Paulina Maria Paiz
Masters Student in Biomedical Data Science, admitted Autumn 2023
Subject Tutor, Student Learning Support
All Publications
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The tidyomics ecosystem: enhancing omic data analyses.
Nature methods
2024
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.
View details for DOI 10.1038/s41592-024-02299-2
View details for PubMedID 38877315
View details for PubMedCentralID 545600