A Bayesian methodology for detecting targeted genes under two related experiments.

Abstract:

:Many gene expression data are based on two experiments where the gene expressions of the targeted genes under both experiments are correlated. We consider problems in which objectives are to find genes that are simultaneously upregulated/downregulated under both experiments. A Bayesian methodology is proposed based on directional multiple hypotheses testing. We propose a false discovery rate specific to the problem under consideration, and construct a Bayes rule satisfying a false discovery rate criterion. The proposed method is compared with a traditional rule through simulation studies. We apply our methodology to two real examples involving microRNAs; where in one example the targeted genes are simultaneously downregulated under both experiments, and in the other the targeted genes are downregulated in one experiment and upregulated in the other experiment. We also discuss how the proposed methodology can be extended to more than two experiments.

journal_name

Stat Med

journal_title

Statistics in medicine

authors

Bansal NK,Jiang H,Pradeep P

doi

10.1002/sim.6555

subject

Has Abstract

pub_date

2015-11-10 00:00:00

pages

3362-75

issue

25

eissn

0277-6715

issn

1097-0258

journal_volume

34

pub_type

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