Haplo2D6: a web-based tool for automated CYP2D6 haplotype and phenotype inference

Area of Science:

• Pharmacogenomics
• Computational Biology

Background:

• The CYP2D6 gene is crucial for drug metabolism, but interpreting its complex genotype data into actionable phenotypes is challenging.
• Manual interpretation of CYP2D6 genotypes is prone to errors and lacks standardization, hindering clinical application.

Purpose of the Study:

• To develop and present Haplo2D6, a free, browser-based tool for automated CYP2D6 genotype to metabolizer phenotype translation.
• To improve the accuracy, reproducibility, and efficiency of CYP2D6 phenotype prediction.

Main Methods:

• Haplo2D6 utilizes the PHASE algorithm for haplotype reconstruction.
• It integrates copy number variation estimates and incorporates curated definitions from ClinPGx and PharmVar.
• The tool assigns star alleles, accounts for gene deletions/duplications, calculates activity scores (AS), and predicts phenotype.

Main Results:

• Haplo2D6 automates the translation of CYP2D6 genotype data into metabolizer phenotypes.
• The tool provides a standardized, high-throughput approach, improving reproducibility and reducing interpretation errors.
• It generates downloadable, human-readable results and requires no installation.

Conclusions:

• Haplo2D6 offers a robust and user-friendly solution for CYP2D6 phenotype prediction.
• The tool facilitates clinical pharmacogenomics by simplifying genotype interpretation.
• Its accessibility and automated nature support broader adoption in research and clinical settings.