Mdv Levant_PPN Mbuti.DG TUR_C_Boncuklu_PPN 354220 26 BGR_Ryahovets_Mdv Levant_PPN Mbuti.DG TUR_Pinarbasi_EpiP 306934 27 BGR_Ryahovets_Mdv Levant_PPN Mbuti.DG WHG 361278 28 BGR_Ryahovets_Mdv SRB_Iron_Gates_HG Mbuti.DG IRN_Ganj_Dareh_N 425679 29 BGR_Ryahovets_Mdv SRB_Iron_Gates_HG Mbuti.DG ISR_Natufian_EpiP 237528 30 BGR_Ryahovets_Mdv SRB_Iron_Gates_HG Mbuti.DG MAR_Taforalt_EpiP 427936 31 BGR_Ryahovets_Mdv SRB_Iron_Gates_HG Mbuti.DG Mesopotamia 363460 32 BGR_Ryahovets_Mdv SRB_Iron_Gates_HG Mbuti.DG RUS_AfontovaGora3 137212 33 BGR_Ryahovets_Mdv SRB_Iron_Gates_HG Mbuti.DG RUS_MA1_HG 315293 34 BGR_Ryahovets_Mdv SRB_Iron_Gates_HG Mbuti.DG TUR_C_Boncuklu_PPN 420419 35 BGR_Ryahovets_Mdv SRB_Iron_Gates_HG Mbuti.DG TUR_Pinarbasi_EpiP 355633 36 BGR_Ryahovets_Mdv SRB_Iron_Gates_HG Mbuti.DG WHG 432303 37 BGR_Ryahovets_Mdv TUR_Marmara_Barcin_N Mbuti.DG IRN_Ganj_Dareh_N 425706 38 BGR_Ryahovets_Mdv TUR_Marmara_Barcin_N Mbuti.DG ISR_Natufian_EpiP 237535 39 BGR_Ryahovets_Mdv TUR_Marmara_Barcin_N Mbuti.DG MAR_Taforalt_EpiP 428004 40 BGR_Ryahovets_Mdv TUR_Marmara_Barcin_N Mbuti.DG Mesopotamia 363480 41 BGR_Ryahovets_Mdv TUR_Marmara_Barcin_N Mbuti.DG RUS_AfontovaGora3 137215 42 BGR_Ryahovets_Mdv TUR_Marmara_Barcin_N Mbuti.DG RUS_MA1_HG 315367 43 BGR_Ryahovets_Mdv TUR_Marmara_Barcin_N Mbuti.DG TUR_C_Boncuklu_PPN 420488 44 BGR_Ryahovets_Mdv TUR_Marmara_Barcin_N Mbuti.DG TUR_Pinarbasi_EpiP 355662 45 BGR_Ryahovets_Mdv TUR_Marmara_Barcin_N Mbuti.DG WHG 432413 ℹ Computing admixture weights... ℹ Computing standard errors... ℹ Computing number of admixture waves... warning: solve(): system is singular (rcond: 2.48275e-17); attempting approx solution warning: solve(): system is singular (rcond: 5.59683e-18); attempting approx solution warning: solve(): system is singular (rcond: 7.05606e-19); attempting approx solution > result_qpadm_Ryahovets$weights # A tibble: 5 × 5 target left weight se z <chr> <chr> <dbl> <dbl> <dbl> 1 BGR_Ryahovets_Mdv CHG 0.307 0.0424 7.24 2 BGR_Ryahovets_Mdv EHG 0.200 0.0359 5.59 3 BGR_Ryahovets_Mdv Levant_PPN 0.0356 0.0558 0.638 4 BGR_Ryahovets_Mdv SRB_Iron_Gates_HG 0.0994 0.0243 4.09 5 BGR_Ryahovets_Mdv TUR_Marmara_Barcin_N 0.357 0.0598 5.98 > Сниповете паднаха, но пък КЛС и ИЕЛС достигнаха нивата на Южната дъга! 31% и 20% съответно. Другите компоненти шават насам-натам, ама нас това вече слабо ни интересува Впрочем, всички тези упражнения имат чисто учебна стойност, защото ф4 и при новия датасет все си е положителна... f4( + "C:/AdmixTools/Dataset/v54.1.p1_HO_public", + "BGR_Ryahovets_Mdv", + "Mbuti.DG", + "EHG", + "CHG" + ) ℹ Getting population combinations... ℹ 1 population combinations found ℹ Computing from f4 from genotype data... ℹ Reading metadata... ℹ Computing block lengths for 593124 SNPs... ℹ Computing 1 f4-statistics for block 711 out of 711... ℹ Summarize across blocks... # A tibble: 1 × 9 pop1 pop2 pop3 pop4 est se z p n <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> 1 BGR_Ryahovets_Mdv Mbuti.DG EHG CHG 0.00234 0.000562 4.17 0.0000310 429339 >

Атомната енергия в сегашния и вид е морално остаряла. За добро или лошо САЩ изостават технологично в тази област, а руснаците изпитват всякакъв вид трудности. Може би трябва да се изчака с мащабните проекти, докато се избистри положението. А тогава нищо чудно китайците да се окажат на дневен ред.

