[BioC] Time course experiment....

[Gordon K Smyth]

Dear Viritha,

To get all genes that pass the FDR<0.05 criterion, you can use

   topTable(fit2, coef=2, n=Inf, p=0.05)

To get all genes that have FDR<0.05 and have log2-fold-change greater than 
1,

   topTable(fit2, coef=2, n=Inf, p=0.05, lfc=1)

See ?topTable.  Note that 'n' is the upper limit on the number of genes to 
list, not necessarily the actual number to list.

Best wishes
Gordon


> Date: Tue, 8 Feb 2011 17:14:42 +0000
> From: viritha <viritha.k at gmail.com>
> To: <bioconductor at stat.math.ethz.ch>
> Subject: Re: [BioC] Time course experiment....
> Message-ID: <loom.20110208T174927-793 at post.gmane.org>
> Content-Type: text/plain; charset="us-ascii"
>
>
> Naomi Altman <naomi at ...> writes:
>>
>> I did not get the original posting, but doesn't Sohail just need
>> "TopTable" for this?
>>
>> --Naomi
>
> Hi Naomi,
> I had a similiar issue and used TopTable but I am getting only first 10 but how
> should I write the code to get selected probesets based on an adjusted p-value
> less than or equal to 0.05.
>
> code:
> design <- model.matrix(~factor(rep(1:2, each=3)))
> fit <- lmFit(eset, design)
> fit2 <- eBayes(fit)
> topTable(fit2,coef=2,adjust="BH")
>
> I have 3 control and 3 treated samples.The eset has the probenames and the
> expression matrix.
> So my question is how do I get the data of all the probesets which pass this
> criteria?
> Thanks,
> Viritha

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