[BioC] limma for spectral counts
naomi at stat.psu.edu
Thu Oct 21 15:54:35 CEST 2010
I do not know anything about spectral count data. However, limma is
meant for continuously distributed data. If the counts are large, then
limma can be used on log(count).
However, if the counts are small, then the methods in edgeR and DEseq
are more suitable as they use a typical assumption for count data -
Negative Binomial distribution.
At 11:23 AM 10/20/2010, Laurent Gatto wrote:
>The spectral counts should indeed be normalised but, as far as I know,
>there is no direct way to do this in Bioconductor. It should however
>not be too difficult to implement if you have the sequence to
>normalise the count to the length of the protein. You might also want
>to have a look at the emPAI  to assess protein abundance from
>spectral counts. The emPAI values will probably need some log
>transformation before using limma.
>If you want to use normalised spectral counts, another option would be
>to investigate the use of RNA-seq methods that are meant to work with
>counts. edgeR mentions spectral counts in the publication , but I'm
>sure other Bioconductor packages can equally apply (see for instance
>the RNAseq Bioc view).
>Hope this helps.
>Cambridge Centre For Proteomics
>On 20 October 2010 14:20, Yolande Tra <yolande.tra at gmail.com> wrote:
> > Hello list members,
> > I was wondering if limma method can be used for spectral counts of
> > proteins from mass spectrometry. If yes, is there a function in
> > Bioconductor that normalizes these counts.before running limma.
> > Thank you for your help,
> > Yolande
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