И самите българи, пак в тази схема: > qpadm( + data = "C:/AdmixTools/Dataset/v54.1.p1_1240K_public", + left = c( + "CHG", + "EHG", + "Levant_PPN", + "SRB_Iron_Gates_HG", + "TUR_Marmara_Barcin_N" + ), + right = c( + "IRN_Ganj_Dareh_N", + "ISR_Natufian_EpiP", + "MAR_Taforalt_EpiP", + "Mbuti.DG", + "Mesopotamia", + "RUS_AfontovaGora3", + "RUS_MA1_HG", + "TUR_C_Boncuklu_PPN", + "TUR_Pinarbasi_EpiP", + "WHG" + ), + target = "Bulgarian.DG", + allsnps = T + ) ℹ Reading metadata... ℹ Computing block lengths for 1150639 SNPs... ℹ Computing 45 f4-statistics for block 713 out of 713... ℹ "allsnps = TRUE" uses different SNPs for each f4-statistic Number of SNPs used for each f4-statistic: pop1 pop2 pop3 pop4 n 1 Bulgarian.DG CHG IRN_Ganj_Dareh_N ISR_Natufian_EpiP 160508 2 Bulgarian.DG CHG IRN_Ganj_Dareh_N MAR_Taforalt_EpiP 997344 3 Bulgarian.DG CHG IRN_Ganj_Dareh_N Mbuti.DG 1029914 4 Bulgarian.DG CHG IRN_Ganj_Dareh_N Mesopotamia 820659 5 Bulgarian.DG CHG IRN_Ganj_Dareh_N RUS_AfontovaGora3 257424 6 Bulgarian.DG CHG IRN_Ganj_Dareh_N RUS_MA1_HG 733035 7 Bulgarian.DG CHG IRN_Ganj_Dareh_N TUR_C_Boncuklu_PPN 985252 8 Bulgarian.DG CHG IRN_Ganj_Dareh_N TUR_Pinarbasi_EpiP 800247 9 Bulgarian.DG CHG IRN_Ganj_Dareh_N WHG 1029826 10 Bulgarian.DG EHG IRN_Ganj_Dareh_N ISR_Natufian_EpiP 154256 11 Bulgarian.DG EHG IRN_Ganj_Dareh_N MAR_Taforalt_EpiP 938341 12 Bulgarian.DG EHG IRN_Ganj_Dareh_N Mbuti.DG 957819 13 Bulgarian.DG EHG IRN_Ganj_Dareh_N Mesopotamia 778206 14 Bulgarian.DG EHG IRN_Ganj_Dareh_N RUS_AfontovaGora3 251015 15 Bulgarian.DG EHG IRN_Ganj_Dareh_N RUS_MA1_HG 684961 16 Bulgarian.DG EHG IRN_Ganj_Dareh_N TUR_C_Boncuklu_PPN 923234 17 Bulgarian.DG EHG IRN_Ganj_Dareh_N TUR_Pinarbasi_EpiP 757902 18 Bulgarian.DG EHG IRN_Ganj_Dareh_N WHG 957764 19 Bulgarian.DG Levant_PPN IRN_Ganj_Dareh_N ISR_Natufian_EpiP 146586 20 Bulgarian.DG Levant_PPN IRN_Ganj_Dareh_N MAR_Taforalt_EpiP 782579 21 Bulgarian.DG Levant_PPN IRN_Ganj_Dareh_N Mbuti.DG 793432 22 Bulgarian.DG Levant_PPN IRN_Ganj_Dareh_N Mesopotamia 683175 23 Bulgarian.DG Levant_PPN IRN_Ganj_Dareh_N RUS_AfontovaGora3 228954 24 Bulgarian.DG Levant_PPN IRN_Ganj_Dareh_N RUS_MA1_HG 574127 25 Bulgarian.DG Levant_PPN IRN_Ganj_Dareh_N TUR_C_Boncuklu_PPN 772871 26 Bulgarian.DG Levant_PPN IRN_Ganj_Dareh_N TUR_Pinarbasi_EpiP 655670 27 Bulgarian.DG Levant_PPN IRN_Ganj_Dareh_N WHG 793411 28 Bulgarian.DG SRB_Iron_Gates_HG IRN_Ganj_Dareh_N ISR_Natufian_EpiP 160662 29 Bulgarian.DG SRB_Iron_Gates_HG IRN_Ganj_Dareh_N MAR_Taforalt_EpiP 998165 30 Bulgarian.DG SRB_Iron_Gates_HG IRN_Ganj_Dareh_N Mbuti.DG 1030158 31 Bulgarian.DG SRB_Iron_Gates_HG IRN_Ganj_Dareh_N Mesopotamia 821471 32 Bulgarian.DG SRB_Iron_Gates_HG IRN_Ganj_Dareh_N RUS_AfontovaGora3 257723 33 Bulgarian.DG SRB_Iron_Gates_HG