4.5 Article

tidybulk: an R tidy framework for modular transcriptomic data analysis

期刊

GENOME BIOLOGY
卷 22, 期 1, 页码 -

出版社

BMC
DOI: 10.1186/s13059-020-02233-7

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资金

  1. Pamela Galli Single Cell & Computational Genomics Initiative
  2. Australian National Health and Medical Research Council (NHMRC) [1054618]
  3. NHMRC [1116955]
  4. Victorian State Government Operational Infrastructure Support
  5. Australian Government NHMRC Independent Research Institute Infrastructure Support
  6. National Health and Medical Research Council of Australia [1116955] Funding Source: NHMRC

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The recently developed tidybulk is a modular framework for bulk transcriptional analyses, introducing a tidy transcriptomic data structure paradigm and analysis grammar. It covers a wide variety of analysis procedures and integrates a large ecosystem of publicly available analysis algorithms. Tidybulk reduces coding burden, facilitates reproducibility, increases efficiency for expert users, lowers the learning curve for inexperienced users, and connects transcriptional data analysis with the tidyverse framework.
Recently, efforts have been made toward the harmonization of transcriptomic data structures and workflows using the concept of data tidiness, to facilitate modularisation. We present tidybulk, a modular framework for bulk transcriptional analyses that introduces a tidy transcriptomic data structure paradigm and analysis grammar. Tidybulk covers a wide variety of analysis procedures and integrates a large ecosystem of publicly available analysis algorithms under a common framework. Tidybulk decreases coding burden, facilitates reproducibility, increases efficiency for expert users, lowers the learning curve for inexperienced users, and bridges transcriptional data analysis with the tidyverse. Tidybulk is available at R/Bioconductor bioconductor.org/packages/tidybulk.

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