Кухулин

Всъщност Лазаридис е прав, просто моделът му е грешен. В българския византиец има много ясен ямненски сигнал, вероятно на капитанандреевско ниво: Изобщо, тази византийска проба се очертава крайно интересна...

Не. Общо са над 20к проби от 16к индивида. Това за голямата база, с модерните (v54.1.p1_HO_public). За останалото си прав. Аз по принцип съм отделил най-тлъстата проба от всеки индивид и само нея включвам в популацията, ама няма да ти казвам каква играчка е да се програмира тоя филтър върху мърлявата база на Райх. Изобщо, имам чувството, че тия в Харвард нямат айтита, ами някакви биолози пишат по файловете. Или пари не им се дават...

Сега за пълнотата на горните модели. Кавказките алани дават много устойчив източноазиатски сигнал, за разлика от салтовците: Хубави мазни зетки, които правят долния модел доста силен, с около 5-6% ИА: Салтово: Според мен тук работата е доста съмнителна, но и покритието е ниско. Да видим какво ще покажат другите салтовски проби от новите руски изследвания.

По този върос Г25 и qpAdm горе-долу са в съгласие един с друг: В тази популация влизат всички кавказки алани: и "ядрото" от предните ми постове, и аутлаерът, и един алан с ниско покритие, който липсва в Г25. Моделът е много добър и се подкрепя от другите статистики (което не означава, че е пълен). Само сърбите издишат, но те и така са си около процент, та не е фатално. Салтовците са рехави откъм статистическа значимост - и тримата са сниско покритие. Обединеният им представител в Г25 даже и след обединението е слабичък по стандартите на Давидски, но въпреки това сходството на двата модела (Г25 и qpAdm) дава основание да се приемат за читави:

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...