The tidyomics ecosystem: enhancing omic data analyses

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Hutchison, W. J., Keyes, T. J., Crowell, H. L., Serizay, J., Soneson, C., Davis, E. S., Sato, N., Moses, L., Tarlinton, B. and The tidyomics, C. (2024) The tidyomics ecosystem: enhancing omic data analyses. Nature Methods, 21 (7). pp. 1166-1170. ISSN 1548-7105

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Article Link: https://doi.org/10.1038/s41592-024-02299-2

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.

Item Type:	Article
Corporate Creators:	Department of Agriculture and Fisheries, Queensland
Business groups:	Horticulture and Forestry Science
Keywords:	Computational biology and bioinformatics Education
Subjects:	Agriculture > Agriculture (General) > Agricultural economics Science > Statistics > Statistical data analysis Science > Statistics > Statistical software Agriculture > Agriculture (General) > Farm economics. Farm management. Agricultural mathematics
Live Archive:	06 Aug 2024 05:47
Last Modified:	06 Aug 2024 05:47

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