View source for Genome-wide Association-MDS and PCA Exercise

__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=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()