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.

Install the latest version of this package by entering the following in R:
AuthorJasmin Straube [aut, cre], Kim-Anh Le Cao [aut], Emma Huang [aut], Dominique Gorse [ctb]
Date of publication2016-03-07 01:09:11
MaintainerJasmin Straube <j.straube@qfab.org>
LicenseGPL (>= 2)

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deriv.lmmspline Man page
filterNoise Man page
filterNoise,matrixOrframe,noise,missingOrnumeric,missingOrnumeri Man page
investNoise Man page
kidneySimTimeGroup Man page
lmms Man page
lmms-class Man page
lmmsDE Man page
lmmsde-class Man page
lmms-package Man page
lmmSpline Man page
lmmspline-class Man page
noise-class Man page
plot.lmmsde Man page
plot.lmmspline Man page
plot.noise Man page
predict.lmmspline Man page
summary.lmmsde Man page
summary.lmmspline Man page
summary.noise Man page

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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