NetReg: Network-regularized linear models for biological association studies
dc.contributor.author
Dirmeier, Simon
dc.contributor.author
Fuchs, Christiane
dc.contributor.author
Müller, Nikola S.
dc.contributor.author
Theis, Fabian J.
dc.date.accessioned
2018-03-28T12:59:24Z
dc.date.available
2018-03-15T04:00:54Z
dc.date.available
2018-03-28T12:59:24Z
dc.date.issued
2018-03
dc.identifier.issn
1367-4803
dc.identifier.issn
1460-2059
dc.identifier.other
10.1093/bioinformatics/btx677
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/250054
dc.identifier.doi
10.3929/ethz-b-000250054
dc.description.abstract
Summary: Modelling biological associations or dependencies using linear regression is often complicated when the analyzed data-sets are high-dimensional and less observations than variables
are available (n p). For genomic data-sets penalized regression methods have been applied settling
this issue. Recently proposed regression models utilize prior knowledge on dependencies,
e.g. in the form of graphs, arguing that this information will lead to more reliable estimates for regression coefficients. However, none of the proposed models for multivariate genomic response
variables have been implemented as a computationally efficient, freely available library. In this
paper we propose netReg, a package for graph-penalized regression models that use large networks
and thousands of variables. netReg incorporates a priori generated biological graph information
into linear models yielding sparse or smooth solutions for regression coefficients.
Availability and implementation: netReg is implemented as both R-package and Cþþ commandline
tool. The main computations are done in Cþþ, where we use Armadillo for fast matrix calculations
and Dlib for optimization. The R package is freely available on Bioconductor https://bioconductor.org/
packages/netReg. The command line tool can be installed using the conda channel Bioconda.
Installation details, issue reports, development versions, documentation and tutorials for the R and
Cþþ versions and the R package vignette can be found on GitHub https://dirmeier.github.io/netReg/.
The GitHub page also contains code for benchmarking and example datasets used in this paper.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Oxford University Press
dc.rights.uri
http://creativecommons.org/licenses/by-nc/4.0/
dc.title
NetReg: Network-regularized linear models for biological association studies
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution-NonCommercial 4.0 International
dc.date.published
2017-10-25
ethz.journal.title
Bioinformatics
ethz.journal.volume
34
en_US
ethz.journal.issue
5
en_US
ethz.journal.abbreviated
Bioinformatics
ethz.pages.start
896
en_US
ethz.pages.end
898
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Oxford
ethz.publication.status
published
en_US
ethz.date.deposited
2018-03-15T04:00:56Z
ethz.source
SCOPUS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2018-03-28T12:59:28Z
ethz.rosetta.lastUpdated
2024-02-02T04:18:22Z
ethz.rosetta.versionExported
true
ethz.COinS
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