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. 2017 Sep 1;33(17):2774-2775.
doi: 10.1093/bioinformatics/btx292.

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

Francesco Del Carratore  1 , Andris Jankevics  2 , Rob Eisinga  3 , Tom Heskes  4 , Fangxin Hong  5 , Rainer Breitling  1
Affiliations

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

Francesco Del Carratore et al. Bioinformatics. .

Abstract

Motivation: 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.

Results: We implemented a completely refactored version of the RankProd package, which provides a more principled implementation of the statistics for unpaired datasets. Moreover, the permutation-based P -value estimation methods have been replaced by exact methods, providing faster and more accurate results.

Availability and implementation: RankProd 2.0 is available at Bioconductor ( https://www.bioconductor.org/packages/devel/bioc/html/RankProd.html ) and as part of the mzMatch pipeline ( http://www.mzmatch.sourceforge.net ).

Contact: rainer.breitling@manchester.ac.uk.

Supplementary information: Supplementary data are available at Bioinformatics online.

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References

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