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


Journal

Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944

Informations de publication

Date de publication:
01 08 2023
Historique:
received: 30 04 2023
revised: 15 08 2023
accepted: 21 08 2023
medline: 5 9 2023
pubmed: 22 8 2023
entrez: 22 8 2023
Statut: ppublish

Résumé

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. 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/).

Identifiants

pubmed: 37607004
pii: 7247532
doi: 10.1093/bioinformatics/btad518
pmc: PMC10471896
pii:
doi:

Types de publication

Journal Article Review Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2023. Published by Oxford University Press.

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Auteurs

Jacob I Marsh (JI)

Centre for Applied Bioinformatics, University of Western Australia, Perth WA, 6009, Australia.
School of Biological Sciences, University of Western Australia, Perth WA, 6009, Australia.

Jakob Petereit (J)

Centre for Applied Bioinformatics, University of Western Australia, Perth WA, 6009, Australia.
School of Biological Sciences, University of Western Australia, Perth WA, 6009, Australia.

Brady A Johnston (BA)

School of Molecular Sciences, University of Western Australia, Perth WA, 6009, Australia.

Philipp E Bayer (PE)

Centre for Applied Bioinformatics, University of Western Australia, Perth WA, 6009, Australia.
School of Biological Sciences, University of Western Australia, Perth WA, 6009, Australia.

Cassandria G Tay Fernandez (CG)

Centre for Applied Bioinformatics, University of Western Australia, Perth WA, 6009, Australia.
School of Biological Sciences, University of Western Australia, Perth WA, 6009, Australia.

Hawlader A Al-Mamun (HA)

Centre for Applied Bioinformatics, University of Western Australia, Perth WA, 6009, Australia.
School of Biological Sciences, University of Western Australia, Perth WA, 6009, Australia.

Jacqueline Batley (J)

Centre for Applied Bioinformatics, University of Western Australia, Perth WA, 6009, Australia.
School of Biological Sciences, University of Western Australia, Perth WA, 6009, Australia.

David Edwards (D)

Centre for Applied Bioinformatics, University of Western Australia, Perth WA, 6009, Australia.
School of Biological Sciences, University of Western Australia, Perth WA, 6009, Australia.

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Classifications MeSH