pcaExplorer: an R/Bioconductor package for interacting with RNA-seq principal components

Abstract

BackgroundPrincipal component analysis (PCA) is frequently used in genomics applications for quality assessment and exploratory analysis in high-dimensional data, such as RNA sequencing (RNA-seq) gene expression assays. Despite the availability of many software packages developed for this purpose, an interactive and comprehensive interface for performing these operations is lacking.\n\nResultsWe developed the pcaExplorer software package to enhance commonly performed analysis steps with an interactive and user-friendly application, which provides state saving as well as the automated creation of reproducible reports. pcaExplorer is implemented in R using the Shiny framework and exploits data structures from the open-source Bioconductor project. Users can easily generate a wide variety of publication-ready graphs, while assessing the expression data in the different modules available, including a general overview, dimension reduction on samples and genes, as well as functional interpretation of the principal components.\n\nConclusionpcaExplorer is distributed as an R package in the Bioconductor project (http://bioconductor.org/packages/pcaExplorer/). Being designed to assist a broad range of researchers in the critical step of interactive data exploration, pcaExplorer is a practical companion tool for any transcriptomic analysis, with an efficient design that facilitates hypothesis generation, while at the same time providing the foundation for reproducible analyses.