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R.JIVE for exploration of multi-source molecular data

2016; Oxford University Press; Volume: 32; Issue: 18 Linguagem: Inglês

10.1093/bioinformatics/btw324

1367-4811

Michael J. O’Connell, Eric F. Lock,

Statistical Methods and Inference

: 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.eduSupplementary data are available at Bioinformatics online.