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Rapid Detection of Identity-by-Descent Tracts for Mega-Scale Datasets

Citation

Shemirani, Ruhollah; Belbin, Gillian Morven; Avery, Christy L.; Kenny, Eimear E.; Gignoux, Christopher R.; & Ambite, Jose Luis (Forthcoming). Rapid Detection of Identity-by-Descent Tracts for Mega-Scale Datasets. Nature Communications, 12(1), 3546. PMCID: PMC8192555

Abstract

The ability to identify segments of genomes identical-by-descent (IBD) is a part of standard workflows in both statistical and population genetics. However, traditional methods for finding local IBD across all pairs of individuals scale poorly leading to a lack of adoption in very large-scale datasets. Here, we present iLASH, an algorithm based on similarity detection techniques that shows equal or improved accuracy in simulations compared to current leading methods and speeds up analysis by several orders of magnitude on genomic datasets, making IBD estimation tractable for millions of individuals. We apply iLASH to the PAGE dataset of ~52,000 multi-ethnic participants, including several founder populations with elevated IBD sharing, identifying IBD segments in ~3 minutes per chromosome compared to over 6 days for a state-of-the-art algorithm. iLASH enables efficient analysis of very large-scale datasets, as we demonstrate by computing IBD across the UK Biobank (~500,000 individuals), detecting 12.9 billion pairwise connections.

URL

http://dx.doi.org/10.1038/s41467-021-22910-w

Reference Type

Journal Article

Article Type

Regular

Year Published

Forthcoming

Journal Title

Nature Communications

Author(s)

Shemirani, Ruhollah
Belbin, Gillian Morven
Avery, Christy L.
Kenny, Eimear E.
Gignoux, Christopher R.
Ambite, Jose Luis

PMCID

PMC8192555

Data Set/Study

Population Architecture Using Genomics and Epidemiology (PAGE) Consortium
UK Biobank Study

Continent/Country

United States of America
United Kingdom

State

Nonspecific