{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T22:06:10Z","timestamp":1773093970456,"version":"3.50.1"},"reference-count":11,"publisher":"Oxford University Press (OUP)","issue":"6","license":[{"start":{"date-parts":[[2020,8,26]],"date-time":"2020-08-26T00:00:00Z","timestamp":1598400000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001711","name":"Swiss National Science Foundation","doi-asserted-by":"publisher","award":["180010"],"award-info":[{"award-number":["180010"]}],"id":[{"id":"10.13039\/501100001711","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,5,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Summary<\/jats:title>\n                    <jats:p>STACAS is a computational method for the identification of integration anchors in the Seurat environment, optimized for the integration of single-cell (sc) RNA-seq datasets that share only a subset of cell types. We demonstrate that by (i) correcting batch effects while preserving relevant biological variability across datasets, (ii) filtering aberrant integration anchors with a quantitative distance measure and (iii) constructing optimal guide trees for integration, STACAS can accurately align scRNA-seq datasets composed of only partially overlapping cell populations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>Source code and R package available at https:\/\/github.com\/carmonalab\/STACAS; Docker image available at https:\/\/hub.docker.com\/repository\/docker\/mandrea1\/stacas_demo.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btaa755","type":"journal-article","created":{"date-parts":[[2020,8,19]],"date-time":"2020-08-19T15:26:54Z","timestamp":1597850814000},"page":"882-884","source":"Crossref","is-referenced-by-count":58,"title":["STACAS: Sub-Type Anchor Correction for Alignment in Seurat to integrate single-cell RNA-seq data"],"prefix":"10.1093","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8036-2647","authenticated-orcid":false,"given":"Massimo","family":"Andreatta","sequence":"first","affiliation":[{"name":"Ludwig Institute for Cancer Research Lausanne, University of Lausanne , CH-1066 Epalinges, Switzerland"},{"name":"Department of Oncology, CHUV , UNIL CHUV, CH-1066 Epalinges, Lausanne, Switzerland"},{"name":"University of Lausanne , Lausanne, Switzerland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2495-0671","authenticated-orcid":false,"given":"Santiago J","family":"Carmona","sequence":"additional","affiliation":[{"name":"Ludwig Institute for Cancer Research Lausanne, University of Lausanne , CH-1066 Epalinges, Switzerland"},{"name":"Department of Oncology, CHUV , UNIL CHUV, CH-1066 Epalinges, Lausanne, Switzerland"},{"name":"University of Lausanne , Lausanne, Switzerland"}]}],"member":"286","published-online":{"date-parts":[[2020,8,26]]},"reference":[{"key":"2023051704133011800_btaa755-B1","doi-asserted-by":"publisher","author":"Andreatta","year":"2020","DOI":"10.1101\/2020.06.23.166546"},{"key":"2023051704133011800_btaa755-B2","doi-asserted-by":"crossref","first-page":"1737369","DOI":"10.1080\/2162402X.2020.1737369","article-title":"Deciphering the transcriptomic landscape of tumor-infiltrating CD8 lymphocytes in B16 melanoma tumors with single-cell RNA-Seq","volume":"9","author":"Carmona","year":"2020","journal-title":"OncoImmunology"},{"key":"2023051704133011800_btaa755-B3","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1038\/s41587-020-0449-8","article-title":"Single-cell RNA-seq analysis software providers scramble to offer solutions","volume":"38","author":"Eisenstein","year":"2020","journal-title":"Nat. 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