[BioC] ttest or fold change

Stephen Henderson s.henderson at ucl.ac.uk
Tue Dec 16 12:27:57 MET 2003

This is exactly the idea behind the False Discovery Rate(FDR) algorithms
that adjust p-values that you can find described in both the multtest and
Limma packages.

A truly excellent reply, and one which I will no doubt refer to
frequently; I am still
very much a novice statistician.  However, and please correct me if I am
wrong, but
I presume that some scientists are equally afraid of false negatives as
false positives?
i.e. that if we are so conservative such that we try to ENSURE that
there are NO
false positives, we may throw away genes as not differentially expressed
when in
reality they are?  It will be interesting to have a discussion on this -
is it possible,
using statistics, to guarentee both no false positives and no false
negatives?  If not,
then surely the investigator must decide which is relevant to the study
in question before 
going on to decide which stats to use.

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