Thanks Simon,

Well, so i omitted the two commands you mentioned, my commands now:
library( "DESeq" )
exampleFile = system.file( "extra/X_Y_Reads.txt", package="DESeq" )
countsTable <- read.delim( exampleFile, header=TRUE, stringsAsFactors=TRUE )
rownames( countsTable ) <- countsTable$gene
countsTable <- countsTable[ , -1 ]
conds <- c( "X","X","Y","Y")
cds <- newCountDataSet( countsTable, conds )
cds <- estimateSizeFactors( cds )
sizeFactors( cds )
cds <- estimateDispersions( cds )
res <- nbinomTest( cds, "X", "Y" )
plot(res$baseMean,res$log2FoldChange,log="x", pch=20, cex=.1,col = ifelse(
res$padj < .001, "red", "black" ) )
resSig <- res[ res$padj < .001, ]
head( resSig[ order(resSig$pval), ] )
write.table(res,"C:\\Users\\OMD\\Desktop\\XY_DEG.txt")

Regarding the FDR, honestly I'm not really sure what is the best cut off
value to use, I picked 0.001 based on what I saw in one of the
examples published in the DESeq paper! Any recommendations!

I have one more question, in the output file i can see only integer ids
(1,2,3,4 ... etc) instead of the (gene0001, gene0023 ... etc ), I am not
sure if these integers match the gene numbers as in my input

Regards,

On Wed, Mar 21, 2012 at 10:18 AM, Simon Anders <anders@embl.de> wrote:

> Hi
>
>
> On 03/21/2012 12:26 AM, Omar Darwish wrote:
>
>>  I used the following commands to find the differentially expressed genes.
>> I have two questions,
>>
>>    1. Are the following commands correct ? or am i missing something?
>>
>
> Yes, except for two oddities:
>
>
> > libsizes<- clibsizes<- c(X.1=18143070, X.2=13544150, Y.1=17853990,
> > Y.2=15038501)
> > sizeFactors(cds)<- libsizes[-1]
> > cds<- estimateSizeFactors( cds )
>
> Why do you set the size factors manually, and the use
> 'estimateSizefactors' to overwrite this information? The first two commands
> are gratuitous (and don't even work becaus of the "[-1]"). Omit them.
>
>
> > resSig<- res[ res$padj<  .001, ]
>
> Do your really want an FDR of only 0.1%? This is extremely stringent. Do
> you have any reason for this unusual choice?
>
>     2. How can i determine which genes are differentially expressed?
>>    induced? suppressed? unchanged?
>>
>
> Those with and adjusted p value (column "padj") below your chosen FDR
> threshold are significant, and the column "log2FoldChange" tells you the
> log2 fold change and hence whether they are up- or downregulated.
>
>  Simon
>
> ______________________________**_________________
> Bioconductor mailing list
> Bioconductor@r-project.org
> https://stat.ethz.ch/mailman/**listinfo/bioconductor<https://stat.ethz.ch/mailman/listinfo/bioconductor>
> Search the archives: http://news.gmane.org/gmane.**
> science.biology.informatics.**conductor<http://news.gmane.org/gmane.science.biology.informatics.conductor>
>



-- 
Regards,
Omar

	[[alternative HTML version deleted]]

