Data from Software for the Integration of Multiomics Experiments in Bioconductor

• DOI: 10.1158/0008-5472.c.6510072
• Publication Date: 2024-03-12T22:51:29Z
• Authors: Marcel Ramos; Lucas Schiffer; Angela Re; Rimsha Azhar; Azfar Basunia; Carmen Rodriguez; Tiffany Chan; Phil Chapman; Sean R. Davis; David Gomez-Cabrero; Aedin C. Culhane; Benjamin Haibe-Kains; Kasper D. Hansen; Hanish Kodali; Marie S. Louis; Arvind S. Mer; Markus Riester; Martin Morgan; Vince Carey; Levi Waldron
• Keywords: Bioconductor

<div>Abstract<p>Multiomics experiments are increasingly commonplace in biomedical research and add layers of complexity to experimental design, data integration, analysis. R Bioconductor provide a generic framework for statistical analysis visualization, as well specialized classes variety high-throughput types, but methods lacking integrative multiomics experiments. The MultiAssayExperiment software package, implemented leveraging design principles, provides the coordinated representation of, storage operation on multiple diverse genomics data. We unrestricted ‘omics each cancer tissue Cancer Genome Atlas ready-to-analyze objects demonstrate these other datasets how simplifies representation, analysis, visualization. package reduces major obstacles efficient, scalable, reproducible enhances science applications omics datasets. <i>Cancer Res; 77(21); e39–42. ©2017 AACR</i>.</p></div>