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

Share:

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.

Author
Jasmin Straube [aut, cre], Kim-Anh Le Cao [aut], Emma Huang [aut], Dominique Gorse [ctb]
Date of publication
2016-03-07 01:09:11
Maintainer
Jasmin Straube <j.straube@qfab.org>
License
GPL (>= 2)
Version
1.3.3

View on CRAN

Man pages

deriv.lmmspline
Derivative information for 'lmmspline' objects
filterNoise-methods
Filter non-informative trajectories
investNoise-methods
Quality control for time course profiles
kidneySimTimeGroup
Kidney Simulation Data
lmms-class
'lmms' class a S4 superclass to extend 'lmmspline' and...
lmmsde-class
'lmmsde' class a S4 class that extends 'lmms' class.
lmmsDE-methods
Differential expression analysis using linear mixed effect...
lmms-package
Data-driven mixed effect model splines fit and differential...
lmmspline-class
'lmmspline' class a S4 class that extends 'lmms' class.
lmmSpline-methods
Data-driven linear mixed effect model spline modelling
noise-class
'noise' S4 class
plot.lmmsde
Plot of 'lmmsde' objects
plot.lmmspline
Plot of 'lmmspline' object
plot.noise
Plot of 'associations' objects
predict.lmmspline
Predicts fitted values of an 'lmmspline' Object
summary.lmmsde
Summary of a 'lmmsde' Object
summary.lmmspline
Summary of a 'lmmspline' Object
summary.noise
Summary of a 'noise' Object

Files in this package

lmms
lmms/NAMESPACE
lmms/data
lmms/data/kidneySimTimeGroup.RData
lmms/data/datalist
lmms/R
lmms/R/AllClasses.R
lmms/R/plot.lmmspline-method.R
lmms/R/investNoise-method.R
lmms/R/lmmSpline-method.R
lmms/R/filterNoise-method.R
lmms/R/summary.lmmspline-methods.R
lmms/R/summary.lmmsde-methods.R
lmms/R/summary.noise-methods.R
lmms/R/predict.lmmspline-method.R
lmms/R/lmmsDE-method.R
lmms/R/plot.noise-method.R
lmms/R/plot.lmmsde-method.R
lmms/R/deriv.lmmspline-method.R
lmms/MD5
lmms/DESCRIPTION
lmms/man
lmms/man/lmms-class.Rd
lmms/man/summary.lmmspline.Rd
lmms/man/noise-class.Rd
lmms/man/investNoise-methods.Rd
lmms/man/lmmSpline-methods.Rd
lmms/man/plot.lmmsde.Rd
lmms/man/deriv.lmmspline.Rd
lmms/man/lmmsde-class.Rd
lmms/man/lmmsDE-methods.Rd
lmms/man/predict.lmmspline.Rd
lmms/man/lmmspline-class.Rd
lmms/man/plot.noise.Rd
lmms/man/summary.lmmsde.Rd
lmms/man/summary.noise.Rd
lmms/man/filterNoise-methods.Rd
lmms/man/lmms-package.Rd
lmms/man/plot.lmmspline.Rd
lmms/man/kidneySimTimeGroup.Rd