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The tidyomics ecosystem: Enhancing omic data analyses.
Hutchison, William J; Keyes, Timothy J; Crowell, Helena L; Serizay, Jacques; Soneson, Charlotte; Davis, Eric S; Sato, Noriaki; Moses, Lambda; Tarlinton, Boyd; Nahid, Abdullah A; Kosmac, Miha; Clayssen, Quentin; Yuan, Victor; Mu, Wancen; Park, Ji-Eun; Mamede, Izabela; Ryu, Min Hyung; Axisa, Pierre-Paul; Paiz, Paulina; Poon, Chi-Lam; Tang, Ming; Gottardo, Raphael; Morgan, Martin; Lee, Stuart; Lawrence, Michael; Hicks, Stephanie C; Nolan, Garry P; Davis, Kara L; Papenfuss, Anthony T; Love, Michael I; Mangiola, Stefano.
Afiliación
  • Hutchison WJ; Walter and Eliza Hall Institute of Medical Research, Division of Bioinformatics, Parkville, VIC 3052, Australia.
  • Keyes TJ; Department of Medical Biology, University of Melbourne, Parkville, VIC 3052, Australia.
  • Crowell HL; Stanford University School of Medicine, Department of Pediatrics, USA.
  • Soneson C; University of Zurich, Switzerland.
  • Davis ES; Centre for Genomic Regulation, Barcelona Institute of Science and Technology, Barcelona, Spain.
  • Sato N; Institut Pasteur, CNRS UMR3525, Unité Régulation Spatiale des Génomes, F-75015, Paris, France.
  • Moses L; Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland.
  • Tarlinton B; SIB Swiss Institute of Bioinformatics, Basel, Switzerland.
  • Nahid AA; Bioinformatics and Computational Biology Program, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA.
  • Kosmac M; Division of Health Medical Intelligence, Human Genome Center, The Institute of Medical Science, The University of Tokyo, Japan.
  • Clayssen Q; California Institute of Technology, USA.
  • Yuan V; Queensland Department of Agriculture and Fisheries, Australia.
  • Mu W; Department of Biochemistry and Molecular Biology, Shahjalal University of Science and Technology, Sylhet, Bangladesh.
  • Park JE; Achilles Therapeutics, UK.
  • Mamede I; DNA Script, France.
  • Ryu MH; Department of Statistics, The University of British Columbia, Canada.
  • Axisa PP; Biostatistics Department, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA.
  • Paiz P; Biostatistics Department, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA.
  • Poon CL; Department of Biochemistry and Immunology, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil.
  • Tang M; Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, USA.
  • Gottardo R; Department of Medicine, Harvard Medical School, USA.
  • Morgan M; Université de Toulouse, Inserm, CNRS, Université Toulouse III-Paul Sabatier, Centre de Recherches en Cancérologie de Toulouse, Toulouse, France.
  • Lee S; Stanford University School of Medicine, Department of Biomedical Data Science, USA.
  • Lawrence M; Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA.
  • Hicks SC; Immunitas Therapeutics, USA.
  • Nolan GP; University of Lausanne, Switzerland.
  • Davis KL; Lausanne University Hospital.
  • Papenfuss AT; SIB Swiss Institute of Bioinformatics, Basel, Switzerland.
  • Love MI; Roswell Park Comprehensive Cancer Center, USA.
  • Mangiola S; Genentech, Department of Bioinformatics and Computational Biology, USA.
bioRxiv ; 2024 May 22.
Article en En | MEDLINE | ID: mdl-38826347
ABSTRACT
The growth of omic data presents evolving challenges in data manipulation, analysis, and integration. Addressing these challenges, Bioconductor1 provides an extensive community-driven biological data analysis platform. Meanwhile, tidy R programming2 offers a revolutionary standard for data organisation and manipulation. 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 analysing 7.5 million peripheral blood mononuclear cells from the Human Cell Atlas3, spanning six data frameworks and ten analysis tools.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: BioRxiv Año: 2024 Tipo del documento: Article País de afiliación: Australia
Texto completo
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XML
PubMed Links
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: BioRxiv Año: 2024 Tipo del documento: Article País de afiliación: Australia