My research code is avilable on Github. These include:
- scContextualized provides utilities for contextualized analysis of biological data, scaling to the requirements of large single-cell datasets.
- Contextualized unifies all sorts of context-specific analysis including context-specific regression, context-specific correlation and context-specific networks for analysis of heterogeneous populations.
- EBM_Utils provides utilities functions for Explainable Boosting Machines.
- Interpret (from MSR) is a package for interpretable machine learning. Includes state-of-the-art generalized additive models in Explainable Boosting Machines for both regression and classification.
- Functional Retrofitting is a scalable method to combine distributional and relational data.
- drPCA is a framework for estimating principal components which differentiate sets of case/control samples.
- GO_Translator is a set of simple utility functions for the Gene Ontology terms.