{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T22:25:36Z","timestamp":1767997536706,"version":"3.49.0"},"reference-count":7,"publisher":"Oxford University Press (OUP)","issue":"19","license":[{"start":{"date-parts":[[2016,10,26]],"date-time":"2016-10-26T00:00:00Z","timestamp":1477440000000},"content-version":"vor","delay-in-days":81,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,10,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Summary: Determination of haplotypes is important for modelling the phenotypic consequences of genetic variation in diploid organisms, including cis-regulatory control and compound heterozygosity. We realized that single-cell RNA-seq (scRNA-seq) data are well suited for phasing genetic variants, since both transcriptional bursts and technical bottlenecks cause pronounced allelic fluctuations in individual single cells. Here we present scphaser, an R package that phases alleles at heterozygous variants to reconstruct haplotypes within transcribed regions of the genome using scRNA-seq data. The devised method efficiently and accurately reconstructed the known haplotype for\u2009\u226593% of phasable genes in both human and mouse. It also enables phasing of rare and de novo variants and variants far apart within genes, which is hard to attain with population-based computational inference.<\/jats:p>\n               <jats:p>Availability and Implementation: scphaser is implemented as an R package. Tutorial and code are available at https:\/\/github.com\/edsgard\/scphaser<\/jats:p>\n               <jats:p>Contact: \u00a0rickard.sandberg@ki.se<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btw484","type":"journal-article","created":{"date-parts":[[2016,8,7]],"date-time":"2016-08-07T00:18:02Z","timestamp":1470529082000},"page":"3038-3040","source":"Crossref","is-referenced-by-count":19,"title":["scphaser: haplotype inference using single-cell RNA-seq data"],"prefix":"10.1093","volume":"32","author":[{"given":"Daniel","family":"Edsg\u00e4rd","sequence":"first","affiliation":[{"name":"1 Department of Cell and Molecular Biology, Karolinska Institutet, 171 77 Stockholm, Sweden"}]},{"given":"Bj\u00f6rn","family":"Reinius","sequence":"additional","affiliation":[{"name":"1 Department of Cell and Molecular Biology, Karolinska Institutet, 171 77 Stockholm, Sweden"}]},{"given":"Rickard","family":"Sandberg","sequence":"additional","affiliation":[{"name":"1 Department of Cell and Molecular Biology, Karolinska Institutet, 171 77 Stockholm, Sweden"},{"name":"2 Ludwig Institute for Cancer Research, Box 240, 171 77 Stockholm, Sweden"}]}],"member":"286","published-online":{"date-parts":[[2016,8,6]]},"reference":[{"key":"2023020113451633900_btw484-B1","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.ajhg.2014.12.001","article-title":"Biased allelic expression in human primary fibroblast single cells","volume":"96","author":"Borel","year":"2015","journal-title":"Am. J. Hum. Genet"},{"key":"2023020113451633900_btw484-B2","doi-asserted-by":"crossref","first-page":"703","DOI":"10.1038\/nrg3054","article-title":"Haplotype phasing: existing methods and new developments","volume":"12","author":"Browning","year":"2011","journal-title":"Nat. Rev. Genet"},{"key":"2023020113451633900_btw484-B3","doi-asserted-by":"crossref","first-page":"206","DOI":"10.1038\/ng.3467","article-title":"Fine-mapping cellular QTLs with RASQUAL and ATAC-seq","volume":"48","author":"Kumasaka","year":"2016","journal-title":"Nat. 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Methods"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/32\/19\/3038\/49021145\/bioinformatics_32_19_3038.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/32\/19\/3038\/49021145\/bioinformatics_32_19_3038.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,1]],"date-time":"2023-02-01T23:49:57Z","timestamp":1675295397000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/32\/19\/3038\/2196642"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,8,6]]},"references-count":7,"journal-issue":{"issue":"19","published-print":{"date-parts":[[2016,10,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btw484","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2016,10,1]]},"published":{"date-parts":[[2016,8,6]]}}}