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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 |
| Reference manual: | epoc.pdf |
| 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, r-oldrel (x86_64): epoc_0.2.6-1.1.tgz |
| Old sources: | epoc archive |
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