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

Jacob I. Marsh, Jakob Petereit, Brady A. Johnston, Philipp E. Bayer, Cassandria G. Tay Fernandez, Hawlader A. Al-Mamun, Jacqueline Batley, David Edwards

Research output: Contribution to journalArticlepeer-review

Abstract

SUMMARY: Genome-wide association studies (GWAS) excels at harnessing dense genomic variant datasets to identify candidate regions responsible for producing a given phenotype. However, GWAS and traditional fine-mapping methods do not provide insight into the complex local landscape of linkage that contains and has been shaped by the causal variant(s). Here, we present crosshap, an R package that performs robust density-based clustering of variants based on their linkage profiles to capture haplotype structures in a local genomic region of interest. Following this, crosshap is equipped with visualization tools for choosing optimal clustering parameters (ɛ) before producing an intuitive figure that provides an overview of the complex relationships between linked variants, haplotype combinations, phenotype, and metadata traits. AVAILABILITY AND IMPLEMENTATION: The crosshap package is freely available under the MIT license and can be downloaded directly from CRAN with R >4.0.0. The development version is available on GitHub alongside issue support (https://github.com/jacobimarsh/crosshap). Tutorial vignettes and documentation are available (https://jacobimarsh.github.io/crosshap/).

Original languageEnglish
Article numberbtad518
JournalBioinformatics (Oxford, England)
Volume39
Issue number8
DOIs
Publication statusPublished - 1 Aug 2023

Cite this