Compute differential causal effects (dce) on (biological) networks. Given observational samples from a control experiment and noncontrol (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 noncontrol 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.
Package details 


Bioconductor views  DifferentialExpression GeneExpression GraphAndNetwork KEGG Network NetworkEnrichment Regression Software StatisticalMethod 
Maintainer  
License  GPL3 
Version  1.3.5 
URL  https://github.com/cbgethz/dce 
Package repository  View on GitHub 
Installation 
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