Tidybulk: an R Tidy Framework for Modular Transcriptomic Data Analysis

Overview

Journal Genome Biol

Specialties Biology
Genetics

Date 2021 Jan 23

PMID 33482892

Citations 16

Authors

Stefano Mangiola

Ramyar Molania

Ruining Dong

Maria A Doyle

Anthony T Papenfuss

Affiliations

Soon will be listed here.

Abstract

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 .

Citing Articles

Transcriptional signature of CD56 NK cells predicts favourable prognosis in bladder cancer.

Khan M, Sedgwick A, Sun Y, Vivian J, Corbett A, Dolcetti R Front Immunol. 2025; 15:1474652.

PMID: 39877370 PMC: 11772185. DOI: 10.3389/fimmu.2024.1474652.

The tidyomics ecosystem: enhancing omic data analyses.

Hutchison W, Keyes T, Crowell H, Serizay J, Soneson C, Davis E Nat Methods. 2024; 21(7):1166-1170.

PMID: 38877315 DOI: 10.1038/s41592-024-02299-2.

The ecosystem: Enhancing omic data analyses.

Hutchison W, Keyes T, Crowell H, Serizay J, Soneson C, Davis E bioRxiv. 2024; .

PMID: 38826347 PMC: 11142095. DOI: 10.1101/2023.09.10.557072.

A multi-organ map of the human immune system across age, sex and ethnicity.

Mangiola S, Milton M, Ranathunga N, Li-Wai-Suen C, Odainic A, Yang E bioRxiv. 2024; .

PMID: 38746418 PMC: 11092463. DOI: 10.1101/2023.06.08.542671.

cellsig plug-in enhances CIBERSORTx signature selection for multidataset transcriptomes with sparse multilevel modelling.

Khan M, Wu J, Sun Y, Barrow A, Papenfuss A, Mangiola S Bioinformatics. 2023; 39(12).

PMID: 37952182 PMC: 10692870. DOI: 10.1093/bioinformatics/btad685.

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