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It could be but in that article it says North Caucasians living in Iraq are actually %75 Chechen/Dagestani origin.
"According to the information obtained from North Caucasians in Iraq, it might be suggested that Chechens in Iraq composes approximately 75 percent of North Caucasian population. "
There are 1890 listed North Caucasian families settled in Iraq and 1300-1400 of them have Chechen and Dagestani origins and rest of them are Adyghe.
Last edited by RatCat; 03-11-2021 at 03:57 PM.
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double post
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Great! If you want to filter out very old alleles common to all populations just repeat all the steps except this time do
/plink --bfile IBS --geno 0.001 --max-maf 0.30 --make-bed --out IBS1
This will filter out all minor alleles with frequency greater than 30% in IBS. You'll lose some SNPs but that's ok. The order of the pops will change a little based on more recent ancestry
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Can you guys stop posting that irrelevant stuff? I understand jack shit about those tables. You can call me stupid but if it ain't Gedmatch or G25, it's basically all Greek to me.
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1-2-Code:50 people (0 males, 0 females, 50 ambiguous) loaded from .fam. Ambiguous sex IDs written to IBS1.nosex . Using 1 thread (no multithreaded calculations invoked). Before main variant filters, 49 founders and 1 nonfounder present. Calculating allele frequencies... done. Warning: Nonmissing nonmale Y chromosome genotype(s) present; many commands treat these as missing. Total genotyping rate is 0.757664. 1032168 variants removed due to missing genotype data (--geno). 192952 variants removed due to minor allele threshold(s) (--maf/--max-maf/--mac/--max-mac). 353388 variants and 50 people pass filters and QC. Note: No phenotypes present. --make-bed to IBS1.bed + IBS1.bim + IBS1.fam ... done.Code:FID IID MISS_PHENO N_MISS N_GENO F_MISS Kaspias_FAM Kaspias Y 0 353388 0 Albanian.DG S_Albanian-1.DG Y 0 353388 0 Altaian.DG S_Altaian-1.DG Y 0 353388 0 Anatolian_Turkish.DG S_Turkish-1.DG Y 0 353388 0 Anatolian_Turkish.DG S_Turkish-2.DG Y 0 353388 0 Armenian.DG S_Armenian-1.DG Y 0 353388 0 Armenian.DG S_Armenian-2.DG Y 0 353388 0 Bashkir.SG Bashkirs1.SG Y 0 353388 0 Bashkir.SG Bashkirs3.SG Y 0 353388 0 Bulgarian.DG S_Bulgarian-1.DG Y 0 353388 0 Bulgarian.DG S_Bulgarian-2.DG Y 0 353388 0 Cretan.DG B_Crete-1.DG Y 0 353388 0 Cretan.DG B_Crete-2.DG Y 0 353388 0 Eskimo_Chaplin.DG S_Eskimo_Chaplin-1.DG Y 0 353388 0 Estonian.DG S_Estonian-1.DG Y 0 353388 0 Estonian.DG S_Estonian-2.DG Y 0 353388 0 Hungarian.DG S_Hungarian-1.DG Y 0 353388 0 Hungarian.DG S_Hungarian-2.DG Y 0 353388 0 Iranian.DG S_Iranian-1.DG Y 0 353388 0 Iranian.DG S_Iranian-2.DG Y 0 353388 0 Kyrgyz_Kyrgyzstan.DG S_Kyrgyz-1.DG Y 0 353388 0 Kyrgyz_Kyrgyzstan.DG S_Kyrgyz-2.DG Y 0 353388 0 Mongola.DG S_Mongola-1.DG Y 0 353388 0 Mongola.DG S_Mongola-2.DG Y 0 353388 0 Polish.DG S_Polish-1.DG Y 0 353388 0 Russian.DG S_Russian-1.DG Y 0 353388 0 Russian.DG S_Russian-2.DG Y 0 353388 0 Saami.DG S_Saami-1.DG Y 0 353388 0 Saami.DG S_Saami-2.DG Y 0 353388 0 Sardinian.DG B_Sardinian-3.DG Y 0 353388 0 Sardinian.DG S_Sardinian-1.DG Y 0 353388 0 Sardinian.DG S_Sardinian-2.DG Y 0 353388 0 S_Greek.DG S_Greek-1.DG Y 0 353388 0 S_Greek.DG S_Greek-2.DG Y 0 353388 0 S_Tuscan.DG S_Tuscan-1.DG Y 0 353388 0 S_Tuscan.DG S_Tuscan-2.DG Y 0 353388 0 Tajik.SG Tadjik.SG Y 0 353388 0 Tajik.SG Tajiks1.SG Y 0 353388 0 Tajik.SG Tajiks3.SG Y 0 353388 0 Tatar_Tomsk.SG TomskTatars1.SG Y 0 353388 0 Tatar_Tomsk.SG TomskTatars2.SG Y 0 353388 0 Tatar_Volga.SG VolgaTatars1.SG Y 0 353388 0 Tatar_Volga.SG VolgaTatars2.SG Y 0 353388 0 Turkmen.SG Turkmens1.SG Y 0 353388 0 Turkmen.SG Turkmens2.SG Y 0 353388 0 Uyghur.DG S_Uygur-1.DG Y 0 353388 0 Uyghur.DG S_Uygur-2.DG Y 0 353388 0 Uzbek.SG Uzbeks1.SG Y 0 353388 0 Uzbek.SG Uzbeks2.SG Y 0 353388 0 Uzbek.SG Uzbeks3.SG Y 0 353388 0
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No of SNPs is ok and no samples have missing SNPs. Are you sure you converted your FTDNA data properly? If yes, then i suspect it’s ascertainment bias because the company that genotyped you used a drastically different set of SNPs than Simons. Too bad you don’t have WGS. Nebula or Sequencing.com does WGS for only like $79 it’s totally worth it for you to do it on yourself
For now disregard max-maf 0.3 to minimize bias
Edit: I just remembered Plink does screw up allele order so max-maf may be affected. I normally import alleles into bim using my Hg19 reference genome using a script that i made
Last edited by Zoro; 03-11-2021 at 06:48 PM.
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