{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T09:59:28Z","timestamp":1791280768761,"version":"4.1.0"},"reference-count":57,"publisher":"Wiley","issue":"S1","license":[{"start":{"date-parts":[[2010,12,14]],"date-time":"2010-12-14T00:00:00Z","timestamp":1292284800000},"content-version":"vor","delay-in-days":347,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cytometry Part B Clinical"],"published-print":{"date-parts":[[2010,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background:<\/jats:title><jats:p>Advances in multiparameter flow cytometry (FCM) now allow for the independent detection of larger numbers of fluorochromes on individual cells, generating data with increasingly higher dimensionality. The increased complexity of these data has made it difficult to identify cell populations from high\u2010dimensional FCM data using traditional manual gating strategies based on single\u2010color or two\u2010color displays.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods:<\/jats:title><jats:p>To address this challenge, we developed a novel program, FLOCK (FLOw Clustering without K), that uses a density\u2010based clustering approach to algorithmically identify biologically relevant cell populations from multiple samples in an unbiased fashion, thereby eliminating operator\u2010dependent variability.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results:<\/jats:title><jats:p>FLOCK was used to objectively identify seventeen distinct B\u2010cell subsets in a human peripheral blood sample and to identify and quantify novel plasmablast subsets responding transiently to tetanus and other vaccinations in peripheral blood. FLOCK has been implemented in the publically available Immunology Database and Analysis Portal\u2014ImmPort (<jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"http:\/\/www.immport.org\">http:\/\/www.immport.org<\/jats:ext-link>)\u2014for open use by the immunology research community.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions:<\/jats:title><jats:p>FLOCK is able to identify cell subsets in experiments that use multiparameter FCM through an objective, automated computational approach. The use of algorithms like FLOCK for FCM data analysis obviates the need for subjective and labor\u2010intensive manual gating to identify and quantify cell subsets. Novel populations identified by these computational approaches can serve as hypotheses for further experimental study. \u00a9 2010 International Clinical Cytometry Society<\/jats:p><\/jats:sec>","DOI":"10.1002\/cyto.b.20554","type":"journal-article","created":{"date-parts":[[2010,9,9]],"date-time":"2010-09-09T07:51:24Z","timestamp":1284018684000},"source":"Crossref","is-referenced-by-count":158,"title":["Elucidation of seventeen human peripheral blood B\u2010cell subsets and quantification of the tetanus response using a density\u2010based method for the automated identification of cell populations in multidimensional flow cytometry data"],"prefix":"10.1002","volume":"78B","author":[{"given":"Yu","family":"Qian","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chungwen","family":"Wei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"F.","family":"Eun\u2010Hyung Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John","family":"Campbell","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jessica","family":"Halliley","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jamie A.","family":"Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jennifer","family":"Cai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Y. 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