A Bayesian Methodology for Detecting Targeted Genes Under Two Related Experiments

Authors

Naveen K. Bansal, Marquette UniversityFollow
Hongmei Jiang, Northwestern University
Prachi Pradeep, Marquette UniversityFollow

Document Type

Article

Language

eng

Format of Original

14 p.

Publication Date

11-10-2015

Publisher

Wiley

Source Publication

Statistics in Medicine

Source ISSN

0277-6715

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.

Comments

Statistics in Medicine, Vol. 34, No. 25 (November 2015): 3362-3375. DOI.

Recommended Citation

Bansal, Naveen K.; Jiang, Hongmei; and Pradeep, Prachi, "A Bayesian Methodology for Detecting Targeted Genes Under Two Related Experiments" (2015). Mathematics, Statistics and Computer Science Faculty Research and Publications. 432.
https://epublications.marquette.edu/mscs_fac/432