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Algorithm for the Automated Evaluation of NAT2 Genotypes.

Georg Michael¹, Ricarda Thier^2,3, Meinolf Blaszkewicz²

¹, Waldstrasse 51, 79585, Steinen, Germany. georg_michael@arcor.de.

Methods in Molecular Biology (Clifton, N.J.)

|September 11, 2017

Summary

Genotyping the N-Acetyltransferase 2 (NAT2) gene provides unphased results. A new program processes these results to determine all possible NAT2 haplotype pairs, crucial for predicting NAT2 phenotype.

Keywords:

Alleles Automated evaluation Computer program Genotyping Haplotype N-Acetyltransferase 2

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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

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Published on: April 4, 2018

Area of Science:

Pharmacogenomics
Molecular Biology
Computational Biology

Background:

N-Acetyltransferase 2 (NAT2) genotyping is essential for predicting drug metabolism.
Current PCR and RFLP methods yield unphased single nucleotide polymorphism (SNP) data.
Determining NAT2 haplotypes from unphased genotypes is computationally challenging.

Purpose of the Study:

To describe a procedure for NAT2 genotyping.
To present a Microsoft Access-based program for haplotype determination.
To facilitate accurate NAT2 phenotype prediction.

Main Methods:

Utilized Polymerase Chain Reaction (PCR) and Restriction Fragment Length Polymorphism (RFLP) for NAT2 genotyping.
Developed a computational program using Microsoft Access to process unphased SNP data.
Implemented algorithms to generate all possible NAT2 haplotype combinations.

Main Results:

The developed program successfully generates all potential NAT2 haplotype pairs from unphased genotypes.
The procedure allows for comprehensive analysis of NAT2 genetic variations.
Automated haplotype pair generation simplifies data processing.

Conclusions:

Accurate NAT2 haplotype determination is critical for predicting individual drug responses.
The presented software provides an efficient tool for researchers in pharmacogenomics.
This method enhances the utility of NAT2 genotyping for clinical applications.