[BioC] extracting significant genes using limma
Naomi Altman
naomi at stat.psu.edu
Mon Mar 13 16:41:08 CET 2006
Since you used "adjust=fdr", the p-value column of the TopTable are
the "adjusted p-values" after fdr (which I think of as q-values).
You can either pick some q-value you want to use to select the
significantly differentially expressing genes, or you can pick some
number of genes, and report the q-value of the least significant of these.
--Naomi
At 10:17 AM 3/13/2006, Assa Yeroslaviz wrote:
>Hi,
>
>I know this theme is an old one, but I look all over the archives and didn't
>find any help regarding this subject.
>Using Affymetrix chips I compared two groups (Control vs compound) with the
>limma procedure.
>I made an affybatch Object using ReadAffy(), normalised the data with the
>RMA algorithm and fitted a linear model with lmFit.
>
> >affy <- ReadAffy(filenames=vec)
> >eset <- rma(affy)
> >design <- cbind(Control=1,AE0627vsCT=c(rep(0,6),rep(1,4)))
>
>my design matrix looks like that (I have 6 control and 4 treated arrays):
> > design
> Control AE143vsCT
> [1,] 1 0
> [2,] 1 0
> [3,] 1 0
> [4,] 1 0
> [5,] 1 0
> [6,] 1 0
> [7,] 1 1
> [8,] 1 1
> [9,] 1 1
>[10,] 1 1
>
>so I don't need any contrast matrix.
>The list is 22,810 genes long. But not all of them can be significant. I
>hope!!!
>
>I sorted the genes with:
> >sig_table <- topTable(fit_e, coef=2, number=6000, adjust="fdr", sort.by=
>"P")
>
>I've chosen 6000 as an arbitrary value, but I still don't know how many
>genes are siginificant.
>
>My question(s) is(are):
>
>1. How do I find out how many genes are significantly differentially
>expressed using a define p-value or FDR?
> Can I use here the decideTests() function although I don't have any
>contrasts?
>
>2. In SAM one can look for the false discovery rates using the different
>delta-values.
> Is it possible to set a fixed FDR-Value in Limma?
> Where Do I find the FDR rates of my significant genes?
>
>3. Is there a possibility (like in SAM) to show the results in a graphic (
>scatter plot etc.)?
>
>Every comment and suggestion would be appreciated!
>
>THX
>
>Assa
>
>--
>Assa Yeroslaviz
>Loetzener Str. 15
>51373 Leverkusen
>
> [[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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