IRN_Ganj_Dareh_N RUS_MA1_HG 733225 34 Bulgarian.DG SRB_Iron_Gates_HG IRN_Ganj_Dareh_N TUR_C_Boncuklu_PPN 985947 35 Bulgarian.DG SRB_Iron_Gates_HG IRN_Ganj_Dareh_N TUR_Pinarbasi_EpiP 800920 36 Bulgarian.DG SRB_Iron_Gates_HG IRN_Ganj_Dareh_N WHG 1030068 37 Bulgarian.DG TUR_Marmara_Barcin_N IRN_Ganj_Dareh_N ISR_Natufian_EpiP 160658 38 Bulgarian.DG TUR_Marmara_Barcin_N IRN_Ganj_Dareh_N MAR_Taforalt_EpiP 997836 39 Bulgarian.DG TUR_Marmara_Barcin_N IRN_Ganj_Dareh_N Mbuti.DG 1029380 40 Bulgarian.DG TUR_Marmara_Barcin_N IRN_Ganj_Dareh_N Mesopotamia 821280 41 Bulgarian.DG TUR_Marmara_Barcin_N IRN_Ganj_Dareh_N RUS_AfontovaGora3 257719 42 Bulgarian.DG TUR_Marmara_Barcin_N IRN_Ganj_Dareh_N RUS_MA1_HG 732812 43 Bulgarian.DG TUR_Marmara_Barcin_N IRN_Ganj_Dareh_N TUR_C_Boncuklu_PPN 985461 44 Bulgarian.DG TUR_Marmara_Barcin_N IRN_Ganj_Dareh_N TUR_Pinarbasi_EpiP 800733 45 Bulgarian.DG TUR_Marmara_Barcin_N IRN_Ganj_Dareh_N WHG 1029288 ℹ Computing admixture weights... ℹ Computing standard errors... ℹ Computing number of admixture waves... warning: solve(): system is singular (rcond: 1.17997e-17); attempting approx solution warning: solve(): system is singular (rcond: 4.76662e-19); attempting approx solution warning: solve(): system is singular (rcond: 7.88902e-19); attempting approx solution $weights # A tibble: 5 × 5 target left weight se z <chr> <chr> <dbl> <dbl> <dbl> 1 Bulgarian.DG CHG 0.291 0.0251 11.6 2 Bulgarian.DG EHG 0.120 0.0216 5.58 3 Bulgarian.DG Levant_PPN 0.0837 0.0349 2.40 4 Bulgarian.DG SRB_Iron_Gates_HG 0.130 0.0156 8.32 5 Bulgarian.DG TUR_Marmara_Barcin_N 0.375 0.0361 10.4 $rankdrop # A tibble: 5 × 7 f4rank dof chisq p dofdiff chisqdiff p_nested <int> <int> <dbl> <dbl> <int> <dbl> <dbl> 1 4 5 29.9 1.57e- 5 7 527. 1.19e-109 2 3 12 557. 1.61e-111 9 859. 3.94e-179 3 2 21 1416. 3.34e-287 11 2037. 0 4 1 32 3453. 0 13 6889. 0 5 0 45 10342. 0 NA NA NA $popdrop # A tibble: 31 × 16 pat wt dof chisq p f4rank CHG EHG Levant_PPN SRB_Iron_Gates_HG <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> 1 00000 0 5 29.9 1.57e- 5 4 0.291 0.120 0.0837 0.130 2 00001 1 6 236. 4.04e- 48 3 0.356 0.115 0.374 0.156 3 00010 1 6 162. 1.88e- 32 3 0.257 0.246 0.122 NA 4 00100 1 6 52.6 1.40e- 9 3 0.312 0.110 NA 0.133 5 01000 1 6 82.8 9.27e- 16 3 0.388 NA 0.0509 0.187 6 10000 1 6 230. 7.77e- 47 3 NA 0.279 0.211 0.0694 7 00011 2 7 407. 7.10e- 84 2 0.201 0.301 0.498 NA 8 00101 2 7 496. 5.90e-103 2 0.823 -0.0805 NA 0.258 9 00110 2 7 230. 5.22e- 46 2 0.271 0.248 NA NA 10 01001 2 7 301. 3.01e- 61 2 0.463 NA 0.329 0.208 # ℹ 21 more rows # ℹ 6 more variables: TUR_Marmara_Barcin_N <dbl>, feasible <lgl>, best <lgl>, dofdiff <dbl>, # chisqdiff <dbl>, p_nested <dbl> # ℹ Use `print(n = ...)` to see more rows >

