library(methylKit) install.packages("data.table") source("http://www.bioconductor.org/biocLite.R") biocLite("GenomicRanges") library(data.table) library(GenomicRanges) file.list <- list('BiGo_lar_M1_methylkit6.txt','BiGo_lar_T1D3_methylkit6.txt','BiGo_lar_T1D5_methylkit6.txt','BiGo_lar_T3D5_methylkit6.txt',"BiGo_lar_T3D3_methylkit6.txt","BiGo_lar_M3_methylkit6") myobj<-read( file.list,pipeline=list(fraction=TRUE,chr.col=1,start.col=2,end.col=2, coverage.col=4,strand.col=3,freqC.col=5 ), sample.id=list("M1","T1D3",'T1D5','T3D5','T3D3','M3'),assembly="v9",treatment=c(1,0,0,0,0,0)) file.list <- list('BiGo_lar_M1_methylkit6.txt','BiGo_lar_T1D3_methylkit6.txt','BiGo_lar_T1D5_methylkit6.txt','BiGo_lar_T3D5_methylkit6.txt',"BiGo_lar_T3D3_methylkit6.txt","BiGo_lar_M3_methylkit6.txt") myobj<-read( file.list,pipeline=list(fraction=TRUE,chr.col=1,start.col=2,end.col=2, coverage.col=4,strand.col=3,freqC.col=5 ), sample.id=list("M1","T1D3",'T1D5','T3D5','T3D3','M3'),assembly="v9",treatment=c(1,0,0,0,0,0)) meth<-unite(myobj,destrand=FALSE) head(meth) nrow(meth) getCorrelation(methnew,plot=T) getCorrelation(meth,plot=T) pdf(file="graph_methylkit6.pdf") getCorrelation(meth,plot=T) dev.off() file.list <- list('BiGo_lar_M1_methylkit6.txt','BiGo_lar_T1D3_methylkit6.txt','BiGo_lar_T1D5_methylkit6.txt','BiGo_lar_T3D5_methylkit6.txt',"BiGo_lar_T3D3_methylkit6.txt","BiGo_lar_M3_methylkit6.txt") myobj<-read( file.list,pipeline=list(fraction=TRUE,chr.col=1,start.col=2,end.col=2, coverage.col=4,strand.col=3,freqC.col=6 ), sample.id=list("M1","T1D3",'T1D5','T3D5','T3D3','M3'),assembly="v9",treatment=c(1,0,0,0,0,0)) meth<-unite(myobj,destrand=FALSE) head(meth) nrow(meth) pdf(file="graph_methylkit6.pdf") getCorrelation(meth,plot=T) dev.off() getCorrelation(meth,plot=T)