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Ida Hatoum
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10

@ida-hatoum-6436
Last seen 9.1 years ago

Hi,
Is there an R/Bioconductor package that can do error-weighted ANOVAs
for microarray data? For every sample and every transcript I have
both a value estimate and an error estimate and I'd like to use the
error estimates to weight the fold changes and p-values.
The error-weighting model of interest is described here:
http://bioinformatics.oxfordjournals.org/content/22/9/1111.full.pdf+ht
ml
Background:
I have inherited a project that was started using Rosetta Resolver
software. Rosetta no longer exists, and the Resolver software was
purchased by Microsoft only to be discontinued. Microarray gene
expression data were generated from Affy chips, and I have access to
the data that are already normalized/pre-processed. Resolver has
generated normalized data with the following 3 pieces of information
for EACH sample and EACH transcript: value, p-value and error
estimate (the p-value and error estimate are estimated for each
sample, it's not a group estimate). I also have group-level
comparison p-value and fold-change results generated from Resolver.
When I run simple means and t-test/anovas on the "values" for each
sample (e.g., using genefilter rowFtests) I get slightly different
fold changes and slightly to significantly different p-values than
what is given from Resolver. I assume this is because of the error-
weighting performed as part of the one-way ANOVAs in Resolver. I'd
like to recreate the results from Resolver, as a significant amount of
down-stream analyses have been performed on the Resolver-derived fold
change and p-value data, but am not particularly comfortable using the
FC and p-value data given to me if I can't replicate it myself.
Any insight would be greatly appreciated!
Sincerely,
Ida