Question: Help to confirm Design matrix and Between array Normalization.
0
gravatar for Veerendra GP
9.0 years ago by
Veerendra GP100
Veerendra GP100 wrote:
Dear friends, I have DNA differently methylated data of (done with differentially methylated hybridization technique) three cancerous experiments. The experimental design is as follows: Normal vs Tumor: wherein Normal is labeled with cy3 and Tumor is labeled with cy5. Normal vs Pre malignant: wherein Normal is labeled with cy3 and Pre malignant is labeled with cy5. Tumor vs Pre maligmant: wherein Tumor is labeled with cy3 and pre malignent is labeled with cy5. I wanted to fit linear model for this experimental design. I have gone through the Limma documentation and done analysis. But, as design matrix need to be more perfect, I would like to confirm the matrix design with your opinion. I also would like to know fitting between array normalization in this context will be meaningfull or not? So, I request you to help me in this context. Here is my sessional info : library(limma) targets<- readTargets("/home/veerendra/MicroarrayData/target.txt") RG <- read.maimages(targets$SlideNumber, source="agilent", path="/home/veerendra/MicroarrayData/DATA") status <- rep("gene", nrow(RG$genes)) status[grep("NC1_*",RG$genes[,"ProbeName"])] <- "cntrl" status[grep("NC2_*",RG$genes[,"ProbeName"])] <- "cntrl" status[grep("LACC*",RG$genes[,"ProbeName"])] <- "cntrl" status[grep("PC_*",RG$genes[,"ProbeName"])] <- "cntrl" status[grep("DarkCorner",RG$genes[,"ProbeName"])] <- "cntrl" status[grep("HsCGHBrightCorner",RG$genes[,"ProbeName"])] <- "cntrl" status[grep("NegativeControl",RG$genes[,"SystematicName"])] <- "cntrl" status[grep("SM_*",RG$genes[,"ProbeName"])] <- "cntrl" status[grep("DCP*",RG$genes[,"ProbeName"])] <- "cntrl" status[grep("unmapped",RG$genes[,"SystematicName"])] <- "cntrl" RGnc <- RG[status!="cntrl",] MA<-normalizeWithinArrays(RGnc,method="loess",bc.method="normexp") design <- modelMatrix(targets, ref="N") N P T P T [1,] 0 1 [2,] 1 0 [3,] 1 -1 fit <- lmFit(MA, design) contrast.matrix <- cbind("N-T"=c(1,0),"N-P"=c(0,1),"P-T"=c(1,-1)) N-T N-P P-T [1,] 1 0 1 [2,] 0 1 -1 rownames(contrast.matrix) <- colnames(design) fit2 <- contrasts.fit(fit, contrast.matrix) fit2 <- eBayes(fit2) tb<-topTable(fit2, adjust="BH", n=200000) write.table(tb,file="testtb.txt", sep="\t") Thanking you in anticipation. Regards, Veerendra. [[alternative HTML version deleted]]
limma • 469 views
ADD COMMENTlink written 9.0 years ago by Veerendra GP100
Please log in to add an answer.

Help
Access

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 16.09
Traffic: 141 users visited in the last hour