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

Ryan C. Thompson rct at thompsonclan.org
Wed Jan 9 01:54:22 CET 2013


Could you share what your "targets

On Tue 08 Jan 2013 04:39:22 PM PST, Huajing Teng [guest] wrote:
>
> 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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>
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