lmms-package | Data-driven mixed effect model splines fit and differential expression analysis |
deriv.lmmspline | Derivative information for 'lmmspline' objects |
filterNoise | Filter non-informative trajectories |
filterNoise-method | Filter non-informative trajectories |
investNoise | Quality control for time course profiles |
investNoise-method | Quality control for time course profiles |
kidneySimTimeGroup | Kidney Simulation Data |
lmms | Data-driven mixed effect model splines fit and differential expression analysis |
lmms-class | 'lmms' class a S4 superclass to extend 'lmmspline' and 'lmmsde' class. |
lmmsDE | Differential expression analysis using linear mixed effect model splines. |
lmmsde-class | 'lmmsde' class a S4 class that extends 'lmms' class. |
lmmSpline | Data-driven linear mixed effect model spline modelling |
lmmSpline,matrixOrFrame,numeric,factorOrcharacterOrnumeric, | Data-driven linear mixed effect model spline modelling |
lmmspline-class | 'lmmspline' class a S4 class that extends 'lmms' class. |
lmmSpline-method | Data-driven linear mixed effect model spline modelling |
missingOrlogical-method | 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 |