A Bayesian methodology for detecting targeted genes under two related experiments.
Stat Med
; 34(25): 3362-75, 2015 Nov 10.
Article
in En
| MEDLINE
| ID: mdl-26112310
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.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Gene Expression Regulation
/
Models, Statistical
/
Bayes Theorem
/
Gene Expression Profiling
/
MicroRNAs
Type of study:
Prognostic_studies
/
Risk_factors_studies
Limits:
Humans
Language:
En
Journal:
Stat Med
Year:
2015
Document type:
Article
Affiliation country:
Estados Unidos