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Global FDR control across multiple RNAseq experiments.

Accepted version
Peer-reviewed

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Authors

Liou, Lathan 
Hornburg, Milena 
Robertson, David S 

Abstract

MOTIVATION: While classical approaches for controlling the false discovery rate (FDR) of RNAseq experiments have been well described, modern research workflows and growing databases enable a new paradigm of controlling the FDR globally across RNAseq experiments in the past, present, and future. The simplest analysis strategy that analyses each RNAseq experiment separately and applies an FDR correction method can lead to inflation of the overall FDR. We propose applying recently developed methodology for online multiple hypothesis testing to control the global FDR in a principled way across multiple RNAseq experiments. RESULTS: We show that repeated application of classical repeated offline approaches has variable control of global FDR of RNAseq experiments over time. We demonstrate that the online FDR algorithms are a principled way to control FDR. Furthermore, in certain simulation scenarios, we observe empirically that online approaches have comparable power to repeated offline approaches. AVAILABILITY AND IMPLEMENTATION: The onlineFDR package is freely available at http://www.bioconductor.org/packages/onlineFDR. Additional code used for the simulation studies can be found at https://github.com/latlio/onlinefdr_rnaseq_simulation. SUPPLEMENTARY INFORMATION: Supplementary Appendix is available in Bioinformatics online.

Description

Keywords

differential expression, false discovery rate, multiple hypothesis testing, RNAseq

Journal Title

Bioinformatics

Conference Name

Journal ISSN

1367-4803
1367-4811

Volume Title

Publisher

Oxford University Press (OUP)
Sponsorship
Medical Research Council (MC_UU_00002/14)
National Institute for Health and Care Research (IS-BRC-1215-20014)