Kyle,

I agree with your reply to question 2 by calculating each "case" sample or
interested sample's ratio versus a a  median intensity from reference
samples. However, my original question also mentioned what if the
experimental design includes for example, different times, different
concentrations (including zero concentration). Therefore, that which samples
are considered as reference ones itself is a question. Usually such
experiment is done on Agilent platform therefore ratio is already there;
however, the question becomes challenging if affy platform is used. Then how
do you calculate fold change for that and how do you "connect" the PGSEA's
result to limma package, for example.

thanks for further help!

Weiwei

On Fri, Sep 5, 2008 at 6:17 PM, Furge, Kyle <Kyle.Furge@vai.org> wrote:

> 1. Yes, the GSEA and PGSEA methods use different calculations to assess
> gene
> set enrichment.  I am not aware of another implementation of GSEA other
> than
> the one available from the GSEA website, but I have not looked in a while.
>
> 2. It is really your preference on how to calculate ratios. I typically
> sweep the median intensity value of the reference set through each test
> sample individually. I do this because I am often interested in looking at
> individual sample variances. You could also average the test samples and
> average the reference samples and then construct a single ratio. It is
> really your preference.
>
> 3. The default settings of PGSEA returns a matrix of z-scores as described
> -- assuming that the test samples were not first not combined in a single
> sample by averaging as discussed in 2. However, the results matrix could
> contain NAs as the PGSEA function has an option to filter the results based
> on a p.value cutoff.  Scores that fall below the p.value threshold will be
> set to NA in the matrix.  If you don't like this behavior, make sure to
> turn
> of that option in the PGSEA function call.
>
> -kyle
>
>
>
> On 9/4/08 9:53 PM, "Weiwei Shi" <helprhelp@gmail.com> wrote:
>
> > Dear all,
> >
> > I have some questions relating to PGSEA package and GSEA method and hope
> to
> > get some replies:
> >
> >
> > 1. After reading the following paper, I think the theoretical basis for
> > PGSEA is very different from GSEA (Broad, MIT).  So, my first question
> is,
> > is there a package in bioconductor running GSEA? (I used some R version
> > downloaded from GSEA website before, though).
> >
> > http://www.biomedcentral.com/1471-2105/6/144
> >
> > 2. The paper above mentioned comparison of two "groups" of samples for a
> > specific pre-defined gene set, but not individual samples. For the case
> of
> > cancer data, for example, I assume PGSEA uses normal patients' medians or
> > something as reference to calculate fold change (ratio data) for each
> cancer
> > patient, then run PGSEA. Is this way PGSEA calculates "enriched" gene
> sets
> > for each sample? I think the question boils down to, how to calculate the
> > fold change or ratio data for PGSEA, esp. in case of experiments with 2
> > factor design and intensity data? (is it a challenging question?)
> >
> > 3. From PGSEA command as below,
> >
> > x <- PGSEA(...);
> >
> > is x a matrix of z-scores described in the paper?
> >
> > thanks,
>
>
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