## ----样式，echo = false，结果='asis'-------------------------------------------------------------------------BiocStyle :: markdown（）suppresspackagestArtupMessages（{library（edger）library（goseq）library（org.hs.eg.db）library（go.db）}）## ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------库（EDGER）路径<-system.file（package =“ goseq”，“ extdata”，“ li_sum.txt”）table.summary < - read.table（路径，sep ='\ t'，header = true，stringsasfactors = false）<-table.summary [， - 1] Rownames（counts）<-table.summary [，1] grp < - factor（rep（c（“控制”，“已处理”），时代= C（4,3）））总结<-dgelist（counts，lib.size = colsums（计数），group = grp）## ------------------------------------------------------------------------------------------------------------------------------------ disp <- estimateCommonDisp(summarized) tested <- exactTest(disp) topTags(tested）## -----前列腺 - edger-padj ---------------------------------------------------------------------------------------------------------------------------------------------- padj <-with（测试$表，{keep <-logfc！= 0 value <-p.Adjust（pvalue [keep]，method =“ bh”）s​​etNames（value，value，ROWNAMES（测试）[keep]）}）基因在--------------------------------- nullp（基因，“ hg19”，“ ensgene”）头（PWF）## ------------------------------------------------------------------------- - - - - - - - - - - - - - - - - - - - - - - - - 去。------------------------------ GO.nobias <- goseq(pwf,"hg19","ensGene",method="Hypergeometric") ## ----prostate-goseq-compare, fig.width=5, fig.height=5------------------- idx <- match(GO.nobias$category, GO.wall$category) plot(log10(GO.nobias[, "over_represented_pvalue"]) ~ log10(GO.wall[idx, "over_represented_pvalue"]), xlab="Wallenius", ylab="Hypergeometric", xlim=c(-5, 0), ylim=c(-5, 0)) abline(0, 1, col="red", lwd=2)