I am new to microarray data and I am having a really hard time finding a good work flow so far. My experiment is with human transcriptome data. I have 4 time points and I am trying to find DEG between them. This is just a test run with two times points. I have no idea what to do and so far my script hasn't worked so well. This is what I have so far. Thanks in advance. My volcano plot also looks really weird.
source("http://bioconductor.org/biocLite.R") biocLite("oligo") biocLite("limma") biocLite("pd.hugene.2.1.st") library(genefilter) library(limma) library(oligo) library(pd.hugene.2.0.st) #directory for the data mydir <- "C:\\Users\\hakim\\Desktop\\Bioinformatics_Thesis_Concordia_Microarry_Data\\Control" #setting seed for reproducibility set.seed(1) #listing the files from directory using special CEL file read function celList <- list.celfiles(mydir, full.names=TRUE) #reading data from cellist and setting annotation package to approiate one for this microarray rawData <- read.celfiles(celList, pkgname='pd.hugene.2.0.st') #normalizing the data using RMA algorithm normData <- rma(rawData) #checking boxplot of raw data par(mar=c(10,4.5,2,1)) boxplot(rawData,las=3) #checking boxplot of normalized data boxplot(normData,las=3) #the annotation package biocLite("hugene20sttranscriptcluster.db") library(hugene20sttranscriptcluster.db) #retreaving feature data featureData(normData) <- getNetAffx(normData, "transcript") design = cbind(control = 1, controlvstreatment = c((rep.int(0,13)),rep.int(1,13))) fit<- lmFit(normData, design) normfit <-eBayes(fit) omg <- topTable(normfit, coef="controlvstreatment", adjust="BH") write.table(omg,file="finally.txt",sep= "/" ) results <- decideTests(fit) vennDiagram(results) volcanoplot(normfit)