lmms: Linear Mixed Effect Model Splines for Modelling and Analysis of Time Course Data

Linear Mixed effect Model Splines ('lmms') implements linear mixed effect model splines for modelling and differential expression for highly dimensional data sets: investNoise() for quality control and filterNoise() for removing non-informative trajectories; lmmSpline() to model time course expression profiles and lmmsDE() performs differential expression analysis to identify differential expression between groups, time and/or group x time interaction.

Version: 1.3.3
Depends: R (≥ 3.0.0), ggplot2
Imports: stats, methods, nlme, lmeSplines, parallel, reshape2, gdata, gplots, gridExtra
Published: 2016-03-07
Author: Jasmin Straube [aut, cre], Kim-Anh Le Cao [aut], Emma Huang [aut], Dominique Gorse [ctb]
Maintainer: Jasmin Straube <j.straube at qfab.org>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: lmms results


Reference manual: lmms.pdf
Package source: lmms_1.3.3.tar.gz
Windows binaries: r-devel: lmms_1.3.3.zip, r-release: lmms_1.3.3.zip, r-oldrel: lmms_1.3.3.zip
OS X binaries: r-release: lmms_1.3.3.tgz, r-oldrel: lmms_1.3.3.tgz
Old sources: lmms archive

Reverse dependencies:

Reverse suggests: dynOmics


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