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Bioinformatics
Article . 2016 . Peer-reviewed
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Bioinformatics
Article
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Bioinformatics
Article . 2017
DBLP
Article . 2020
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R.JIVE for exploration of multi-source molecular data

Authors: Michael J. O'Connell; Eric F. Lock;

R.JIVE for exploration of multi-source molecular data

Abstract

AbstractSummary: 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.Availability and Implementation: R.JIVE is available via the Comprehensive R Archive Network (CRAN) under the GPLv3 license: https://cran.r-project.org/web/packages/r.jive/.Contact: elock@umn.eduSupplementary information: Supplementary data are available at Bioinformatics online.

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Keywords

Electronic Data Processing, Neoplasms, Computational Biology, Humans, Metabolomics, Algorithms, Software

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
62
Top 1%
Top 10%
Top 10%
gold