Ramos, Marcel, Schiffer, Lucas, Re, Angela, Azhar, Rimsha, Rodriguez Cabrera, Carmen , Chan, Tiffany, Chapman, Philip , Gomez-Cabrero, David, Haibe-Kains, Benjamin, Hansen, Kasper, Kodali, Hanish , Louis, Marie Stephie, Mer, Arvind , Riester, Markus, Morgan, Martin, Carey, Vincent and Waldron, Levi (2017) Software for the integration of multi-omics experiments in Bioconductor. Cancer research. ISSN 1538-7445; 0008-5472

Abstract

Background
Cancer research has been transformed by the general availability of high-throughput molecular
assays that can measure multiple complementary biological processes, leading to complex
experiments, analysis designs, and data integration challenges. New software classes and
methods that deal with the complexity of multiple assays applied across overlapping sample
sets are needed to enable efficient analysis of these complex multi-omics datasets.
Methods
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.
Results
Example applications that integrate omics data types showcase the software and
documentation. We also provide ready-to-analyze MultiAssayExperiment objects for each
cancer type in The Cancer Genome Atlas (TCGA).
Conclusions
The MultiAssayExperiment Bioconductor package reduces major obstacles to efficient and
reproducible statistical analysis of multi-omics data and enhances data science applications of
multiple omics datasets.

Item Type:	Article
Date Deposited:	19 Dec 2017 00:45
Last Modified:	19 Dec 2017 00:45
URI:	https://oak.novartis.com/id/eprint/32102