[BioC] Evaluating differentiall expressed genes

[Kasper Daniel Hansen]

On Dec 7, 2005, at 3:17 PM, Tim Smith wrote:

> Thanks for the replies Sean and Naomi. I feel I'm on the right track.
>
>   I did the following:
>
>
>     sam.out <- sam(zz, ncl, method = "d.stat", delta = NULL,  
> n.delta = 10, p0 = NA,
>   lambda = seq(0, 0.95, 0.05), ncs.value = "max", ncs.weights = NULL,
>   gene.names = dimnames(zz)[[1]])
>
>
>   sam.sum <-summary(sam.out,2,ll=FALSE)
>
>
>   Now, I wanted to get to the d-value matrix. The documentation  
> says that I can get this by the line:
>
>          # The matrix containing the d-values, q-values etc. of the
>        # differentially expressed genes can be obtained by
>
>
>   sam.outATmat.sig     # sam.out at mat.sig
>
>   but when I do this, I get :
>
>   Error: no slot of name "mat.sig" for this object of class "SAM"
>
>   How can I access the matrix to get at the underlying d-values  
> etc..??
>
>   many thanks.

Without going into too much detail, in R you have S3 objects and S4  
objects. You use $ for S3 objects and @ for S4 objects. Valid names  
may be found by names(object) for S3 objects and slotNames(object)  
for S4 objects.

Kasper



> Sean Davis <sdavis2 at mail.nih.gov> wrote:
>
>
>
>
> On 12/7/05 12:49 PM, "Tim Smith" wrote:
>
>> Hi all,
>>
>> A newbie to Bioconductor, so please forgive the naive question..
>>
>> I had two sets of data (normalized affy data). The first set contains
>> cancerous expression data for 40 patients, and the second set  
>> contains
>> expression data for 30 'normal' (i.e non cancerous) patients.
>>
>> I wanted to find out the genes that are 'differentially expressed'  
>> in the
>> two sets. Which package, and which functions can I use? Any  
>> reasonably popular
>> method/package would work for me.
>
> Welcome to bioconductor.
>
> See here for a full list. Best to do a little reading, as each  
> method has
> potentially different assumptions, etc.
>
> http://www.bioconductor.org/packages/bioc/1.7/src/contrib/html/
>
> That said, look at siggenes which contains the SAM method; the  
> multtest
> package for traditional t-tests; and the limma package.
>
> And just to be sure, when you say you have two sets of normalized  
> data, you
> mean that they were normalized together or separately?
>
> Sean
>
>
>
>
>
> 			
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