[BioC] [Rocky] - LIMMA to identify deferentially expressed genes

[하오잠 로]

Bioconductor Team

Dear Sir,
I have a special request to you. I would like to fit a model for GSE11024 dataset consisting of 5 different case groups and normal group detail infromation is given below. I have normalized the raw files with the following comments in R-package using affy /simpleaffy. Could you please send me the code or hints to fit this normalized data to LIMMA in R-package. I would be glad and highly appreciate for your kindness.

source("http://www.bioconductor.org/biocLite.R")
biocLite("limma")
biocLite("affy")
library(affy)
setwd("/home/haojamrocky/DATA/GSE11024")
rawdata<-ReadAffy()
eset <- expresso(rawdata, normalize.method="quantiles",bgcorrect.method="rma",pmcorrect.method="pmonly",summary.method="liwong")
write.exprs(eset, file="mydata.txt")

http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE11024
GSM278765 - GSM278774 (10 samples)	-> CC_KIDNEY
GSM278775 - GSM278780 (6 samples) -> CHR_KIDNEY
GSM278781 - GSM278792 (12 samples) -> NOR_KIDNEY
GSM278793 - GSM278799 (7 samples) -> ON_KIDNEY
GSM278800 - GSM278816 (17 samples) -> Pappilary_KIDNEY
GSM278817 - GSM278843 (27 samples) -> WM_KIDNEY
I have attach the zip EXCEL file where the first row represents samples name and first column represents probes ID . The file size  is big so I reduce to 10,000 rows only but it has 54675 rows.

Warm regards,
Rocky Haojam
Seoul National University college of Medicine
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