The tidyomics ecosystem: enhancing omic data analyses

William J. Hutchison^†, Timothy J. Keyes^†, The tidyomics Consortium, Helena L. Crowell, Jacques Serizay, Charlotte Soneson, Eric S. Davis, Noriaki Sato, Lambda Moses, Boyd Tarlinton, Abdullah A. Nahid, Miha Kosmac, Quentin Clayssen, Victor Yuan, Wancen Mu, Ji-Eun Park, Izabela Mamede, Min Hyung Ryu, Pierre-Paul Axisa, Paulina Paiz, Chi-Lam Poon, Ming Tang, Raphael Gottardo, Martin Morgan, Stuart Lee, Michael Lawrence, Stephanie C. Hicks, Garry P. Nolan, Kara L. Davis, Anthony T. Papenfuss, Michael I. Love, Stefano Mangiola

^† Equal contribution

Nature Methods21(7): 1166-1170 1 June 2024

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Abstract

The growth of omic data presents evolving challenges in data manipulation, analysis and integration. Addressing these challenges, Bioconductor provides an extensive community-driven biological data analysis platform. Meanwhile, tidy R programming offers a revolutionary data organization and manipulation standard. 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 analyzing 7.5 million peripheral blood mononuclear cells from the Human Cell Atlas, spanning six data frameworks and ten analysis tools.

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Hutchison WJ, Keyes TJ, The tidyomics Consortium, Crowell HL, Serizay J, Soneson C, et al. The tidyomics ecosystem: enhancing omic data analyses. Nature Methods. 2024;21(7):1166-1170. doi:10.1038/s41592-024-02299-2

@article{hutchinson_natmethods_2024,
  author  = {Hutchison, William J. and Keyes, Timothy J. and {The tidyomics Consortium} and Crowell, Helena L. and Serizay, Jacques and Soneson, Charlotte and Davis, Eric S. and Sato, Noriaki and Moses, Lambda and Tarlinton, Boyd and Nahid, Abdullah A. and Kosmac, Miha and Clayssen, Quentin and Yuan, Victor and Mu, Wancen and Park, Ji-Eun and Mamede, Izabela and Ryu, Min Hyung and Axisa, Pierre-Paul and Paiz, Paulina and Poon, Chi-Lam and Tang, Ming and Gottardo, Raphael and Morgan, Martin and Lee, Stuart and Lawrence, Michael and Hicks, Stephanie C. and Nolan, Garry P. and Davis, Kara L. and Papenfuss, Anthony T. and Love, Michael I. and Mangiola, Stefano},
  title   = {{The tidyomics ecosystem: enhancing omic data analyses}},
  journal = {Nature Methods},
  year    = {2024},
  volume  = {21},
  number  = {7},
  pages   = {1166--1170},
  doi     = {10.1038/s41592-024-02299-2},
  url     = {https://doi.org/10.1038/s41592-024-02299-2}
}

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