{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T14:09:59Z","timestamp":1775916599965,"version":"3.50.1"},"reference-count":14,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2023,2,16]],"date-time":"2023-02-16T00:00:00Z","timestamp":1676505600000},"content-version":"vor","delay-in-days":15,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Institute of Health","award":["U01AG068880"],"award-info":[{"award-number":["U01AG068880"]}]},{"name":"National Institute of Health","award":["R00HG010909"],"award-info":[{"award-number":["R00HG010909"]}]},{"name":"National Institute of Health","award":["R35GM147004"],"award-info":[{"award-number":["R35GM147004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,2,3]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Motivation<\/jats:title><jats:p>Linkage disequilibrium (LD) matrices derived from large populations are widely used in population genetics in fine-mapping, LD score regression, and linear mixed models for Genome-wide Association Studies (GWAS). However, these matrices can reach large sizes when they are derived from millions of individuals; hence, moving, sharing and extracting granular information from this large amount of data can be cumbersome.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>We sought to address the need for compressing and easily querying large LD matrices by developing LDmat. LDmat is a standalone tool to compress large LD matrices in an HDF5 file format and query these compressed matrices. It can extract submatrices corresponding to a sub-region of the genome, a list of select loci, and loci within a minor allele frequency range. LDmat can also rebuild the original file formats from the compressed files.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>LDmat is implemented in python, and can be installed on Unix systems with the command \u2018pip install ldmat\u2019. It can also be accessed through https:\/\/github.com\/G2Lab\/ldmat and https:\/\/pypi.org\/project\/ldmat\/.<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btad092","type":"journal-article","created":{"date-parts":[[2023,2,16]],"date-time":"2023-02-16T13:45:14Z","timestamp":1676555114000},"source":"Crossref","is-referenced-by-count":4,"title":["LDmat: efficiently queryable compression of linkage disequilibrium matrices"],"prefix":"10.1093","volume":"39","author":[{"given":"Rockwell J","family":"Weiner","sequence":"first","affiliation":[{"name":"Department of Biomedical Informatics, Columbia University , New York, NY 10032, USA"},{"name":"New York Genome Center , New York, NY 10013, USA"},{"name":"Department of Computer Science, Columbia University , New York, NY 10027, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chirag","family":"Lakhani","sequence":"additional","affiliation":[{"name":"New York Genome Center , New York, NY 10013, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7408-146X","authenticated-orcid":false,"given":"David A","family":"Knowles","sequence":"additional","affiliation":[{"name":"New York Genome Center , New York, NY 10013, USA"},{"name":"Department of Computer Science, Columbia University , New York, NY 10027, USA"},{"name":"Department of Systems Biology, Columbia University , New York, NY 10032, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1352-8686","authenticated-orcid":false,"given":"Gamze","family":"G\u00fcrsoy","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, Columbia University , New York, NY 10032, USA"},{"name":"New York Genome Center , New York, NY 10013, USA"},{"name":"Department of Computer Science, Columbia University , New York, NY 10027, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2023,2,16]]},"reference":[{"key":"2023022713392180400_","doi-asserted-by":"crossref","first-page":"539","DOI":"10.1016\/j.ajhg.2017.08.012","article-title":"Prospects of fine-mapping trait-associated genomic regions by using summary statistics from genome-wide association studies","volume":"101","author":"Benner","year":"2017","journal-title":"Am. 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