RankProd 2.0: a refactored bioconductor package for detecting differentially expressed features in molecular profiling datasets | Zendy

Francesco Del Carratore | Zendy; Andris Jankevics | Zendy; Rob Eisinga | Zendy; Tom Heskes | Zendy; Fangxin Hong | Zendy; Rainer Breitling | Zendy

Open Access

RankProd 2.0: a refactored bioconductor package for detecting differentially expressed features in molecular profiling datasets

Author(s) -

Francesco Del Carratore,

Andris Jankevics,

Rob Eisinga,

Tom Heskes,

Fangxin Hong,

Rainer Breitling

Publication year - 2017

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btx292

Subject(s) - bioconductor , r package , code refactoring , computer science , profiling (computer programming) , pipeline (software) , data mining , rank (graph theory) , software , computational biology , biology , programming language , mathematics , biochemistry , combinatorics , gene

The Rank Product (RP) is a statistical technique widely used to detect differentially expressed features in molecular profiling experiments such as transcriptomics, metabolomics and proteomics studies. An implementation of the RP and the closely related Rank Sum (RS) statistics has been available in the RankProd Bioconductor package for several years. However, several recent advances in the understanding of the statistical foundations of the method have made a complete refactoring of the existing package desirable.

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