Abstract
The growth of omic data presents evolving challenges in data manipulation, analysis, and integration. Addressing these challenges, Bioconductor1 provides an extensive community-driven biological data analysis platform. Meanwhile, tidy R programming2 offers a revolutionary standard for data organisation and manipulation. Here, we present the tidyomics software ecosystem, bridging Bioconductor to the tidy R paradigm. This ecosystem aims to streamline omic analysis, ease learning, and encourage cross-disciplinary collaborations. We demonstrate the effectiveness of tidyomics by analysing 7.5 million peripheral blood mononuclear cells from the Human Cell Atlas3, spanning six data frameworks and ten analysis tools.
Competing Interest Statement
R.G. has received consulting income from Takeda and Sanofi, and declares ownership in Ozette Technologies. M.K. is an employee of and declares ownership in Achilles Therapeutics. The remaining authors declare no competing interests.
Footnotes
↵† A list of authors and their affiliations appears at the end of the paper.
We revised the manuscript with new figures.
