Software for the integration of multi-omics experiments in Bioconductor
Software for the integration of multi-omics experiments in Bioconductor
ABSTRACT Multi-omics experiments are increasingly commonplace in biomedical research, and add layers of complexity to experimental design, data integration, and analysis. R and Bioconductor provide a generic framework for statistical analysis and visualization, as well as specialized data classes for a variety of high-throughput data types, but methods are lacking for integrative analysis of multi-omics experiments. The MultiAssayExperiment software package, implemented in R and leveraging Bioconductor software and design principles, provides for the coordinated representation of, storage of, and operation on multiple diverse genomics data. We provide all of the multiple ‘omics data for each cancer tissue in The Cancer Genome Atlas (TCGA) as ready-to-analyze MultiAssayExperiment objects, and demonstrate in these and other datasets how the software simplifies data representation, statistical analysis, and visualization. The MultiAssayExperiment Bioconductor package reduces major obstacles to efficient, scalable and reproducible statistical analysis of multi-omics data and enhances data science applications of multiple omics datasets.
Chan Tiffany、Gomez-Cabrero David、Hansen Kasper D.、Morgan Martin、Ramos Marcel、Azhar Rimsha、Kodali Hanish、Davis Sean、Louis Marie Stephie、Riester Markus、Mer Arvind Singh、Haibe-Kains Benjamin、Re Angela、Basunia Azfar、Schiffer Lucas、Carey Vincent、Culhane Aedin C.、Waldron Levi、Chapman Philip、Cabrera Carmen Rodriguez
CUNY School of Public Health||Institute for Implementation Science in Population Health, City University of New YorkMucosal and Salivary Biology Division, King's College London Dental InstituteDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health||McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of MedicineRoswell Park Cancer Institute, University of BuffaloCUNY School of Public Health||Institute for Implementation Science in Population Health, City University of New YorkCUNY School of Public Health||Institute for Implementation Science in Population Health, City University of New YorkCUNY School of Public Health||Institute for Implementation Science in Population Health, City University of New YorkCenter for Cancer Research, National Cancer Institute, National Institutes of HealthCUNY School of Public Health||Institute for Implementation Science in Population Health, City University of New YorkNovartis Institutes for BioMedical ResearchPrincess Margaret Cancer Center, University Health NetworkPrincess Margaret Cancer Center, University Health Network||Department of Medical Biophysics, University of Toronto||Department of Computer Science, University of Toronto||Ontario Institute of Cancer ResearchLaboratory of Translational Genomics, Centre for Integrative Biology, University of Trento, Polo Scientifico e Tecnologico Fabio FerrariHarvard TH Chan School of Public HealthCUNY School of Public Health||Institute for Implementation Science in Population Health, City University of New YorkHarvard TH Chan School of Public Health||Channing Division of Network Medicine, Brigham and Women?ˉs Hospital and Harvard Medical SchoolHarvard TH Chan School of Public Health||Dana-Farber Cancer Institute, 450 Brookline AveCUNY School of Public Health||Institute for Implementation Science in Population Health, City University of New YorkComputational Biology Support Team, Cancer Research UK Manchester Institute, The University of ManchesterCUNY School of Public Health||Institute for Implementation Science in Population Health, City University of New York
生物科学研究方法、生物科学研究技术计算技术、计算机技术生物科学现状、生物科学发展
Chan Tiffany,Gomez-Cabrero David,Hansen Kasper D.,Morgan Martin,Ramos Marcel,Azhar Rimsha,Kodali Hanish,Davis Sean,Louis Marie Stephie,Riester Markus,Mer Arvind Singh,Haibe-Kains Benjamin,Re Angela,Basunia Azfar,Schiffer Lucas,Carey Vincent,Culhane Aedin C.,Waldron Levi,Chapman Philip,Cabrera Carmen Rodriguez.Software for the integration of multi-omics experiments in Bioconductor[EB/OL].(2025-03-28)[2025-06-29].https://www.biorxiv.org/content/10.1101/144774.点此复制
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