{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T01:21:30Z","timestamp":1776302490641,"version":"3.50.1"},"reference-count":12,"publisher":"Oxford University Press (OUP)","issue":"12","license":[{"start":{"date-parts":[[2020,4,24]],"date-time":"2020-04-24T00:00:00Z","timestamp":1587686400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,6,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Summary<\/jats:title>\n                    <jats:p>Bulk RNA sequencing studies have demonstrated that human leukocyte antigen (HLA) genes may be expressed in a cell type-specific and allele-specific fashion. Single-cell gene expression assays have the potential to further resolve these expression patterns, but currently available methods do not perform allele-specific quantification at the molecule level. Here, we present scHLAcount, a post-processing workflow for single-cell RNA-seq data that computes allele-specific molecule counts of the HLA genes based on a personalized reference constructed from the sample\u2019s HLA genotypes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>scHLAcount is available under the MIT license at https:\/\/github.com\/10XGenomics\/scHLAcount.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btaa264","type":"journal-article","created":{"date-parts":[[2020,4,17]],"date-time":"2020-04-17T07:13:55Z","timestamp":1587107635000},"page":"3905-3906","source":"Crossref","is-referenced-by-count":29,"title":["scHLAcount: allele-specific HLA expression from single-cell gene expression data"],"prefix":"10.1093","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2195-5300","authenticated-orcid":false,"given":"Charlotte A","family":"Darby","sequence":"first","affiliation":[{"name":"Department of Computer Science , Johns Hopkins University, Baltimore, MD 21218, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5924-3566","authenticated-orcid":false,"given":"Michael J T","family":"Stubbington","sequence":"additional","affiliation":[{"name":"10x\u00a0Genomics , Pleasanton, CA 94588, USA"}]},{"given":"Patrick J","family":"Marks","sequence":"additional","affiliation":[{"name":"10x\u00a0Genomics , Pleasanton, CA 94588, USA"}]},{"given":"\u00c1lvaro","family":"Mart\u00ednez Barrio","sequence":"additional","affiliation":[{"name":"10x\u00a0Genomics , Pleasanton, CA 94588, USA"}]},{"given":"Ian T","family":"Fiddes","sequence":"additional","affiliation":[{"name":"10x\u00a0Genomics , Pleasanton, CA 94588, USA"}]}],"member":"286","published-online":{"date-parts":[[2020,4,24]]},"reference":[{"key":"2023063011474400900_btaa264-B1","doi-asserted-by":"crossref","first-page":"e1008091","DOI":"10.1371\/journal.pgen.1008091","article-title":"Expression estimation and eQTL mapping for HLA genes with a personalized pipeline","volume":"15","author":"Aguiar","year":"2019","journal-title":"PLoS Genet"},{"key":"2023063011474400900_btaa264-B2","first-page":"bbw097","article-title":"Evaluation of computational programs to predict HLA genotypes from genomic sequencing data","volume":"19","author":"Bauer","year":"2018","journal-title":"Brief. Bioinform"},{"key":"2023063011474400900_btaa264-B3","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1186\/s12920-018-0354-x","article-title":"HLA and proteasome expression body map","volume":"11","author":"Boegel","year":"2018","journal-title":"BMC Med. Genomics"},{"key":"2023063011474400900_btaa264-B4","doi-asserted-by":"crossref","first-page":"525","DOI":"10.1038\/nbt.3519","article-title":"Near-optimal probabilistic RNA-seq quantification","volume":"34","author":"Bray","year":"2016","journal-title":"Nat. Biotechnol"},{"key":"2023063011474400900_btaa264-B5","doi-asserted-by":"crossref","first-page":"582","DOI":"10.1126\/science.aao4572","article-title":"Patient HLA class I genotype influences cancer response to checkpoint blockade immunotherapy","volume":"359","author":"Chowell","year":"2018","journal-title":"Science"},{"key":"2023063011474400900_btaa264-B6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/j.1399-0039.2012.01881.x","article-title":"HLA DNA typing: past, present, and future","volume":"80","author":"Erlich","year":"2012","journal-title":"Tissue Antigens"},{"key":"2023063011474400900_btaa264-B7","doi-asserted-by":"crossref","first-page":"10582","DOI":"10.1038\/ncomms10582","article-title":"Melanoma-specific MHC-II expression represents a tumour-autonomous phenotype and predicts response to anti-PD-1\/PD-L1 therapy","volume":"7","author":"Johnson","year":"2016","journal-title":"Nat. Commun"},{"key":"2023063011474400900_btaa264-B8","doi-asserted-by":"crossref","first-page":"2401","DOI":"10.1093\/bioinformatics\/bty125","article-title":"AltHapAlignR: improved accuracy of RNA-seq analyses through the use of alternative haplotypes","volume":"34","author":"Lee","year":"2018","journal-title":"Bioinformatics"},{"key":"2023063011474400900_btaa264-B9","doi-asserted-by":"crossref","first-page":"3868","DOI":"10.1038\/s41467-018-06300-3","article-title":"Acquired cancer resistance to combination immunotherapy from transcriptional loss of class I HLA","volume":"9","author":"Paulson","year":"2018","journal-title":"Nat. Commun"},{"key":"2023063011474400900_btaa264-B10","doi-asserted-by":"crossref","first-page":"3660","DOI":"10.1038\/s41467-019-11591-1","article-title":"A general approach for detecting expressed mutations in AML cells using single cell RNA-sequencing","volume":"10","author":"Petti","year":"2019","journal-title":"Nat. Commun"},{"key":"2023063011474400900_btaa264-B11","doi-asserted-by":"crossref","first-page":"D423","DOI":"10.1093\/nar\/gku1161","article-title":"The IPD and IMGT\/HLA database: allele variant databases","volume":"43","author":"Robinson","year":"2015","journal-title":"Nucleic Acids Res"},{"key":"2023063011474400900_btaa264-B12","author":"Tian","year":"2019"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btaa264\/33195615\/btaa264.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/36\/12\/3905\/50748438\/bioinformatics_36_12_3905.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/36\/12\/3905\/50748438\/bioinformatics_36_12_3905.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,30]],"date-time":"2023-06-30T07:48:33Z","timestamp":1688111313000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/36\/12\/3905\/5824792"}},"subtitle":[],"editor":[{"given":"Anthony","family":"Mathelier","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2020,4,24]]},"references-count":12,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2020,6,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btaa264","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/750612","asserted-by":"object"}]},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2020,6,15]]},"published":{"date-parts":[[2020,4,24]]}}}