Abstract
The exponential growth of omic data presents challenges in data manipulation, analysis, and integration. Addressing these challenges, Bioconductor offers an extensive data analysis platform and community, while R tidy programming offers a standard data organisation and manipulation that has revolutionised data science. Bioconductor and tidy R have mostly remained independent; bridging these two ecosystems would streamline omic analysis, ease learning and encourage cross-disciplinary collaborations. Here, we introduce the tidyomics ecosystem—a suite of interoperable software that brings the vast tidy software ecosystem to omic data analysis.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Copyright
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
Posted September 13, 2023.
