powsimR: power analysis for bulk and single cell RNA-seq experiments

Beate Vieth; Christoph Ziegenhain; Swati Parekh; Wolfgang Enard; Ines Hellmann

doi:10.1093/bioinformatics/btx435

powsimR: power analysis for bulk and single cell RNA-seq experiments

Bioinformatics. 2017 Nov 1;33(21):3486-3488. doi: 10.1093/bioinformatics/btx435.

Authors

Beate Vieth¹, Christoph Ziegenhain¹, Swati Parekh¹, Wolfgang Enard¹, Ines Hellmann¹

Affiliation

¹ Anthropology & Human Genomics, Department of Biology II, Ludwig-Maximilians University, 82152 Munich, Germany.

PMID: 29036287
DOI: 10.1093/bioinformatics/btx435

Abstract

Summary: Power analysis is essential to optimize the design of RNA-seq experiments and to assess and compare the power to detect differentially expressed genes in RNA-seq data. PowsimR is a flexible tool to simulate and evaluate differential expression from bulk and especially single-cell RNA-seq data making it suitable for a priori and posterior power analyses.

Availability and implementation: The R package and associated tutorial are freely available at https://github.com/bvieth/powsimR.

Contact: vieth@bio.lmu.de or hellmann@bio.lmu.de.

Supplementary information: Supplementary data are available at Bioinformatics online.

MeSH terms

Gene Expression Profiling / methods*
Sequence Analysis, RNA / methods*
Single-Cell Analysis
Software*