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.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
We added the biological application of tidyomics.
