The tidyomics ecosystem: Enhancing omic data analyses

Abstract The exponential availability of omic data presents challenges in data manipulation, analysis, and integration. Addressing these challenges, Bioconductor offers an extensive community-driven data analysis platform, while R tidy programming offers a revolutionary standard for data organisation and manipulation. Bioconductor and tidy R have mostly remained independent; bridging them would streamline omic analysis and ease learning and cross-disciplinary collaborations. Here, we introduce the tidyomics software ecosystem that brings the R tidy toolkit to omic data analysis. We demonstrate its benefits by analysing 7.5 million PBMCs from the Human Cell Atlas, bridging six data frameworks and ten analysis tools.