cbg-ethz/dce: Pathway Enrichment Based on Differential Causal Effects

Compute differential causal effects (dce) on (biological) networks. Given observational samples from a control experiment and non-control (e.g., cancer) for two genes A and B, we can compute differential causal effects with a (generalized) linear regression. If the causal effect of gene A on gene B in the control samples is different from the causal effect in the non-control samples the dce will differ from zero. We regularize the dce computation by the inclusion of prior network information from pathway databases such as KEGG.

Getting started

Package details

Bioconductor views DifferentialExpression GeneExpression GraphAndNetwork KEGG Network NetworkEnrichment Regression Software StatisticalMethod
Maintainer
LicenseGPL-3
Version0.99.3
URL https://github.com/cbg-ethz/dce
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("cbg-ethz/dce")
cbg-ethz/dce documentation built on April 18, 2021, 9:47 a.m.