rSEA - Simultaneous Enrichment Analysis

SEA performs simultaneous feature-set testing for (gen)omics data. It tests the unified null hypothesis and controls the family-wise error rate for all possible pathways. The unified null hypothesis is defined as: "The proportion of true features in the set is less than or equal to a threshold." Family-wise error rate control is provided through use of closed testing with Simes test. There are some practical functions to play around with the pathways of interest.

Last updated 6 months ago

3.70 score 10 scripts 521 downloads

rOCEAN - Two-Way Feature Set Testing for Multi-Omics

For any two way feature-set from a pair of pre-processed omics data, pairwise-TDP, Column-TDP and row-TDP are calculated. Due to embeded closed testing procedure, the choice of feature-sets can be changed infinite times and even after seeing the data withuot any change in type I error rate. For more details refer to the refrence article.

Last updated 23 days ago

3.40 score 2 scripts

SlaPMEG - Pathway Testing for Longitudinal Omics

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.

Last updated 1 months ago

2.70 score 1 stars 401 downloads