[BioC] detailed analysis process of Comparisons Both Between and Within Subjects of edgeR

[Gordon K Smyth]

Dear Huajing Teng,

See

https://www.stat.math.ethz.ch/pipermail/bioconductor/2012-November/049087.html

for a solution.  The problem is arising because you have different numbers 
of patients in the two groups (5 males but 4 female).  This causes one of 
the columns of your design matrix to be all zero.  You will need to remove 
the all zero column.

Best wishes
Gordon

> Date: Tue,  8 Jan 2013 16:39:22 -0800 (PST)
> From: "Huajing Teng [guest]" <guest at bioconductor.org>
> To: bioconductor at r-project.org, tenghj at mail.biols.ac.cn
> Subject: [BioC] detailed analysis process of \"Comparisons Both
> 	Between and	Within Subjects\" of edgeR
>
>
> Dear Dr.Smyth,

> I am very interested in "Comparisons Both Between and Within Subjects" 
> of edgeR. Because one of my study is according to this design. But i 
> found some detailed analysis have not been provided in the manual (After 
> estimating the dispersions (code not shown), we can fit a linear 
> model:), and i met some difficulty in using this pipline.  When i used y 
> <- estimateGLMCommonDisp(y, design, verbose=TRUE), I got an error: error 
> in solve.default(R, t(beta)) : Lapack routine dgesv: system is exactly 
> singular
>
> I wonder whether you can provide some detailed analysis process 
> (especially in data reading, dispersion evaluation ). Thanks for your 
> kind assistance.
>
> -- output of sessionInfo():
>
> source("http://bioconductor.org/biocLite.R")
> biocLite("edgeR")    biocLite("limma")
> library(edgeR)
>> targets <- read.delim("F:/teng/thyroidcarcinoma/gene_exp.diff/edgeR/2nd/geneexpression/allnosui/design.txt", check.names=FALSE, stringsAsFactors=FALSE)
>> targets
>> Patient <- gl(5,2,length=18)
>> Sex <- factor(targets$Sex, levels=c("M","F"))
>> Treatment <- factor(targets$Treatment, levels=c("N","T"))
>> data.frame(Sex,Patient,Treatment)
>> y <- read.delim("F:/teng/thyroidcarcinoma/gene_exp.diff/edgeR/2nd/geneexpression/allnosui/genecount.txt", row.names=1, header=T, stringsAsFactors=FALSE)
>> design <- model.matrix(~Sex+Sex:Patient+Sex:Treatment)
>> rownames(design) <- colnames(y)
>> y <- estimateGLMCommonDisp(y, design, verbose=TRUE)
> #error:
> #error in solve.default(R, t(beta)) : Lapack routine dgesv: system is exactly singular
>

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