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.


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("lmms")

1.3.3 by Jasmin Straube, 2 years ago


Browse source code at https://github.com/cran/lmms


Authors: Jasmin Straube [aut, cre], Kim-Anh Le Cao [aut], Emma Huang [aut], Dominique Gorse [ctb]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports stats, methods, nlme, lmeSplines, parallel, reshape2, gdata, gplots, gridExtra

Depends on ggplot2


See at CRAN