guide-to-R-scripts.md

General guide to R scripts for analyzing your transcriptome data

Gene expression analysis

Compare gene expression using DESeq2

library(DESeq2) 
counts<-read.delim(‘counts.txt,row.names=1) 
cds<-DESeqDataSetFromMatrix(counts.txt,meta,~cluster) 
cds<-DESeq(cds) 
res<-results(cds) 
sig<-res[which(res$padj<0.05),] 
write.table(sig,file=‘DEcontigs.txt’,quote=F,sep=‘\t') 

WGCNA

• in program R
• website
• script TBD

Identify expression SNPs

• see Noah Rose's R package: https://github.com/noahrose/vcf2eqtl

SNP ANALYSIS

A simple way to format your 012 SNP matrix

snps<-read.delim('file.012', header=F)
pos<-read.delim('file.012.pos',header=F)
indv<-read.delim<-('file.012.indv',header=F)

colnames(snps)<-paste(pos[,1],pos[,2],sep='-')
rownames(snps)<-indv[,1]
snps<-as.matrix(snps)

#PCA of SNPs
pc.out<-prcomp(snps)
summary(pc.out)
plot(pc.out$x[,1],pc.out$x[,2])	#PC1 v PC2

Add meta data to your SNP matrix

• make a meta data file with info about individuals (location, date, etc.)
• make sure your meta file is ordered the same as your vcfs! (i.e. ls your samples in the terminal to see their order)
• script TBD

Allow for missing SNP data with SNPrelate

Look at ancestry with admixture

• you will need to make a plink file from your vcf file instead of using your 012 matrix