pharmacogenomics

The Pharmacogenomic Clinical Annotation Tool

A Python package for pharmacogenomics (PGx) research

A tool to genotype CYP2D6 with WGS data

PyTorch implementation of bimodal neural networks for drug-cell (pharmarcogenomics) and drug-protein (proteochemometrics) interaction prediction

This repository is the collection point of reference data for the GPCRdb. The GPCRdb contains reference data, interactive visualisation and experiment design tools for G protein-coupled receptors (GPCRs).

Protwis is the backbone of the GPCRdb. The GPCRdb contains reference data, interactive visualisation and experiment design tools for G protein-coupled receptors (GPCRs).

Text mining for pharmacogenomic associations for PharmGKB

A phase-aware pharmacogenomic diplotyper for PacBio datasets

💊🧬 PharMe - Pharmaceutical insights tailored to your personal genome

Velodrome combines semi-supervised learning and out-of-distribution generalization (domain generalization) for drug response prediction and pharmacogenomics

rvDNA — AI-native genomic analysis in pure Rust + WASM: biomarker risk scoring, 23andMe genotyping, CYP2D6/CYP2C19 pharmacogenomics, variant calling, protein prediction, epigenomics, and HNSW vector search.

A clinical decision-support system to identify pharmacogenomics profiles based on subjects genotype of five core genes. The paper has been published in the Journal of Personalized Medicine.

PGxCorpus, a manually annotated corpus, designed for the extraction of pharmacogenomic relations from text.

Whole genome sequencing analysis pipeline for consumer hardware. 100% local, Docker-powered, free and open source.

Local-first DNA and VCF analysis copilot for evidence-bound genomics workflows, confidence tiers, and Claude/Codex support.

DWFA consensus algorithm for pb-StarPhase

R scripts included in a bioinformatics pipeline for differential PGx analysis of cancer drug response

Clinical VCF variant annotation platform integrating Ensembl VEP, ClinVar, 3D PDB structural mapping, pharmacogenomics (PGx), and precision oncology clinical trials.

AI-powered pharmacogenomic risk prediction system. Analyzes patient VCF files across 6 genes (CYP2D6, CYP2C19, CYP2C9, SLCO1B1, TPMT, DPYD) to predict drug-specific risks with CPIC-aligned recommendations and Gemini AI explanations.