ПП Утре, ако остане време, ще мина през църквата да запаля една свещичка. Може още малко да се качи.

Мани-мани. Движим се в грешната посока. Трябва да го качим тоя CHG, че иначе язък за барута. Най-добрият ми резултат досега (трябва да се смята привечер, на тиха музика): > qpadm( + data = "C:/AdmixTools/Dataset/v54.1.p1_1240K_public", + left = c( + "CHG", + "EHG", + "Levant_PPN", + "SRB_Iron_Gates_HG", + "TUR_Marmara_Barcin_N" + ), + right = c( + "IRN_Ganj_Dareh_N", + "ISR_Natufian_EpiP", + "MAR_Taforalt_EpiP", + "Mbuti.DG", + "Mesopotamia", + "RUS_AfontovaGora3", + "RUS_MA1_HG", + "TUR_C_Boncuklu_PPN", + "TUR_Pinarbasi_EpiP", + "WHG" + ), + target = "BGR_Ryahovets_Mdv", + allsnps = T + ) ℹ Reading metadata... ℹ Computing block lengths for 1150639 SNPs... ℹ Computing 45 f4-statistics for block 713 out of 713... ℹ "allsnps = TRUE" uses different SNPs for each f4-statistic Number of SNPs used for each f4-statistic: pop1 pop2 pop3 pop4 n 1 BGR_Ryahovets_Mdv CHG IRN_Ganj_Dareh_N ISR_Natufian_EpiP 143473 2 BGR_Ryahovets_Mdv CHG IRN_Ganj_Dareh_N MAR_Taforalt_EpiP 792952 3 BGR_Ryahovets_Mdv CHG IRN_Ganj_Dareh_N Mbuti.DG 802867 4 BGR_Ryahovets_Mdv CHG IRN_Ganj_Dareh_N Mesopotamia 681995 5 BGR_Ryahovets_Mdv CHG IRN_Ganj_Dareh_N RUS_AfontovaGora3 229459 6 BGR_Ryahovets_Mdv CHG IRN_Ganj_Dareh_N RUS_MA1_HG 579754 7 BGR_Ryahovets_Mdv CHG IRN_Ganj_Dareh_N TUR_C_Boncuklu_PPN 781910 8 BGR_Ryahovets_Mdv CHG IRN_Ganj_Dareh_N TUR_Pinarbasi_EpiP 660444 9 BGR_Ryahovets_Mdv CHG IRN_Ganj_Dareh_N WHG 803231 10 BGR_Ryahovets_Mdv EHG IRN_Ganj_Dareh_N ISR_Natufian_EpiP 139193 11 BGR_Ryahovets_Mdv EHG IRN_Ganj_Dareh_N MAR_Taforalt_EpiP 762693 12 BGR_Ryahovets_Mdv EHG IRN_Ganj_Dareh_N Mbuti.DG 769527 13 BGR_Ryahovets_Mdv EHG IRN_Ganj_Dareh_N Mesopotamia 657988 14 BGR_Ryahovets_Mdv EHG IRN_Ganj_Dareh_N RUS_AfontovaGora3 224990 15 BGR_Ryahovets_Mdv EHG IRN_Ganj_Dareh_N RUS_MA1_HG 556655 16 BGR_Ryahovets_Mdv EHG IRN_Ganj_Dareh_N TUR_C_Boncuklu_PPN 751090 17 BGR_Ryahovets_Mdv EHG IRN_Ganj_Dareh_N TUR_Pinarbasi_EpiP 636837 18 BGR_Ryahovets_Mdv EHG IRN_Ganj_Dareh_N WHG 769897 19 BGR_Ryahovets_Mdv Levant_PPN IRN_Ganj_Dareh_N ISR_Natufian_EpiP 134395 20 BGR_Ryahovets_Mdv Levant_PPN IRN_Ganj_Dareh_N MAR_Taforalt_EpiP 672902 21 BGR_Ryahovets_Mdv Levant_PPN IRN_Ganj_Dareh_N Mbuti.DG 677430 22 BGR_Ryahovets_Mdv Levant_PPN IRN_Ganj_Dareh_N Mesopotamia 599021 23 BGR_Ryahovets_Mdv Levant_PPN IRN_Ganj_Dareh_N RUS_AfontovaGora3 210160 24 BGR_Ryahovets_Mdv Levant_PPN IRN_Ganj_Dareh_N RUS_MA1_HG 493493 25 BGR_Ryahovets_Mdv Levant_PPN IRN_Ganj_Dareh_N TUR_C_Boncuklu_PPN 664470 26 BGR_Ryahovets_Mdv Levant_PPN IRN_Ganj_Dareh_N TUR_Pinarbasi_EpiP 574494 27 BGR_Ryahovets_Mdv Levant_PPN IRN_Ganj_Dareh_N WHG 677759 28 BGR_Ryahovets_Mdv SRB_Iron_Gates_HG IRN_Ganj_Dareh_N ISR_Natufian_EpiP 143634 29 BGR_Ryahovets_Mdv SRB_Iron_Gates_HG IRN_Ganj_Dareh_N MAR_Taforalt_EpiP 794044 30 BGR_Ryahovets_Mdv SRB_Iron_Gates_HG IRN_Ganj_Dareh_N Mbuti.DG 803953 31 BGR_Ryahovets_Mdv