Differential expression analysis using linear mixed effect model splines.
Description
Function to fit a linear mixed effect model splines to perform differential expression analysis. The lmmsDE
function fits LMM models with either a cubic
, pspline
or cubic pspline
basis and compares the models to the null models. The type of basis to use is specified with the basis
argument.
Usage
1 2 
Arguments
data 

time 

sampleID 

group 

type 

experiment 

basis 

knots 
can take an integer value corresponding to the number of knots for the chosen basis or by default calculated as in Ruppert 2002. Not in use for the 'cubic' smoothing spline basis. 
keepModels 
alternative 
numCores 
alternative 
Details
lmmsDE extends the LMMS modelling framework to permit tests between groups, across time, and for interactions between the two implemented as described in Straube et al. 2015.
Value
lmmsDE returns an object of class lmmsde
containing the following components:
DE 

modelsUsed 

predTime 

predGroup 

predTime 

predTimeGroup 

modelTime 
a 
modelGroup 
a 
modelTimeGroup 
a 
type 
an object of class 
experiment 
an object of class 
References
Durban, M., Harezlak, J., Wand, M. P., & Carroll, R. J. (2005). Simple fitting of subjectspecific curves for longitudinal data. Stat. Med., 24(8), 115367.
Ruppert, D. (2002). Selecting the number of knots for penalized splines. J. Comp. Graph. Stat. 11, 735757
Verbyla, A. P., Cullis, B. R., & Kenward, M. G. (1999). The analysis of designed experiments and longitudinal data by using smoothing splines. Appl.Statist, 18(3), 269311.
Straube J., Gorse A.D., Huang B.E., & Le Cao K.A. (2015). A linear mixed model spline framework for analyzing time course 'omics' data PLOSONE, 10(8), e0134540.
See Also
summary.lmmsde
, plot.lmmsde
Examples
1 2 3 4 5 6  ## Not run:
data(kidneySimTimeGroup)
lmmsDEtest <lmmsDE(data=kidneySimTimeGroup$data,time=kidneySimTimeGroup$time,
sampleID=kidneySimTimeGroup$sampleID,group=kidneySimTimeGroup$group)
summary(lmmsDEtest)
## End(Not run)

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