thanks for reply.
I've performed a part of example analysis from metaArray, I haven't
succeeded to perform analysis on a dataset from three partially
overlapping experiments. Zscore function gave results only for the
If I found a way to transform various experiments to effect-size
scale (probably with inverse-variance method as recommended in
Ramasamy et al. 2008 - very useful article) or something similar
I will try metahdep.
> Hi Maciej,
> My metahdep package doesn't require all datasets to come from the
version -- so
while the package's tutorial vignette doesn't explicitly say anything
values, the example there does allow for missing values in this sense
represented in all datasets).
> As to your second question, if you're combining studies with
platforms (Affy for some, two-color for others, for example), you'll
need to be
define an effect size (or some measure of differential expression)
thing on all platforms, and for which you can calculate a meaningful
think trans-platform cases like this lead to the appeal of alternative
as those in the metaArray package (which uses the 'probability of
expression' or POE
> John Stevens
> From: bioconductor-bounces at r-project.org [bioconductor-bounces at
on behalf of
mjonczyk at biol.uw.edu.pl [mjonczyk at biol.uw.edu.pl]
> Sent: Tuesday, August 09, 2011 1:45 PM
> To: bioconductor at r-project.org
> Subject: [BioC] Missing values - metaArray, GeneMeta, RankProd,
> Dear List Members,
> I'd like to perform a metaanalysis for few (minimum three) datasets.
> Some of them are one channel (Affymetrix), some two-colour data.
> Obviously, when I join, say three studies I will have big dataset in
> which some data will be missing. Just because some probes will be
> in two experiments and absent in third experiment. I'd prefer not to
> use *only* probes which are present on all arrays, but also this
> are present on two arrays.
> My *question* is: which package (metaArray, GeneMeta, RankProd,
> could handle metaanalysis with missing data - in tutorials/manuals
> not stated if missing data is allowed. Although metaArray cites
> package as a example software for merging data with non-overlapping
> Second *question* which of the above package will best handle
> from merged two-colour and affymetrix studies?
> I'd also be grateful for directions to additional tutorials,
> Best Regards,
> Maciej Jończyk
> Maciej Jończyk, MSc
> Department of Plant Molecular Ecophysiology
> Institute of Plant Experimental Biology
> Faculty of Biology, University of Warsaw
> 02-096 Warszawa, Miecznikowa