R.JIVE for exploration of multi-source molecular data

• Published in: Bioinformatics (Oxford, England) Vol. 32; no. 18; pp. 2877 - 2879
• Main Authors: O'Connell, Michael J, Lock, Eric F
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 15.09.2016
• Subjects: Algorithms; Applications Notes; Automatic Data Processing; Computational Biology - methods; Humans; Metabolomics - methods; Neoplasms; Software
• ISSN: 1367-4803; 1367-4811
• DOI: 10.1093/bioinformatics/btw324

: The integrative analysis of multiple high-throughput data sources that are available for a common sample set is an increasingly common goal in biomedical research. Joint and individual variation explained (JIVE) is a tool for exploratory dimension reduction that decomposes a multi-source dataset into three terms: a low-rank approximation capturing joint variation across sources, low-rank approximations for structured variation individual to each source and residual noise. JIVE has been used to explore multi-source data for a variety of application areas but its accessibility was previously limited. We introduce R.JIVE, an intuitive R package to perform JIVE and visualize the results. We discuss several improvements and extensions of the JIVE methodology that are included. We illustrate the package with an application to multi-source breast tumor data from The Cancer Genome Atlas. R.JIVE is available via the Comprehensive R Archive Network (CRAN) under the GPLv3 license: https://cran.r-project.org/web/packages/r.jive/ elock@umn.edu Supplementary data are available at Bioinformatics online.