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

[Sean Davis]

2012/1/17 하오잠 로 <haojam at snu.ac.kr>:
> 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.
>

Have a look at the limma user guide.  You might find the section on
"several groups" useful.

Sean