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.
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.
Authors: Robert A Amezquita; Aaron T L Lun; Etienne Becht; Vince J Carey; Lindsay N Carpp; Ludwig Geistlinger; Federico Marini; Kevin Rue-Albrecht; Davide Risso; Charlotte Soneson; Levi Waldron; Hervé Pagès; Mike L Smith; Wolfgang Huber; Martin Morgan; Raphael Gottardo; Stephanie C Hicks Journal: Nat Methods Date: 2019-12-02 Impact factor: 28.547
Authors: Kevin R Moon; David van Dijk; Zheng Wang; Scott Gigante; Daniel B Burkhardt; William S Chen; Kristina Yim; Antonia van den Elzen; Matthew J Hirn; Ronald R Coifman; Natalia B Ivanova; Guy Wolf; Smita Krishnaswamy Journal: Nat Biotechnol Date: 2019-12-03 Impact factor: 54.908