SRB_Iron_Gates_HG IRN_Ganj_Dareh_N Mesopotamia 682830 32 BGR_Ryahovets_Mdv SRB_Iron_Gates_HG IRN_Ganj_Dareh_N RUS_AfontovaGora3 229748 33 BGR_Ryahovets_Mdv SRB_Iron_Gates_HG IRN_Ganj_Dareh_N RUS_MA1_HG 580406 34 BGR_Ryahovets_Mdv SRB_Iron_Gates_HG IRN_Ganj_Dareh_N TUR_C_Boncuklu_PPN 782885 35 BGR_Ryahovets_Mdv SRB_Iron_Gates_HG IRN_Ganj_Dareh_N TUR_Pinarbasi_EpiP 661212 36 BGR_Ryahovets_Mdv SRB_Iron_Gates_HG IRN_Ganj_Dareh_N WHG 804356 37 BGR_Ryahovets_Mdv TUR_Marmara_Barcin_N IRN_Ganj_Dareh_N ISR_Natufian_EpiP 143633 38 BGR_Ryahovets_Mdv TUR_Marmara_Barcin_N IRN_Ganj_Dareh_N MAR_Taforalt_EpiP 793965 39 BGR_Ryahovets_Mdv TUR_Marmara_Barcin_N IRN_Ganj_Dareh_N Mbuti.DG 803814 40 BGR_Ryahovets_Mdv TUR_Marmara_Barcin_N IRN_Ganj_Dareh_N Mesopotamia 682784 41 BGR_Ryahovets_Mdv TUR_Marmara_Barcin_N IRN_Ganj_Dareh_N RUS_AfontovaGora3 229745 42 BGR_Ryahovets_Mdv TUR_Marmara_Barcin_N IRN_Ganj_Dareh_N RUS_MA1_HG 580330 43 BGR_Ryahovets_Mdv TUR_Marmara_Barcin_N IRN_Ganj_Dareh_N TUR_C_Boncuklu_PPN 782797 44 BGR_Ryahovets_Mdv TUR_Marmara_Barcin_N IRN_Ganj_Dareh_N TUR_Pinarbasi_EpiP 661171 45 BGR_Ryahovets_Mdv TUR_Marmara_Barcin_N IRN_Ganj_Dareh_N WHG 804215 ℹ Computing admixture weights... ℹ Computing standard errors... ℹ Computing number of admixture waves... warning: solve(): system is singular (rcond: 2.38973e-17); attempting approx solution warning: solve(): system is singular (rcond: 9.83176e-18); attempting approx solution warning: solve(): system is singular (rcond: 3.92669e-18); attempting approx solution $weights # A tibble: 5 × 5 target left weight se z <chr> <chr> <dbl> <dbl> <dbl> 1 BGR_Ryahovets_Mdv CHG 0.279 0.0343 8.11 2 BGR_Ryahovets_Mdv EHG 0.231 0.0305 7.57 3 BGR_Ryahovets_Mdv Levant_PPN 0.0806 0.0543 1.48 4 BGR_Ryahovets_Mdv SRB_Iron_Gates_HG 0.0799 0.0208 3.85 5 BGR_Ryahovets_Mdv TUR_Marmara_Barcin_N 0.330 0.0566 5.83 $rankdrop # A tibble: 5 × 7 f4rank dof chisq p dofdiff chisqdiff p_nested <int> <int> <dbl> <dbl> <int> <dbl> <dbl> 1 4 5 13.9 1.60e- 2 7 505. 7.06e-105 2 3 12 519. 2.15e-103 9 814. 1.67e-169 3 2 21 1333. 1.83e-269 11 1944. 0 4 1 32 3277. 0 13 6448. 0 5 0 45 9725. 0 NA NA NA $popdrop # A tibble: 31 × 16 pat wt dof chisq p f4rank CHG EHG Levant_PPN SRB_Iron_Gates_HG <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> 1 00000 0 5 13.9 1.60e- 2 4 0.279 0.231 0.0806 0.0799 2 00001 1 6 170. 5.40e-34 3 0.329 0.237 0.336 0.0983 3 00010 1 6 73.0 1.00e-13 3 0.277 0.290 0.0734 NA 4 00100 1 6 29.4 5.00e- 5 3 0.302 0.222 NA 0.0760 5 01000 1 6 112. 9.12e-22 3 0.457 NA 0.0498 0.186 6 10000 1 6 150. 9.49e-30 3 NA 0.392 0.195 0.0201 7 00011 2 7 255. 2.93e-51 2 0.272 0.345 0.384 NA 8 00101 2 7 405. 2.18e-83 2 0.721 0.113 NA 0.166 9 00110 2 7 95.5 9.13e-18 2 0.281 0.294 NA NA 10 01001 2 7 343. 4.35e-70 2 0.569 NA 0.227 0.205 # ℹ 21 more rows # ℹ 6 more variables: TUR_Marmara_Barcin_N <dbl>, feasible <lgl>, best <lgl>, dofdiff <dbl>, # chisqdiff <dbl>, p_nested <dbl> # ℹ Use `print(n = ...)` to see more rows

