ArticleNature communications2021
Rapid detection of identity-by-descent tracts for mega-scale datasets.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 1 of them a synthesis that pooled it.
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Who cites it
39 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Fully exploiting SNP arrays: a systematic review on the tools to extract underlying genomic structure.Briefings in bioinformatics · 2022Pooled it
- DRIVE v3: Command Line Application for Identity-by-Descent Haplotype Clustering in Large Biobank Scale Data.Genetic epidemiology · 2026Article
- HiFiMAP: High-resolution fast identity-by-descent mapping test.medRxiv : the preprint server for health sciences · 2026Article
- Article
- A spectral component approach leveraging identity-by-descent graphs to address recent population structure in genomic analysis.Genome research · 2026Article
- Topological stratification of continuous genetic variation in large biobanks.PLoS genetics · 2026Article
- Leveraging ancestral recombination graphs for scalable mixed-model analysis of complex traits.Cell genomics · 2026Article
- RaPID2: a parallel scalable framework for identity-by-descent segment detection via parallel PBWT.Bioinformatics advances · 2026Article
- COMPADRE: Combined pedigree-aware distant relatedness estimation for improved pedigree reconstruction.American journal of human genetics · 2025Article
- Identity-by-descent segments in large samples.Theoretical population biology · 2025Article
- SPC: a SPectral Component approach leveraging Identity-by-Descent graphs to address recent population structure in genomic analysis.medRxiv : the preprint server for health sciences · 2025Article
- Benchmarking and optimization of methods for the detection of identity-by-descent in high-recombiningeLife · 2025Article
- Fast simulation of identity-by-descent segments.Bulletin of mathematical biology · 2025Article
- Characterizing substructure via mixture modeling in large-scale genetic summary statistics.American journal of human genetics · 2025Article
- Fast simulation of identity-by-descent segments.bioRxiv : the preprint server for biology · 2025Article
- Modeling recent positive selection using identity-by-descent segments.American journal of human genetics · 2024Article
- Secure discovery of genetic relatives across large-scale and distributed genomic data sets.Genome research · 2024Article
- Detection of distant relatedness in biobanks to identify undiagnosed cases of Mendelian disease as applied to Long QT syndrome.Nature communications · 2024Article
- Characterizing substructure via mixture modeling in large-scale genetic summary statistics.bioRxiv : the preprint server for biology · 2024Article
- Biobank-scale inference of multi-individual identity by descent and gene conversion.American journal of human genetics · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.