## ---- include = FALSE--------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----setup-------------------------------------------------------------------- library(ROSeq) library(edgeR) library(limma) ## ----data, message=FALSE,warning = FALSE,include=TRUE, cache=FALSE------------ samples<-list() samples$count<-ROSeq::L_Tung_single$NA19098_NA19101_count samples$group<-ROSeq::L_Tung_single$NA19098_NA19101_group samples$count[1:5,1:5] ## ----preprocesing, message=FALSE,warning = FALSE,include=TRUE, cache=FALSE---- gene_names<-rownames(samples$count) samples$count<-apply(samples$count,2,function(x) as.numeric(x)) rownames(samples$count)<-gene_names samples$count<-samples$count[,colSums(samples$count> 0) > 2000] gkeep<-apply(samples$count,1,function(x) sum(x>2)>=3) samples$count<-samples$count[gkeep,] samples$count<-limma::voom(ROSeq::TMMnormalization(samples$count)) ## ----main, message=FALSE,warning = FALSE, include=TRUE, cache=FALSE----------- output<-ROSeq(countData=samples$count$E, condition = samples$group, numCores=1) ## ----output, message=FALSE,warning = FALSE,include=TRUE, cache=FALSE---------- output[1:5,]