А това са всички образци, които ползва в 5-компонентния модел, калибрирани спрямо официалния файл на Райх: V1 V2 1 SATP_noUDG.SG CHG 2 KK1_noUDG.SG CHG 3 I0211 EHG 4 I0061 EHG 5 I0124 EHG 6 I1954 IRN_Ganj_Dareh_N 7 I1947 IRN_Ganj_Dareh_N 8 I7527 IRN_Ganj_Dareh_N 9 I1290 IRN_Ganj_Dareh_N 10 I1945 IRN_Ganj_Dareh_N 11 I1687_d ISR_Natufian_EpiP 12 I1690 ISR_Natufian_EpiP 13 I1069 ISR_Natufian_EpiP 14 I0861_d ISR_Natufian_EpiP 15 I1072_d ISR_Natufian_EpiP 16 I1685_d ISR_Natufian_EpiP 17 I0867 Levant_PPN 18 I1414 Levant_PPN 19 I1700 Levant_PPN 20 I1709 Levant_PPN 21 I8554 Levant_PPN 22 I1415 Levant_PPN 23 I1701 Levant_PPN 24 I1710 Levant_PPN 25 I1679 Levant_PPN 26 I1699 Levant_PPN 27 TAF010_noUDG MAR_Taforalt_EpiP 28 TAF015_noUDG MAR_Taforalt_EpiP 29 TAF014_noUDG MAR_Taforalt_EpiP 30 TAF013_noUDG MAR_Taforalt_EpiP 31 TAF011_noUDG MAR_Taforalt_EpiP 32 TAF009_noUDG MAR_Taforalt_EpiP 33 B_Mbuti-4.DG Mbuti.DG 34 S_Mbuti-2.DG Mbuti.DG 35 S_Mbuti-1.DG Mbuti.DG 36 S_Mbuti-3.DG Mbuti.DG 37 I6445 Mesopotamia 38 I6457 Mesopotamia 39 I6441 Mesopotamia 40 I8432 Mesopotamia 41 AfontovaGora3_noUDG_d RUS_AfontovaGora3 42 MA1_noUDG.SG RUS_MA1_HG 43 I4657 SRB_Iron_Gates_HG 44 I5235 SRB_Iron_Gates_HG 45 I5240 SRB_Iron_Gates_HG 46 I5244 SRB_Iron_Gates_HG 47 I5242 SRB_Iron_Gates_HG 48 I5239 SRB_Iron_Gates_HG 49 I5773 SRB_Iron_Gates_HG 50 I5236 SRB_Iron_Gates_HG 51 I5238 SRB_Iron_Gates_HG 52 I5772 SRB_Iron_Gates_HG 53 I5771 SRB_Iron_Gates_HG 54 I4872 SRB_Iron_Gates_HG 55 I4871 SRB_Iron_Gates_HG 56 I4660 SRB_Iron_Gates_HG 57 I5409 SRB_Iron_Gates_HG 58 I5237 SRB_Iron_Gates_HG 59 I5234 SRB_Iron_Gates_HG 60 I5401 SRB_Iron_Gates_HG 61 I4916 SRB_Iron_Gates_HG 62 I4870 SRB_Iron_Gates_HG 63 I4877 SRB_Iron_Gates_HG 64 I4874 SRB_Iron_Gates_HG 65 I4875 SRB_Iron_Gates_HG 66 I4876 SRB_Iron_Gates_HG 67 I4881 SRB_Iron_Gates_HG 68 I5402 SRB_Iron_Gates_HG 69 I4915 SRB_Iron_Gates_HG 70 I4914 SRB_Iron_Gates_HG 71 I4917 SRB_Iron_Gates_HG 72 I5233 SRB_Iron_Gates_HG 73 I5407 SRB_Iron_Gates_HG 74 I4873 SRB_Iron_Gates_HG 75 I4880 SRB_Iron_Gates_HG 76 I4878 SRB_Iron_Gates_HG 77 ZHJ_BON024.A0101_Luk84 TUR_C_Boncuklu_PPN 78 ZMOJ_BON014.A0101_Luk21 TUR_C_Boncuklu_PPN 79 ZKO_BON001.A0101_Luk7 TUR_C_Boncuklu_PPN 80 ZHAJ_BON034.A0101_Luk9 TUR_C_Boncuklu_PPN 81 ZHAG_BON004.A0101_Luk10 TUR_C_Boncuklu_PPN 82 I1103 TUR_Marmara_Barcin_N 83 I1102 TUR_Marmara_Barcin_N 84 I1101 TUR_Marmara_Barcin_N 85 I1100 TUR_Marmara_Barcin_N 86 I1099 TUR_Marmara_Barcin_N 87 I1096 TUR_Marmara_Barcin_N 88 I0736 TUR_Marmara_Barcin_N 89 I1098 TUR_Marmara_Barcin_N 90 I1097 TUR_Marmara_Barcin_N 91 I1583 TUR_Marmara_Barcin_N 92 I0744 TUR_Marmara_Barcin_N 93 I1581 TUR_Marmara_Barcin_N 94 I0745 TUR_Marmara_Barcin_N 95 I1580 TUR_Marmara_Barcin_N 96 I0708 TUR_Marmara_Barcin_N 97 I0707 TUR_Marmara_Barcin_N 98 I0709 TUR_Marmara_Barcin_N 99 I1579 TUR_Marmara_Barcin_N 100 I1585 TUR_Marmara_Barcin_N 101 I0746 TUR_Marmara_Barcin_N 102 ZBC_IPB001.B-C0101_Luk2-Pinarbasi TUR_Pinarbasi_EpiP 103 Villabruna_noUDG WHG 104 Loschbour_snpAD.DG WHG 105 LaBrana1_noUDG.SG WHG 106 Bichon_noUDG.SG WHG >

