Plink Data QC
#PLINK
plink --file GWAS
plink --file GWAS --mind 0.10 --recode --out GWAS_clean_mind
plink --file GWAS_clean_mind --maf 0.05 --recode --out MAF_greater_5
plink --file GWAS_clean_mind --exclude MAF_greater_5.map --recode --out MAF_less_5
plink --file MAF_greater_5 --geno 0.05 --recode --out MAF_greater_5_clean
plink --file MAF_less_5 --geno 0.01 --recode --out MAF_less_5_clean
plink --file MAF_greater_5_clean --merge MAF_less_5_clean.ped MAF_less_5_clean.map --recode --out GWAS_MAF_clean
plink --file GWAS_MAF_clean --mind 0.03 --recode --out GWAS_clean2
plink --file GWAS_clean2 --check-sex --out GWAS_sex_checking
#### in R - open R by simply typing R
setwd("to_your_working_directory/")
sexcheck = read.table("GWAS_sex_checking.sexcheck", header=T)
names(sexcheck)
sex_problem = sexcheck[which(sexcheck$STATUS=="PROBLEM"),]
sex_problem
q()
##################################
plink --file GWAS_clean2 --genome --out duplicates
#### in R
setwd("to_your_working_directory/")
dups = read.table("duplicates.genome", header = T)
problem_pairs = dups[which(dups$PI_HAT > 0.4),]
problem_pairs
problem_pairs = dups[which(dups$PI_HAT > 0.05),]
myvars = c("FID1", "IID1", "FID2", "IID2", "PI_HAT")
problem_pairs[myvars]
q()
######
plink --file GWAS_clean2 --remove IBS_excluded.txt --recode --out GWAS_clean3
plink --file GWAS_clean3 --het
###### in R
Dataset <- read.table("plink.het", header=TRUE, sep="", na.strings="NA", dec=".", strip.white=TRUE)
mean(Dataset$F)
sd(Dataset$F)
jpeg("hist.jpeg", height=1000, width=1000)
hist(scale(Dataset$F), xlim=c(-4,4))
dev.off()
q()
######
plink --file GWAS_clean3 --pheno pheno.txt --pheno-name Aff --hardy
##### in R
hardy = read.table("plink.hwe", header = T)
names(hardy)
hwe_prob = hardy[which(hardy$P < 0.0000009),]
hwe_prob
q()
##########
plink --file GWAS_clean3 --exclude HWE_out.txt --recode --out GWAS_clean4
