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tidybulk: an R tidy framework for modular transcriptomic data analysis.

Stefano MangiolaRamyar MolaniaRuining DongMaria A DoyleAnthony T Papenfuss
Published in: Genome biology (2021)
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 .
Keyphrases
  • data analysis
  • gene expression
  • electronic health record
  • single cell
  • machine learning
  • transcription factor
  • rna seq
  • deep learning
  • risk assessment
  • mass spectrometry