I10548 F BGR_Ryahovets_Mdv KK1_noUDG.SG M CHG SATP_noUDG.SG M CHG I0061 M EHG I0211 M EHG I0124 M EHG Това са образците, които ползва Лазаридис. UzOO77 също е ИЕЛС, но по някаква причина не го е включил в популацията.

Стават грешки, но при него са една след друга. Вече му нямам вяра.

Ряховец е средновековно българско момиче с ID I10548, което се приема за прокси на съвременните българи. В модела на Лазаридис се води с излишък на КЛС спрямо ИЕЛС, което дава повод за обсъждане на всякакви кавказки миграци и прочее. Само че аз този излишък не го виждам. Може да ми трябват очила а може и да не ми трябват. Ще видим.

Хммм. Формално ф4 също потвърждава, че Ряховец има по-висок ИЕЛС компонент, отколкото КЛС... > f4 (dataset, "BGR_Ryahovets_Mdv", "Mbuti.DG", "EHG", "CHG") ℹ Getting population combinations... ℹ 1 population combinations found ℹ Computing from f4 from genotype data... ℹ Reading metadata... ℹ Computing block lengths for 1150639 SNPs... ℹ Computing 1 f4-statistics for block 713 out of 713... ℹ Summarize across blocks... # A tibble: 1 × 9 pop1 pop2 pop3 pop4 est se z p n <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> 1 BGR_Ryahovets_Mdv Mbuti.DG EHG CHG 0.00309 0.000515 6.01 0.00000000189 779763 >

Ряховец директно от файла, всяка ф4 с максимум наличи снипове. Не знам какво повече да му бая, че да заприлича на ЮД. > qpadm (dataset, pops_SA_left, pops_SA_right, 'BGR_Ryahovets_Mdv', allsns = T) ℹ Reading metadata... ℹ Computing block lengths for 1150639 SNPs... ℹ Computing 45 f4-statistics for block 713 out of 713... ℹ Number of SNPs after excluding those with missing data: 30201 ℹ Computing admixture weights... ℹ Computing standard errors... ℹ Computing number of admixture waves... warning: solve(): system is singular (rcond: 2.09067e-18); attempting approx solution warning: solve(): system is singular (rcond: 5.1679e-18); attempting approx solution warning: solve(): system is singular (rcond: 1.21638e-17); attempting approx solution $weights # A tibble: 5 × 5 target left weight se z <chr> <chr> <dbl> <dbl> <dbl> 1 BGR_Ryahovets_Mdv CHG 0.240 0.0817 2.93 2 BGR_Ryahovets_Mdv EHG 0.273 0.0765 3.56 3 BGR_Ryahovets_Mdv Levant_PPN 0.137 0.121 1.13 4 BGR_Ryahovets_Mdv SRB_Iron_Gates_HG 0.0218 0.0532 0.409 5 BGR_Ryahovets_Mdv TUR_Marmara_Barcin_N 0.329 0.125 2.62 $rankdrop # A tibble: 5 × 7 f4rank dof chisq p dofdiff chisqdiff p_nested <int> <int> <dbl> <dbl> <int> <dbl> <dbl> 1 4 5 3.50 6.23e- 1 7 115. 7.50e- 22 2 3 12 119. 1.10e- 19 9 165. 6.68e- 31 3 2 21 284. 6.29e- 48 11 498. 7.22e-100 4 1 32 782. 8.89e-144 13 2312. 0 5 0 45 3094. 0 NA NA NA $popdrop # A tibble: 31 × 16 pat wt dof chisq p f4rank CHG EHG Levant_PPN SRB_Iron_Gates_HG TUR_Marmara_Barcin_N feasible <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl> 1 00000 0 5 3.50 6.23e- 1 4 0.240 0.273 0.137 0.0218 0.329 TRUE 2 00001 1 6 41.0 2.89e- 7 3 0.307 0.275 0.388 0.0306 NA TRUE 3 00010 1 6 14.9 2.14e- 2 3 0.239 0.293 0.133 NA 0.335 TRUE 4 00100 1 6 10.0 1.24e- 1 3 0.284 0.252 NA 0.0274 0.436 TRUE 5 01000 1 6 28.7 6.79e- 5 3 0.451 NA 0.104 0.148 0.298 TRUE 6 10000 1 6 21.6 1.44e- 3 3 NA 0.410 0.247 -0.0268 0.370 FALSE 7 00011 2 7 49.3 2.01e- 8 2 0.290 0.302 0.408 NA NA TRUE 8 00101 2 7 92.8 3.23e-17 2 0.828 0.0408 NA 0.131 NA TRUE 9 00110 2 7 22.3 2.30e- 3 2 0.279 0.278 NA NA 0.443 TRUE 10 01001 2 7 80.6 1.04e-14 2 0.617 NA 0.240 0.143 NA TRUE # ℹ 21 more rows # ℹ 4 more variables: best <lgl>, dofdiff <dbl>, chisqdiff <dbl>, p_nested <dbl> # ℹ Use `print(n = ...)` to see more rows > Дясната група: > pops_SA_right [1] "IRN_Ganj_Dareh_N" "ISR_Natufian_EpiP" "MAR_Taforalt_EpiP" "Mbuti.DG" "Mesopotamia" [6] "RUS_AfontovaGora3" "RUS_MA1_HG" "TUR_C_Boncuklu_PPN" "TUR_Pinarbasi_EpiP" "WHG" > В суплемента на Лазаридис: We describe the implementation of the stages of our protocol below. In all the analyses of this section we use the following set of 15 “Right” outgroup populations: Base: Mbuti.DG(407), CHG(7), EHG(8, 9), IRN_Ganj_Dareh_N(10), ISR_Natufian_EpiP(10), Levant_PPN(10), MAR_Taforalt_EpiP(408), Mesopotamia, RUS_AfontovaGora3(75), RUS_MA1_HG(409), SRB_Iron_Gates_HG(3), TUR_C_Boncuklu_PPN(410), TUR_Marmara_Barcın_N ((9) and this study), TUR_Pınarbaşı_EpiP(410), WHG(25, 75, 411)

