GWAS分析 一般线性模型GLM + 协变量中meta、se、T、p值的计算
001、plink
root@PC1:/home/test# ls gwas_test.map gwas_test.ped root@PC1:/home/test# plink --file gwas_test --pca 3 1> /dev/null root@PC1:/home/test# ls gwas_test.map gwas_test.ped plink.eigenval plink.eigenvec plink.log root@PC1:/home/test# head -n 3 plink.eigenvec fam1 id1 -0.0102664 0.0442708 -0.0658835 fam2 id2 0.0421124 -0.0313769 -0.0705913 fam3 id3 -0.0467758 -0.00993805 -0.000487215 root@PC1:/home/test# plink --file gwas_test --covar plink.eigenvec --linear hide-covar 1> /dev/null root@PC1:/home/test# ls gwas_test.map gwas_test.ped plink.assoc.linear plink.eigenval plink.eigenvec plink.log root@PC1:/home/test# head -n 5 plink.assoc.linear CHR SNP BP A1 TEST NMISS BETA STAT P 1 snp1 2802 G ADD 541 0.9887 0.1258 0.8999 1 snp2 2823 T ADD 541 6.096 0.6524 0.5144 1 snp3 4512 G ADD 541 9.957 1.091 0.2759 1 snp4 16529 T ADD 541 5.631 0.5394 0.5899 root@PC1:/home/test# head -n 5 plink.assoc.linear | awk '{if(NR == 1) {print "SE"} else {print $(NF -2 )/$(NF - 1)}}' SE 7.8593 9.34396 9.12649 10.4394
002、R
root@PC1:/home/test# ls gwas_test.map gwas_test.ped root@PC1:/home/test# plink --file gwas_test --recode A 1> /dev/null root@PC1:/home/test# ls gwas_test.map gwas_test.ped plink.log plink.raw root@PC1:/home/test# plink --file gwas_test --pca 3 header 1> /dev/null root@PC1:/home/test# ls gwas_test.map gwas_test.ped plink.eigenval plink.eigenvec plink.log plink.raw root@PC1:/home/test# awk '{print $2, $6}' plink.raw | paste -d " " - <(cut -d " " -f 3- plink.eigenvec ) | paste -d " " - <(cut -d " " -f 7- plink.raw ) > dat.txt root@PC1:/home/test# head -n 3 dat.txt | cut -d " " -f 1-10 | column -t IID PHENOTYPE PC1 PC2 PC3 snp1_G snp2_T snp3_G snp4_T snp5_G id1 580 -0.0102664 0.0442708 -0.0658835 0 1 1 0 1 id2 690 0.0421124 -0.0313769 -0.0705913 0 0 0 0 0
library(data.table) dat <- fread("dat.txt", data.table = F) dat[1:3,1:8] result <- data.frame() for (i in 6:12) { reg = lm(PHENOTYPE ~ 1 + PC1 + PC2 + PC3 + dat[,i], data=dat) result<- rbind(result, summary(reg)$coefficients[5,]) } names(result) <- c("beta", "se", "t", "p") result