Genome-wide Association-MDS and PCA Exercise

From Center for Statistical Genetics

Revision as of 12:22, 24 January 2019 by Serveradmin (Talk | contribs) (Created page with "__NOTITLE__ ==Genome-wide Association-MDS and PCA Exercise== plink --file GWAS_clean4 --genome --cluster --mds-plot 10 R mydata = read.table("mds_components.txt", header=...")

(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to: navigation, search

Genome-wide Association-MDS and PCA Exercise

plink --file GWAS_clean4 --genome --cluster --mds-plot 10
R
mydata = read.table("mds_components.txt", header=T)
mydata$pch[mydata$Group==1 ] <-15 
mydata$pch[mydata$Group==2 ] <-16 
mydata$pch[mydata$Group==3 ] <-2
jpeg("mds.jpeg", height=500, width=500) 
plot(mydata$C1, mydata$C2 ,pch=mydata$pch) 
dev.off()
q()
plink --file GWAS_clean4 --pheno pheno.txt --pheno-name Aff --logistic --adjust --out unadj
plink --file GWAS_clean4 --genome --cluster --pca 10 header
plink --file GWAS_clean4 --pheno pheno.txt --pheno-name Aff --covar plink.eigenvec --covar-name PC1 --logistic --adjust --out PC1
plink --file GWAS_clean4 --pheno pheno.txt --pheno-name Aff --covar plink.eigenvec --covar-name PC1-PC2 --logistic --adjust --out PC1-PC2
R
source("broadqq.R")
gws_unadj = aff_unadj[which(aff_unadj$P < 0.0000001),] 
gws_unadj
gws_adjusted = aff_C1C2[which(aff_C1C2$P < 0.0000001),] 
gws_adjusted
q()