The tidyomics ecosystem: enhancing omic data analyses

William J Hutchison; Timothy J Keyes; tidyomics Consortium; Helena L Crowell; Jacques Serizay; Charlotte Soneson; Eric S Davis; Noriaki Sato; Lambda Moses; Boyd Tarlinton; Abdullah A Nahid; Miha Kosmac; Quentin Clayssen; Victor Yuan; Wancen Mu; Ji-Eun Park; Izabela Mamede; Min Hyung Ryu; Pierre-Paul Axisa; Paulina Paiz; Chi-Lam Poon; Ming Tang; Raphael Gottardo; Martin Morgan; Stuart Lee; Michael Lawrence; Stephanie C Hicks; Garry P Nolan; Kara L Davis; Anthony T Papenfuss; Michael I Love; Stefano Mangiola

doi:10.1038/s41592-024-02299-2

The tidyomics ecosystem: enhancing omic data analyses

Nat Methods. 2024 Jul;21(7):1166-1170. doi: 10.1038/s41592-024-02299-2. Epub 2024 Jun 14.

Authors

William J Hutchison^#^{1

2}, Timothy J Keyes^#^{3

4}; tidyomics Consortium; Helena L Crowell^{5

6}, Jacques Serizay⁷, Charlotte Soneson^{8

9}, Eric S Davis¹⁰, Noriaki Sato¹¹, Lambda Moses¹², Boyd Tarlinton¹³, Abdullah A Nahid¹⁴, Miha Kosmac¹⁵, Quentin Clayssen¹⁶, Victor Yuan¹⁷, Wancen Mu¹⁸, Ji-Eun Park¹⁸, Izabela Mamede¹⁹, Min Hyung Ryu^{20

21}, Pierre-Paul Axisa²², Paulina Paiz³, Chi-Lam Poon²³, Ming Tang²⁴, Raphael Gottardo^{9

25

26}, Martin Morgan²⁷, Stuart Lee²⁸, Michael Lawrence²⁸, Stephanie C Hicks^{29

30

31}, Garry P Nolan³², Kara L Davis⁴, Anthony T Papenfuss^{33

34}, Michael I Love^{35

36}, Stefano Mangiola^{37

38

39}

Affiliations

¹ The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia.
² Department of Medical Biology, University of Melbourne, Parkville, Victoria, Australia.
³ Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA.
⁴ Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
⁵ University of Zurich, Zurich, Switzerland.
⁶ Centro Nacional de Análisis Genómico (CNAG), Barcelona, Spain.
⁷ Unité Régulation Spatiale des Génomes, Institut Pasteur, CNRS UMR3525, Paris, France.
⁸ Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland.
⁹ SIB Swiss Institute of Bioinformatics, Basel, Switzerland.
¹⁰ Bioinformatics and Computational Biology Program, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA.
¹¹ Division of Health Medical Intelligence, Human Genome Center, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan.
¹² California Institute of Technology, Pasadena, CA, USA.
¹³ Queensland Department of Agriculture and Fisheries, Brisbane, Queensland, Australia.
¹⁴ Department of Biochemistry and Molecular Biology, Shahjalal University of Science and Technology, Sylhet, Bangladesh.
¹⁵ Achilles Therapeutics, London, UK.
¹⁶ DNA Script, Le Kremlin-Bicêtre, France.
¹⁷ Department of Statistics, The University of British Columbia, Vancouver, British Columbia, Canada.
¹⁸ Biostatistics Department, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA.
¹⁹ Department of Biochemistry and Immunology, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.
²⁰ Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.
²¹ Department of Medicine, Harvard Medical School, Boston, MA, USA.
²² Centre de Recherches en Cancérologie de Toulouse, Université de Toulouse, Inserm, CNRS, Université Toulouse III-Paul Sabatier, Toulouse, France.
²³ Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA.
²⁴ Immunitas Therapeutics, Waltham, MA, USA.
²⁵ University of Lausanne, Lausanne, Switzerland.
²⁶ Lausanne University Hospital, Lausanne, Switzerland.
²⁷ Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA.
²⁸ Department of Bioinformatics and Computational Biology, Genentech, South San Francisco, CA, USA.
²⁹ Department of Biostatistics, Johns Hopkins University, Baltimore, MD, USA.
³⁰ Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
³¹ Malone Center for Engineering in Healthcare, Johns Hopkins University, Baltimore, MD, USA.
³² Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
³³ The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia. [email protected].
³⁴ Department of Medical Biology, University of Melbourne, Parkville, Victoria, Australia. [email protected].
³⁵ Biostatistics Department, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA. [email protected].
³⁶ Genetics Department, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA. [email protected].
³⁷ The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia. [email protected].
³⁸ Department of Medical Biology, University of Melbourne, Parkville, Victoria, Australia. [email protected].
³⁹ South Australian immunoGENomics Cancer Institute, The University of Adelaide, Adelaide, South Australia, Australia. [email protected].

^# Contributed equally.

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

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.

MeSH terms

Computational Biology / methods
Data Analysis
Genomics / methods
Humans
Leukocytes, Mononuclear / cytology
Leukocytes, Mononuclear / metabolism
Software*