bioRxivBioinformaticsPreprint
Local haplotype visualization for trait association analysis with crosshap
Jacob Ian MarshiD, Jakob PetereitiD, Brady JohnstoniD, Philipp E. BayeriD, Cassandria G. Tay FernandeziD, Hawlader Abdullah Al-MamuniD, Jacqueline BatleyiD, David EdwardsiD
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Abstract
SummaryGWAS 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 ({varepsilon}) before producing an intuitive figure that provides an overview of the complex relationships between linked variants, haplotype combinations, phenotypic traits and metadata. Availability and implementationThe 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/).
- assay: GWAS summary statistics
- research focus: benchmarking
- research focus: software / tool
- approach: statistical model
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