Dear Neeraj Rana, You targets file is ok, although your samples are really normal and tumour rather than wt and mutant. You can use design <- model.matrix(~factor(targets$Cy5)) colnames(design) <- c("NodNeg","PosvsNeg") ... topTable(fit, coef="PosvsNeg") Best wishes Gordon > Date: Fri, 25 Jun 2010 13:55:46 +0530 > From: neeraj <kushrn at="" gmail.com=""> > To: Bioconductor at stat.math.ethz.ch > Subject: [BioC] limma matrix design for biological replicates. > > hi, > > i am doing analysis for 10 breast cancer arrays (two color Agilent4x44 > arrays) with limma,where Cy3 is normal and Cy5 is tumor.And all are > biological replicates ,means all 10 arrays have been prepared from 10 > different patients. > there are two categories as nod negative and nod positive.Five arrays from > nod negative(5 patients) and five are from nod positive(another 5 > patients).I want to see the differentially regulated genes between two > categories(NOD NEGATIVE vs NOD POSITIVE). > i designed the target file as given below..I want to make it sure whether it > is correct or not. > > SampleNumber FileName Cy3 Cy5 > 1 1135_NN.txt > wt1 mu1 > 2 2157_NN.txt wt1 > mu1 > 3 3159_NN.txt > wt1 mu1 > 4 4171_NN.txt > wt1 mu1 > 5 5179_NN.txt wt1 > mu1 > 6 628_NP.txt > wt2 mu2 > 7 758_NP.txt > wt2 mu2 > 8 880_NP.txt > wt2 mu2 > 9 993_NP.txt > wt2 mu2 > 10 1096_NP.txt > wt2 mu2 > > 1 to 5 are nod negative and ,6 to 10 are nod positive. > > thanx. > NEERAJ RANA > JRF > IISC BANGLORE(INDIA) ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}