R.JIVE for exploration of multi-source molecular data.
: 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.
Division of Biostatistics, University of Minnesota, Minneapolis, MN 55455, USA.
Michael J
MJ
O'Connell
Division of Biostatistics, University of Minnesota, Minneapolis, MN 55455, USA.
Eric F
EF
Lock
D000465:Algorithms; D019295:Computational Biology / Q000379:methods; D001330:Electronic Data Processing; D006801:Humans; D055432:Metabolomics / Q000379:methods*; D009369:Neoplasms; D012984:Software