epoc: Endogenous Perturbation Analysis of Cancer

Estimates sparse matrices A or G using fast lasso regression from mRNA transcript levels Y and CNA profiles U. Two models are provided, EPoC A where AY + U + R = 0 and EPoC G where Y = GU + E, the matrices R and E are so far treated as noise. For details see the manual page of 'lassoshooting' and the article Rebecka Jörnsten, Tobias Abenius, Teresia Kling, Linnéa Schmidt, Erik Johansson, Torbjörn E M Nordling, Bodil Nordlander, Chris Sander, Peter Gennemark, Keiko Funa, Björn Nilsson, Linda Lindahl, Sven Nelander (2011) <doi:10.1038/msb.2011.17>.

Version: 0.2.6-1.1
Depends: R (≥ 2.12.0), lassoshooting (≥ 0.1.4), Matrix, methods
Imports: irr, elasticnet, survival
Suggests: graph
Published: 2019-08-26
Author: Rebecka Jornsten, Tobias Abenius, Sven Nelander
Maintainer: Tobias Abenius <Tobias.Abenius at Chalmers.se>
License: LGPL-3
NeedsCompilation: no
Materials: ChangeLog
CRAN checks: epoc results

Documentation:

Reference manual: epoc.pdf

Downloads:

Package source: epoc_0.2.6-1.1.tar.gz
Windows binaries: r-devel: epoc_0.2.6-1.1.zip, r-release: epoc_0.2.6-1.1.zip, r-oldrel: epoc_0.2.6-1.1.zip
macOS binaries: r-release (arm64): epoc_0.2.6-1.1.tgz, r-oldrel (arm64): epoc_0.2.6-1.1.tgz, r-release (x86_64): epoc_0.2.6-1.1.tgz
Old sources: epoc archive

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