[BioC] R: Time course experiment....

Manca Marco (PATH) m.manca at maastrichtuniversity.nl
Tue Feb 8 18:35:56 CET 2011


Hi Viritha,

just do

code:
 design <- model.matrix(~factor(rep(1:2, each=3)))
 fit <- lmFit(eset, design)
 fit2 <- eBayes(fit)
top.list<-topTable(fit2,coef=2,adjust="BH")
your.results <- top.list[top.list$adj.P.Val < 0.05, ]

...it should do the trick...

All the best, Marco


--
Marco Manca, MD
University of Maastricht
Faculty of Health, Medicine and Life Sciences (FHML)
Cardiovascular Research Institute (CARIM)

Mailing address: PO Box 616, 6200 MD Maastricht (The Netherlands)
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________________________________________
Da: bioconductor-bounces at r-project.org [bioconductor-bounces at r-project.org] per conto di viritha [viritha.k at gmail.com]
Inviato: martedì 8 febbraio 2011 18.14
A: bioconductor at stat.math.ethz.ch
Oggetto: Re: [BioC] Time course experiment....

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

>
> At 08:51 AM 1/2/2006, Gordon Smyth wrote:
> >Dear Sohail,
> >
> >Well, there are lots of ways to generate such a table. Perhaps the simplest
is
> >
> >    fitsel <- fit2[sel.dif, ]
> >    as.data.frame( fitsel )
> >
> >Best wishes
> >Gordon
> >
> > >Date: Tue, 20 Dec 2005 14:03:43 -0500
> > >From: "Khan, Sohail" <khan at ...>
> > >Subject: [BioC] Time course experiment....
> > >To: <bioconductor at ...>
> > >
> > >Dear List,
> > >
> > >I have performed a time course analysis using limma, as described in
> > >"Bioinformatics and Computational Biology Solutions ........".
> > >How can I get a list of differentially expressed genes?  I've tried
> > >the code below:
> > >sel.dif<-p.adjust(fit2$F.p.vlaue,method="fdr") <0.05
> > >This produces a logical vector, right?.  I would like a table of
> > >differentially expressed genes with p vales etc.  Sorry, if I missed
> > >this in the limma user's guide.  Thanks for any suggestions.
> > >
> > >
> > >Sohail Khan
> > >Scientific Programmer
> > >COLD SPRING HARBOR LABORATORY
> > >Genome Research Center
> > >500 Sunnyside Boulevard
> > >Woodbury, NY 11797
> > >(516)422-4076
> >
> >_______________________________________________
> >Bioconductor mailing list
> >Bioconductor at ...
> >https://stat.ethz.ch/mailman/listinfo/bioconductor
>
> 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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