<![CDATA[BOL: RPKM normalization- R script]]> https://bioinformaticsonline.com/snippets/view/28042/rpkm-normalization-r-script? https://bioinformaticsonline.com/snippets/view/28042/rpkm-normalization-r-script Fri, 24 Jun 2016 17:45:55 -0500 https://bioinformaticsonline.com/snippets/view/28042/rpkm-normalization-r-script <![CDATA[RPKM normalization- R script]]> P<-read.table("input_table.txt",sep="\t",header=T) len <- ncol(p) rownames(p) <- p[,1] for(i in 2:ncol(p)-1) { d <-p[,i] l <- p[,len] #accessing the length column cS <- sum(as.numeric(p[,i])) #Total mapped reads per sample rpkm[[i]] <- (10^9)*(as.numeric(p[,i]))/(as.numeric(l)*cS) rpkm[[1]] <- p[[1]] } write.table(rpkm,"output_table_rpkm.txt",sep="\t",quote=F,row.names=F)​]]> EagleEye https://bioinformaticsonline.com/snippets/view/28042/rpkm-normalization-r-script#item-annotation-2501 Fri, 24 Jun 2016 17:58:14 -0500 https://bioinformaticsonline.com/snippets/view/28042/rpkm-normalization-r-script#item-annotation-2501 <![CDATA[Comment by EagleEye]]> Using Perl script,

 

http://bioinformaticsonline.com/snippets/view/28043/rpkm-normalization-perl

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