Variable-length haplotype construction for gene-gene interaction studies

TL;DR

This paper introduces VarHAP, a non-parametric method for constructing variable-length haplotypes to identify gene-gene interactions associated with disease susceptibility, outperforming existing techniques in various linkage disequilibrium scenarios.

Contribution

The paper presents a novel variable-length haplotype construction technique, VarHAP, that improves detection of gene-gene interactions in disease studies over existing methods.

Findings

VarHAP performs well across different linkage disequilibrium levels.

It outperforms MDR and FAMHAP in two-locus interaction problems.

Suitable for weak and strong linkage disequilibrium scenarios.

Abstract

This paper presents a non-parametric classification technique for identifying a candidate bi-allelic genetic marker set that best describes disease susceptibility in gene-gene interaction studies. The developed technique functions by creating a mapping between inferred haplotypes and case/control status. The technique cycles through all possible marker combination models generated from the available marker set where the best interaction model is determined from prediction accuracy and two auxiliary criteria including low-to-high order haplotype propagation capability and model parsimony. Since variable-length haplotypes are created during the best model identification, the developed technique is referred to as a variable-length haplotype construction for gene-gene interaction (VarHAP) technique. VarHAP has been benchmarked against a multifactor dimensionality reduction (MDR) program and a haplotype interaction technique embedded in a FAMHAP program in various two-locus interaction problems. The results reveal that VarHAP is suitable for all interaction situations with the presence of weak and strong linkage disequilibrium among genetic markers.