LocalNgsRelate: a software tool for inferring IBD sharing along the genome between pairs of individuals from low-depth NGS data.


Journal

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

Informations de publication

Date de publication:
27 01 2022
Historique:
received: 22 02 2021
revised: 28 09 2021
accepted: 24 10 2021
pubmed: 1 11 2021
medline: 3 2 2023
entrez: 31 10 2021
Statut: ppublish

Résumé

Inference of identity-by-descent (IBD) sharing along the genome between pairs of individuals has important uses. But all existing inference methods are based on genotypes, which is not ideal for low-depth Next Generation Sequencing (NGS) data from which genotypes can only be called with high uncertainty. We present a new probabilistic software tool, LocalNgsRelate, for inferring IBD sharing along the genome between pairs of individuals from low-depth NGS data. Its inference is based on genotype likelihoods instead of genotypes, and thereby it takes the uncertainty of the genotype calling into account. Using real data from the 1000 Genomes project, we show that LocalNgsRelate provides more accurate IBD inference for low-depth NGS data than two state-of-the-art genotype-based methods, Albrechtsen et al. (2009) and hap-IBD. We also show that the method works well for NGS data down to a depth of 2×. LocalNgsRelate is freely available at https://github.com/idamoltke/LocalNgsRelate. Supplementary data are available at Bioinformatics online.

Identifiants

pubmed: 34718411
pii: 6413625
doi: 10.1093/bioinformatics/btab732
pmc: PMC8796377
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

1159-1161

Subventions

Organisme : NHGRI NIH HHS
ID : R01 HG005855
Pays : United States
Organisme : European Research Council
ID : ERC-2018-STG-804679
Pays : International

Informations de copyright

© The Author(s) 2021. Published by Oxford University Press.

Auteurs

Alissa L Severson (AL)

Department of Genetics, Stanford University, Stanford, CA 94305-5020, USA.

Thorfinn Sand Korneliussen (TS)

GLOBE Institute, University of Copenhagen, 1350 Copenhagen K, Denmark.

Ida Moltke (I)

Department of Biology, University of Copenhagen, 2200 Copenhagen N, Denmark.

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Classifications MeSH