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.metho d="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 -------------- next part --------------

2012/1/17 ??? ? <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.met hod="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