omicplotR: Visualizing omic datasets as compositions

Abstract

Background: Differential abundance analysis is widely used with high-throughput sequencing data to compare gene abundance or expression between groups of samples. Many software packages exist for this purpose, but each uses a unique set of statistical assumptions to solve problems on a case-by-case basis. These software packages are typically difficult to use for researchers without command-line skills, and software that does offer a graphical user interface do not use a compositionally valid method. Results: OmicplotR facilitates visual exploration of omic datasets for researchers with and without prior scripting knowledge. Reproducible visualizations include principal component analysis, hierarchical clustering, MA plots and effect plots. We demonstrate the functionality of omicplotR using a publicly available metatranscriptome dataset. Conclusions: OmicplotR provides a graphical user interface to explore sequence count data using generalizable compositional methods, facilitating visualization for investigators without command-line experience.