Hi everyone,
I have genotypes with the codes of 1 and 2. For my aim, I must convert them to 0, 1, and 2. I found that plink can do it. So, I run them by plink with the use of the below codes.
shell("plink --file r --maf 0.05 --geno 0.01 --mind 0.1 --hwe 1e-6 --nonfounders --horse --recode --out rk")
3011 3011 2788 2327 1 1.4625 2 2 1 1 1 2 2 2 1 2 1 1 2 2 2 1 1 2 1 2 1 1 2
shell("plink --file r --maf 0.05 --geno 0.01 --mind 0.1 --hwe 1e-6 --nonfounders --horse --recodeA --out rA")
3011 3011 2788 2327 1 1.4625 0 0 1 0 1 0 0 1 1 1 0 1 1 1 1 1 1 1 1 1
shell("plink --file r --maf 0.05 --geno 0.01 --mind 0.1 --hwe 1e-6 --nonfounders --horse --recodeAD --out rAD")
3011 3011 2788 2327 1 1.4625 0 0 0 0 1 1 0 0 1 1 0 0 0 0 1 1 1 1 1 1 0 0 1
By the use of --recode, I only see 1 and 2 codes. For --recodeA and --recodeAD options, they generated codes 0, 1, 2. But when I compared the results of them, they are different in genomic regions.
How can I have accurately converted genotypes (0,1,2) from my data? Which option in plink is suitable for my work?
Thanks
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Using just --recodeA is the usual way to do this, as per: convert from plink format into 012 format
For "--recodeA" and "--recodeAD" options, they generated codes 0, 1, 2. But when I compared the results of them, they are different in genomic regions.
You should not directly compare the results of these - they produce different results. Please see:
Or, please explain what you mean by "they are different in genomic regions"
Kevin
why important snps remove in --geno 0.2 filter steps ? i have gwas study in plink but remove important snps in alzheimer disease ( rs429358) --geno step. pls explain Kevin Blighe
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