Software for the Integration of Multiomics Experiments in Bioconductor

Cancer Research
Marcel RamosLevi Waldron

Abstract

Multiomics 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 multiomics 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 the unrestricted multiple 'omics data for each cancer tissue in The Cancer Genome Atlas 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 multiomics data and enhances data science applications of multiple omics datasets. Cancer Res; 77(21); e39-42. ©2017 AACR.

References

Jan 14, 2011·Bioinformatics·Riku Louhimo, Sampsa Hautaniemi
Aug 21, 2013·PLoS Computational Biology·Michael LawrenceVincent J Carey
Jan 31, 2015·Nature Methods·Wolfgang HuberMartin Morgan
Oct 16, 2015·Briefings in Bioinformatics·Lavanya KannanLevi Waldron
Jan 18, 2017·BMC Bioinformatics·Carles Hernandez-FerrerJuan R González

❮ Previous
Next ❯

Citations

Jul 15, 2018·Journal of Molecular Endocrinology·Biswapriya B MisraLaura A Cox
Jan 29, 2019·American Journal of Epidemiology·Levi WaldronNicola Segata
May 16, 2019·Metabolomics : Official Journal of the Metabolomic Society·Andreas MockChristel Herold-Mende
Jun 20, 2020·Scientific Reports·Akito IshikawaKazuyoshi Endo
Jun 16, 2019·Scientific Data·Mira PavkovicVishal S Vaidya
Apr 23, 2020·Frontiers in Oncology·Guillermo de Anda-Jáuregui, Enrique Hernández-Lemus
Oct 30, 2020·JCO Clinical Cancer Informatics·Marcel RamosLevi Waldron
Jan 17, 2021·Scientific Reports·Mario ZanfardinoMonica Franzese
Mar 15, 2021·Bioinformatics·Irzam SarfrazJoshua D Campbell
Mar 23, 2021·Frontiers in Genetics·Nuria PlanellDavid Gomez-Cabrero
Mar 30, 2021·Microbiome·Yue ZhaoW Evan Johnson
Jun 3, 2021·International Journal of Molecular Sciences·Francesco PettiniOttavia Spiga
Oct 6, 2021·Nature Communications·Anthony MammolitiBenjamin Haibe-Kains

❮ Previous
Next ❯

Related Concepts

Related Feeds

CZI Human Cell Atlas Seed Network

The aim of the Human Cell Atlas (HCA) is to build reference maps of all human cells in order to enhance our understanding of health and disease. The Seed Networks for the HCA project aims to bring together collaborators with different areas of expertise in order to facilitate the development of the HCA. Find the latest research from members of the HCA Seed Networks here.

Cancer Genomics (Keystone)

Cancer genomics approaches employ high-throughput technologies to identify the complete catalog of somatic alterations that characterize the genome, transcriptome and epigenome of cohorts of tumor samples. Discover the latest research using such technologies in this feed.