Description
Pathway Testing for Longitudinal Omics.
Description
A self-contained hypothesis is tested for a given pathway of longitudinal omics. 'SlaPMEG' is a two-step procedure. First, a shared latent process mixed model is fitted over the longitudinal measures of omics in a pathway. This shared model allows deviation from the shared process at subject level (a random intercept, slope, or both per subject) and also at omic level (a random effect per omic). These random effects summarize the longitudinal trend of the observations which can be used to test for group differences using 'Globaltest' in the second step. If the pathway is large or the shared effect is small, the package fits a series of pairwise models and estimates the shared random effects based on them.
README.md
SlaPMEG
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-setmultslapmeg
fits slapmeg simultaneously for several feature-setspairslapmeg
fits slapmeg based on a computationally efficient approachplotslapmeg
Plots the estimated random effects within the pathway print.slapmeg
Prints the slapmeg model and results with detailssummary.slapmeg
Prints the slapmeg model and results simslapmeg
Generates joint lingitudinal observations
Usage
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.