title: Extending the R LibraryPROPERto Enable Power Calculations for Isoform-Level Analysis withEBSeq.
abstract: RNA-Sequencing (RNA-Seq) has become a routine technology for investigating gene expression differences in comparative transcriptomic studies. Differential expression (DE) analysis of the isoforms of genes is just emerging now that expression (read counts) can be estimated with higher accuracy at the isoform level. Estimating the statistical power that can be achieved with a specific number of repeats is a key step in RNA-Seq analysis. The R library proper was developed to provide realistic empirical power analysis. However, proper uses differential expression methods more suited for power calculation of gene-level expression data. We propose extensions to this tool that would allow for power analysis which takes into account the specificities of isoforms expression. This was achieved by enabling the use ofEBSeq, a DE approach well-tailored for isoform-level expression, as an additional analysis method withinPROPER. The new extensions and exemplar code for their usage are freely available online at: https://github.com/agaye/proper_extension.
authors.affiliation: Metabolic, Cardiovascular and Inflammatory Disease Genomics Branch, National Human Genome Research Institute Bethesda, MD, USA.
authors.forename: Amadou
authors.initials: A
authors.lastname: Gaye
keywords: differential expression analysis; genetic; isoforms; mRNA; statistical power; transcription