{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T07:30:53Z","timestamp":1782372653212,"version":"3.54.5"},"reference-count":6,"publisher":"Oxford University Press (OUP)","issue":"11","license":[{"start":{"date-parts":[[2020,2,27]],"date-time":"2020-02-27T00:00:00Z","timestamp":1582761600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100000048","name":"American Cancer Society","doi-asserted-by":"publisher","award":["IRG-17-180-19"],"award-info":[{"award-number":["IRG-17-180-19"]}],"id":[{"id":"10.13039\/100000048","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Brain Tumor Funders"},{"name":"San Francisco Glioma Precision Medicine Program"},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["P30CA082103"],"award-info":[{"award-number":["P30CA082103"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"name":"University of California Cancer Research Coordinating Committee"}],"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>Single-cell data are being generated at an accelerating pace. How best to project data across single-cell atlases is an open problem. We developed a boosted learner that overcomes the greatest challenge with status quo classifiers: low sensitivity, especially when dealing with rare cell types. By comparing novel and published data from distinct scRNA-seq modalities that were acquired from the same tissues, we show that this approach preserves cell-type labels when mapping across diverse platforms.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>https:\/\/github.com\/diazlab\/ELSA<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Contact<\/jats:title>\n                  <jats:p>aaron.diaz@ucsf.edu<\/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\/btaa137","type":"journal-article","created":{"date-parts":[[2020,2,25]],"date-time":"2020-02-25T04:47:25Z","timestamp":1582606045000},"page":"3585-3587","source":"Crossref","is-referenced-by-count":21,"title":["Ensemble learning for classifying single-cell data and projection across reference atlases"],"prefix":"10.1093","volume":"36","author":[{"given":"Lin","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Neurosurgery , University of California, San Francisco, CA 94158, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francisca","family":"Catalan","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery , University of California, San Francisco, CA 94158, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Karin","family":"Shamardani","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery , University of California, San Francisco, CA 94158, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Husam","family":"Babikir","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9059-9501","authenticated-orcid":false,"given":"Aaron","family":"Diaz","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery , University of California, San Francisco, CA 94158, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2020,2,27]]},"reference":[{"key":"2023062312021205800_btaa137-B1","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1038\/nbt.4096","article-title":"Integrating single-cell transcriptomic data across different conditions, technologies, and species","volume":"36","author":"Butler","year":"2018","journal-title":"Nat. Biotechnol"},{"key":"2023062312021205800_btaa137-B2","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1038\/s41576-018-0088-9","article-title":"Challenges in unsupervised clustering of single-cell RNA-seq data","volume":"20","author":"Kiselev","year":"2019","journal-title":"Nat. Rev. Genet"},{"key":"2023062312021205800_btaa137-B3","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1038\/nmeth.4644","article-title":"Scmap: projection of single-cell RNA-seq data across data sets","volume":"15","author":"Kiselev","year":"2018","journal-title":"Nat. Methods"},{"key":"2023062312021205800_btaa137-B4","doi-asserted-by":"crossref","first-page":"983","DOI":"10.1038\/s41592-019-0535-3","article-title":"Supervised classification enables rapid annotation of cell atlases","volume":"16","author":"Pliner","year":"2019","journal-title":"Nat. Methods"},{"key":"2023062312021205800_btaa137-B5","doi-asserted-by":"crossref","first-page":"284","DOI":"10.1038\/s41467-017-02554-5","article-title":"A general and flexible method for signal extraction from single-cell RNA-seq data","volume":"9","author":"Risso","year":"2018","journal-title":"Nat. Commun"},{"key":"2023062312021205800_btaa137-B6","doi-asserted-by":"crossref","first-page":"1708","DOI":"10.1158\/2159-8290.CD-19-0329","article-title":"The phenotypes of proliferating glioblastoma cells reside on a single axis of variation","volume":"9","author":"Wang","year":"2019","journal-title":"Cancer Discov"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btaa137\/32923775\/btaa137.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/36\/11\/3585\/50670615\/bioinformatics_36_11_3585.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/36\/11\/3585\/50670615\/bioinformatics_36_11_3585.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,23]],"date-time":"2023-06-23T12:03:24Z","timestamp":1687521804000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/36\/11\/3585\/5762611"}},"subtitle":[],"editor":[{"given":"Alfonso","family":"Valencia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2020,2,27]]},"references-count":6,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2020,6,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btaa137","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2020,6]]},"published":{"date-parts":[[2020,2,27]]}}}