Мани майтапа, ама тоя qpAdm по три компонента е по-близо до Г25 и само по два - до ЮД Мойта сметка: target left weight se z <chr> <chr> <dbl> <dbl> <dbl> 1 BGR_Ryahovets_Mdv CHG 0.255 0.0815 3.13 2 BGR_Ryahovets_Mdv EHG 0.265 0.0746 3.56 3 BGR_Ryahovets_Mdv Levant_PPN 0.127 0.119 1.06 4 BGR_Ryahovets_Mdv SRB_Iron_Gates_HG 0.0317 0.0523 0.606 5 BGR_Ryahovets_Mdv TUR_Marmara_Barcin_N 0.321 0.120 2.68 Южната дъга: ID CHG EHG Levant_PPN SRB_Iron_Gates_HG TUR_Marmara_Barcın_N Population I10548 0.298 0.204 0.014 0.063 0.421 BGR_Ryahovets_Mdv Г25: И между другото екселският файл на ЮД не съвпада със суплемента...

Мамицата им неандерталска и всякакви други цървули, оставили са ме с 500 снипа. Сега прекомпилирах само с Ряховец и излязох на 29734. Не че резултатът има нещо общо с Южната дъга, ама поне не стряска... Нещо не съм възхитен от възпроизвеждането на модела. Уж всичко е както пише в суплемента, ама гредичка. Сигурно трябва да се бърникне по опциите.

Викам чакай ще пробвам да възпроизведа компонентите на Лазаридис. Оказа се, че съм голям оптимист # A tibble: 5 × 5 target left weight se z <chr> <chr> <dbl> <dbl> <dbl> 1 BGR_Ryahovets_Mdv CHG -0.573 1.36 -0.422 2 BGR_Ryahovets_Mdv EHG -0.556 1.72 -0.323 3 BGR_Ryahovets_Mdv Levant_PPN 2.26 2.90 0.780 4 BGR_Ryahovets_Mdv SRB_Iron_Gates_HG 0.204 1.11 0.185 5 BGR_Ryahovets_Mdv TUR_Marmara_Barcin_N -0.334 2.47 -0.135 Някакви идеи?

Подобна история. Гледам на плота по-малки дистанции до съвременните и средновековните българи, отколкото до неолитните. И не знам каква е тази история в публикациите пробите да са групирани по един начин, а в базата на Райх - по друг. Изкуствено се създават пречки пред възпроизводството на резултатите. Но нас това няма как да ни спре Впрочем, нищо чудно някъде да седи .ind с оригиналните етикети, не съм търсил.

А това са ф2/фст-дистанциите, които нито съответстват на аутгруп ф3, нито на реалния компонент ТМБ. f2(f2_blocks, "TUR_Barcin_N", pops) # A tibble: 5 × 4 pop1 pop2 est se <chr> <chr> <dbl> <dbl> 1 TUR_Barcin_N BGR_Ezero_EBA 0.0856 0.00172 2 TUR_Barcin_N BGR_KA_EIA 0.00842 0.000675 3 TUR_Barcin_N BGR_Late_C 0.0143 0.00101 4 TUR_Barcin_N BGR_Ryahovets 0.137 0.00203 5 TUR_Barcin_N Bulgarian.HO 0.00966 0.000439 Имам чувството, че тези функции са много чувствителни към естеството на пробите (брой, качество и др.), докато в Г25 всички тези фактори са елиминирани. Затова там простите дистанции може би са по-достоверни. Евентуално. С уговорки. Затова толкова хвалят Давидски, че знае как да ги филтрира и да ги гласи. Явно си е майсторлък.