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crosshap: R package for local haplotype visualization for trait association analysis.

Jacob I Marsh1,2, Jakob Petereit1,2, Brady A Johnston3

  • 1Centre for Applied Bioinformatics, University of Western Australia, Perth WA, 6009, Australia.

Bioinformatics (Oxford, England)
|August 22, 2023
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Summary
This summary is machine-generated.

crosshap, an R package, identifies complex haplotype structures and variant relationships using density-based clustering. This tool enhances understanding of genomic regions and their link to phenotypes beyond traditional GWAS methods.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Statistical Genetics

Background:

  • Genome-wide association studies (GWAS) identify candidate regions for phenotypes but lack insight into local linkage disequilibrium.
  • Fine-mapping methods struggle to fully resolve complex haplotype structures shaped by causal variants.

Purpose of the Study:

  • To introduce crosshap, an R package for robust density-based clustering of variants.
  • To capture and visualize complex haplotype structures within local genomic regions.
  • To provide tools for understanding relationships between variants, haplotypes, phenotypes, and metadata.

Main Methods:

  • Utilizes density-based clustering of variants based on linkage profiles.
  • Employs visualization tools for selecting optimal clustering parameters (epsilon).
  • Generates intuitive figures illustrating variant-haplotype-phenotype relationships.

Main Results:

  • Successfully captures complex haplotype structures in local genomic regions.
  • Provides visualization for parameter selection and relationship overview.
  • Offers a novel approach to fine-mapping beyond traditional GWAS.

Conclusions:

  • crosshap enhances the analysis of complex genomic regions by revealing detailed haplotype structures.
  • The package facilitates a deeper understanding of variant contributions to phenotypes.
  • crosshap is a valuable tool for researchers in statistical genetics and bioinformatics.