lmms-package: Data-driven mixed effect model splines fit and differential...
In lmms: Linear Mixed Effect Model Splines for Modelling and Analysis of Time Course Data
Description
The package provides quality control and filtering methods as well as linear mixed effect model splines techniques for modelling and differential expression analysis to model and mine highly dimensional data sets: investNoise to identify noisy profiles and filterNoise to remove them; lmmSpline to model heterogeneous time course expression profiles; lmmsDE to perform differential expression analysis of time course data to identify differential expression over time, between groups or time and group interaction.
Details
Package: lmms
Type: Package
Version: 1.3.3
Date: 2016-03-04
License: GPL-2
LazyLoad: yes
Functions for quality control and filtering: investNoise, filterNoise,summary.noise,plot.noise
Functions for data modelling: lmmSpline, lmmsDE,deriv.lmmspline,predict.lmmspline
Functions for summarization: summary.lmmspline, summary.lmmsde
Functions for plots: plot.lmmspline, plot.lmmsde
Author(s)
Jasmin Straube with contributions from Kim-Anh Le Cao, Emma Huang and Dominique Gorse
Maintainer: Jasmin Straube <j.straube@qfab.org>
lmms documentation built on May 2, 2019, 6:53 a.m.
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Description
The package provides quality control and filtering methods as well as linear mixed effect model splines techniques for modelling and differential expression analysis to model and mine highly dimensional data sets: investNoise to identify noisy profiles and filterNoise to remove them; lmmSpline to model heterogeneous time course expression profiles; lmmsDE to perform differential expression analysis of time course data to identify differential expression over time, between groups or time and group interaction.
Details
| Package: | lmms |
| Type: | Package |
| Version: | 1.3.3 |
| Date: | 2016-03-04 |
| License: | GPL-2 |
| LazyLoad: | yes |
Functions for quality control and filtering: investNoise, filterNoise,summary.noise,plot.noise
Functions for data modelling: lmmSpline, lmmsDE,deriv.lmmspline,predict.lmmspline
Functions for summarization: summary.lmmspline, summary.lmmsde
Functions for plots: plot.lmmspline, plot.lmmsde
Author(s)
Jasmin Straube with contributions from Kim-Anh Le Cao, Emma Huang and Dominique Gorse
Maintainer: Jasmin Straube <j.straube@qfab.org>
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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