DRIVE v3: Command Line Application for Identity-by-Descent Haplotype Clustering in Large Biobank Scale Data

Area of Science:

• Genetics and Genomics
• Computational Biology
• Bioinformatics

Background:

• Existing genetic analytical methods often separate identity-by-descent (IBD) sharing identification from phenotype association testing.
• There is a need for integrated tools that can discover novel shared haplotypes contributing to disease traits by combining IBD and phenotypic enrichment.
• Current tools require separate analyses for IBD detection and subsequent interpretation, limiting efficiency in large-scale genetic studies.

Purpose of the Study:

• To introduce Distant Relatedness for Identification and Variant Evaluation (DRIVE) v3, a novel python command-line interface tool.
• To enable the identification of participant networks sharing identical haplotypes and to estimate trait enrichment within these networks.
• To demonstrate the utility and performance improvements of DRIVE v3 in analyzing large-scale genetic data for disease-associated variants.

Main Methods:

• Development of DRIVE v3, a python-based tool for identifying networks of individuals with shared haplotypes at specific genomic locations.
• Integration of phenotypic data to perform enrichment testing for dichotomous traits within identified haplotype-sharing networks.
• Application of DRIVE v3 to analyze genetic data for an autosomal dominant condition (cardiomyopathy) and an autosomal recessive condition (cystic fibrosis).

Main Results:

• DRIVE v3 successfully identifies networks of participants sharing identical haplotypes across genomic locations.
• The tool demonstrates significant performance improvements compared to previous versions, facilitating efficient analysis of large datasets.
• Phenotypic enrichment testing within identified networks provides insights into the association of specific traits with shared haplotypes, as shown in cardiomyopathy and cystic fibrosis cases.

Conclusions:

• DRIVE v3 offers an integrated approach for genetic discovery by combining IBD analysis with phenotypic enrichment.
• The tool's efficient design and versatile API allow for flexible integration into existing bioinformatics pipelines for large-scale genetic resources.
• DRIVE v3 enhances the interpretation of genetic findings by directly linking haplotype sharing networks to specific disease traits.