Statistical tools for synthesizing lists of differentially expressed features in related experiments.

Abstract:

:We propose a novel approach for finding a list of features that are commonly perturbed in two or more experiments, quantifying the evidence of dependence between the experiments by a ratio. We present a Bayesian analysis of this ratio, which leads us to suggest two rules for choosing a cut-off on the ranked list of p values. We evaluate and compare the performance of these statistical tools in a simulation study, and show their usefulness on two real datasets.

journal_name

Genome Biol

journal_title

Genome biology

authors

Blangiardo M,Richardson S

doi

10.1186/gb-2007-8-4-r54

subject

Has Abstract

pub_date

2007-01-01 00:00:00

pages

R54

issue

4

eissn

1474-7596

issn

1474-760X

pii

gb-2007-8-4-r54

journal_volume

8

pub_type

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