Integrative Pathway Enrichment Analysis of Multivariate Omics Data
ActivePathways
Merge p-values using the Brown's method.
Determine which terms are found to be significant using each column in...
Merge p-values using the DPM method.
Perform pathway enrichment analysis on an ordered list of genes
Export the results from ActivePathways as a comma-separated values (CS...
Read and Write GMT files
Hypergeometric test
Make a background list of genes (i.e., the statistical universe) based...
Merge a list or matrix of p-values
Ordered Hypergeometric Test
Prepare files for building an enrichment map network visualization in ...
Framework for analysing multiple omics datasets in the context of molecular pathways, biological processes and other types of gene sets. The package uses p-value merging to combine gene- or protein-level signals, followed by ranked hypergeometric tests to determine enriched pathways and processes. Genes can be integrated using directional constraints that reflect how the input datasets are expected interact with one another. This approach allows researchers to interpret a series of omics datasets in the context of known biology and gene function, and discover associations that are only apparent when several datasets are combined. The recent version of the package is part of the following publication: Directional integration and pathway enrichment analysis for multi-omics data. Slobodyanyuk M^, Bahcheli AT^, Klein ZP, Bayati M, Strug LJ, Reimand J. Nature Communications (2024) <doi:10.1038/s41467-024-49986-4>.