Journal article

tidybulk: an R tidy framework for modular transcriptomic data analysis

Stefano Mangiola, Ramyar Molania, Ruining Dong, Maria A Doyle, Anthony T Papenfuss

GENOME BIOLOGY | BMC | Published : 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...

View full abstract


Awarded by Australian National Health and Medical Research Council (NHMRC)

Awarded by NHMRC

Awarded by National Health and Medical Research Council of Australia

Funding Acknowledgements

SM and RM were supported by the Pamela Galli Single Cell & Computational Genomics Initiative. ATP was supported by an Australian National Health and Medical Research Council (NHMRC) Program Grant (1054618) and NHMRC Senior Research Fellowship (1116955). The research benefitted by support from the Victorian State Government Operational Infrastructure Support and Australian Government NHMRC Independent Research Institute Infrastructure Support.