title: Experimental Design and Power Calculation for RNA-seq Experiments.
abstract: Power calculation is a critical component of RNA-seq experimental design. The flexibility of RNA-seq experiment and the wide dynamic range of transcription it measures make it an attractive technology for whole transcriptome analysis. These features, in addition to the high dimensionality of RNA-seq data, bring complexity in experimental design, making an analytical power calculation no longer realistic. In this chapter we review the major factors that influence the statistical power of detecting differential expression, and give examples of power assessment using the R package PROPER.
authors.affiliation: Department of Biostatistics, Brown University, Providence, RI, USA.
authors.forename: Zhijin
authors.initials: Z
authors.lastname: Wu
authors.affiliation: Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
authors.forename: Hao
authors.initials: H
authors.lastname: Wu
mesh_terms: D019295:Computational Biology / Q000379:methods; D015870:Gene Expression; D020869:Gene Expression Profiling / Q000379:methods; D023281:Genomics / Q000379:methods; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods; D012107:Research Design; D017423:Sequence Analysis, RNA / Q000379:methods; D012984:Software; D064878:Web Browser
keywords: Experimental design; Gene expression; RNA-Seq; Sample size; Statistical power