This package is designed to perform a Shared latent Process Mixed Effects analysis with Globaltest.
Here is a list of functions:
slapmeg
fits slapmeg for a single feature-set
multslapmeg
fits slapmeg simultaneously for several
feature-sets
pairslapmeg
fits slapmeg based on a computationally
efficient approach
plotslapmeg
Plots the estimated random effects within the
pathway
print.slapmeg
Prints the slapmeg model and results with
details
summary.slapmeg
Prints the slapmeg model and results
simslapmeg
Generates joint lingitudinal observations
For details explanations and example usage check the help files
within package, but here are some tips. * The data need to be in the
conventional genomics format, so columns indicate variables and
features, whereas rows indicate subjects and repeated measurements. *
The formula must be supplied as a formula object
. * There
is a function to simulate longitudinal observations, so you can give it
a try if you do not have a real dataset. * It is possible to use
predefined pathways such as GO, KEGG, Wikipathways, and etc. as long as
they are put into a list format, you can take a look at examples of
creating such lists in the “Creating the Pathlists” section of rSEA package manual. * If
the feature-set has more than 10 features, the
slapmeg function
will automatically switch to the
pairslapmeg which is computationally more efficient. * If you had
convergance issues with smaller feature-sets, try the
pairslapmeg function
. * The
plotslapmeg function
will give an insight on the source of
differential expression.