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Dear Gordon,
many thanks! I thought that was the answer but I wanted to be sure.
Best wishes
Richard.
________________________________
From: Gordon K Smyth <smyth@wehi.edu.au>
Cc: bioconductor@r-project.org
Sent: Thu, 27 January, 2011 23:48:54
Subject: GeneSetTest: which statistics and other measures can be used
Dear Richard,
Yes, geneSetTest() is designed so that it can be used with any
statistic
of interest, exactly as you suggest. There is no need for the
statistic
to be a "test statistic" is the usual statistical sense. It can be
anything that you want to rank the genes by.
The null hypothesis is that the gene set is no more highly ranked than
randomly selected sets of the same size.
Best wishes
Gordon
> Date: Thu, 27 Jan 2011 11:25:50 +0000 (GMT)
> To: bioconductor@r-project.org
> Subject: [BioC] GeneSetTest: which statistics and other measures can
> be used
>
> Dear list,
>
> having read the description of GeneSetTest I understand that it
tests whether
a
> specified subset of genes have higher values of a test statistic
than random
> expectation, using a permutation test. If the test statistic has
positive and
> negative values it is treated as 't-like'; if it has only positive
values it
is
> treated as 'F-like'.
>
> My question is: is there any restriction on the type of statistic
used in this
> analysis? If GeneSetTest employs a straightforward permutation test
then the
> probability distribution of the statistic shouldn't matter, should
it? Only
> whether it contains positive-only versus positive and negative
values?
>
> To give a couple of specific examples:
>
> 1) The deviance is a very useful statistic in generalized linear
modelling and
> maximum likelihood analysis - would there be any issue with using
the deviance
> as the test statistic?
>
> 2) Any number of other 'statistics' that are not probability
distributions
> commonly employed in hypothesis testing might be calculated from
gene
>expression
> data, a simple example being log fold change. Could such a measure
>appropriately
> be used in GeneSetTest (in the sense that it wouldn't violate any of
the
> assumptions required to produce unbiased p values)?
>
> Many thanks and best wishes
>
> Richard.
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