[R] EdgeR annotation

[Martin Morgan]

On 08/24/2013 04:50 AM, Robin Mjelle wrote:
> after updating R and edgeR I lost the annotations in the final
> Diff.Expressed matrix (toptags) when running the edgeR pipeline. How do I
> get the row.names from the data matrix into the topTag-matrix?
>
> data <- read.table("KO_and_WT_Summary_miRNA_Expression.csv", row.names=1,
> sep="", header=T)

edgeR is a Bioconductor package, so please ask on their mailing list (no 
subscription required!)

   http://bioconductor.org/help/mailing-list/

Remember to provide a reproducible example (people on the list will not be able 
to created your 'data' object; perhaps working with the simulated data on the 
help page ?glmFit is a good place to start?) and to include the output of 
sessionInfo() so that there is no ambiguity about the software version you are 
using.

Martin

>
>
> keep <- rowSums(cpm(data)>2) >=2
> data <- data[keep, ]
> table(keep)
> y <- DGEList(counts=data[,1:18], genes=data[,0:1])
> y <- calcNormFactors(y)
> y$samples
> plotMDS(y,main="")
> Time=c("0.25h","0.5h","1h","2h","3h","6h","12h","24h","48h","0.25h","0.5h","1h","2h","3h","6h","12h","24h","48h")
> Condition=c("KO","KO","KO","KO","KO","KO","KO","KO","KO","WT","WT","WT","WT","WT","WT","WT","WT","WT")
> design <- model.matrix(~0+Time+Condition)
> rownames(design) <- colnames(y)
> y <- estimateGLMCommonDisp(y, design, verbose=TRUE,
> method="deviance",robust=TRUE, subset=NULL)
> y <- estimateGLMTrendedDisp(y, design)
> y <- estimateGLMTagwiseDisp(y, design)
> fit <- glmFit(y, design)
> lrt <- glmLRT(fit)
> topTags(lrt)
>
> Coefficient:  ConditionWT
>       genes      logFC    logCPM        LR PValue FDR
> 189   5128 -11.028422  7.905804  4456.297      0   0
> 188  12271 -10.582267  9.061326  5232.075      0   0
> 167 121120  -9.831894 12.475576  5957.104      0   0
> 34  255235  -9.771266 13.592968  7355.592      0   0
> 168 311906  -9.597952 13.907951 10710.111      0   0
> 166 631262  -9.592550 14.932018 11719.222      0   0
> 79      79   9.517226 11.466696  7964.269      0   0
> 169   2512  -8.946429  6.758584  2502.548      0   0
> 448   3711  -7.650068  7.764682  2914.784      0   0
> 32  260769  -7.412197 13.633352  4906.198      0   0
>
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>
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