{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Browning SR"],"funding":["NHGRI NIH HHS","National Institutes of Health","National Human Genome Research Institute"],"pagination":["326-335"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9943733"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["110(2)"],"pubmed_abstract":["Local ancestry is the source ancestry at each point in the genome of an admixed individual. Inferred local ancestry is used for admixture mapping and population genetic analyses. We present FLARE (fast local ancestry estimation), a method for local ancestry inference. FLARE achieves high accuracy through the use of an extended Li and Stephens model, and it achieves exceptional computational performance through incorporation of computational techniques developed for genotype imputation. Memory requirements are reduced through on-the-fly compression of reference haplotypes and stored checkpoints. Computation time is reduced through the use of composite reference haplotypes. These techniques allow FLARE to scale to datasets with hundreds of thousands of sequenced individuals and to provide superior accuracy on large-scale data. FLARE is open source and available at https://github.com/browning-lab/flare."],"journal":["American journal of human genetics"],"pubmed_title":["Fast, accurate local ancestry inference with FLARE."],"pmcid":["PMC9943733"],"funding_grant_id":["R01 HG008359","HG008359","HG010869","R01 HG010869"],"pubmed_authors":["Browning BL","Waples RK","Browning SR"],"additional_accession":[]},"is_claimable":false,"name":"Fast, accurate local ancestry inference with FLARE.","description":"Local ancestry is the source ancestry at each point in the genome of an admixed individual. Inferred local ancestry is used for admixture mapping and population genetic analyses. We present FLARE (fast local ancestry estimation), a method for local ancestry inference. FLARE achieves high accuracy through the use of an extended Li and Stephens model, and it achieves exceptional computational performance through incorporation of computational techniques developed for genotype imputation. Memory requirements are reduced through on-the-fly compression of reference haplotypes and stored checkpoints. Computation time is reduced through the use of composite reference haplotypes. These techniques allow FLARE to scale to datasets with hundreds of thousands of sequenced individuals and to provide superior accuracy on large-scale data. FLARE is open source and available at https://github.com/browning-lab/flare.","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 Feb","modification":"2025-04-04T20:33:22.268Z","creation":"2025-04-04T20:33:22.268Z"},"accession":"S-EPMC9943733","cross_references":{"pubmed":["36610402"],"doi":["10.1101/2022.08.02.502540","10.1016/j.ajhg.2022.12.010"]}}