Hello Forum,
I am doing gene expression analysis using limma package. After reducing the number of tests through filtering of genes, I am getting higher adjusted p values. Just curious, what is causing this, probably no significant differences in signals.
I appreciate any insight.
Thanks,
R code:
setwd("C:/Users/chaudhak/Desktop/Michelle_celfiels/Heart/CDCB vs HFDM") getwd() library(affy) Mydata<-ReadAffy() ### reading in the celfiles Mydata phenoData(eset) ### phenotypic data pData(eset)$case=c("CD.ND","CD.ND","CD.ND","CD.ND","CD.ND","CD.ND","CD.ND","CD.ND", "HF.DM","HF.DM","HF.DM","HF.DM","HF.DM") ### phenotype dataframe pData(eset) library(limma) Group<- as.factor(pData(eset)[,2]) design<-model.matrix(~0+Group) colnames(design)<-c("CD.DM","HF.DM") contrast.matrix<-makeContrasts( CD.DM VS HF.DM=(CD.DM-HF.DM), levels=design) fit <- lmFit(eset, design) fit2 <- contrasts.fit(fit, contrast.matrix) fit2 <- eBayes(fit2) colnames(fit2) topTable(fit2,coef=1,adjust="fdr")
Hi Jim,
I am filtering the genes at eset object.
source("http://bioconductor.org/biocLite.R")
biocLite("ragene10sttranscriptcluster.db")
biocLite("ALL")
library(ragene10sttranscriptcluster.db)
library(genefilter)
annotation(eset) <- "ragene10sttranscriptcluster.db"
celfiles.filt<- nsFilter(eset,require.entrez=TRUE, var.cutoff =0.5)$eset
celfiles.filt$filter.log
dim(celfiles.filt)
mat1<-exprs(celfiles.filt)
dim(mat1)
head(mat1)
sessionInfo()
I was wondering how to select genes after ebayes() step?
Thanks for your help.