[BioC] Evaluating differentiall expressed genes

Naomi Altman naomi at stat.psu.edu
Thu Dec 8 04:25:42 CET 2005


I have not used this particular Bioconductor package.  But I have 
learned in general how to deal with the various types of objects that 
the Bioconductor developers have created for us.

class(myobject)

tells you the class of "myobject"

?myclass

should give the documentation of what the class "myclass" consists of

method(myobject)

tells you what methods (and slots) work with "myobject"

names(myobject)

tells you what the components of "myobject" are.

Using these functions and the documentation, (vignettes and html 
help) I can usually figure out what I need.  If not ... there is 
always the mailing list.

--Naomi

At 06:17 PM 12/7/2005, 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.
>
>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
>
>
>
>
>
>
>---------------------------------
>
>
>         [[alternative HTML version deleted]]
>
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Naomi S. Altman                                814-865-3791 (voice)
Associate Professor
Dept. of Statistics                              814-863-7114 (fax)
Penn State University                         814-865-1348 (Statistics)
University Park, PA 16802-2111



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