{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T17:57:27Z","timestamp":1792259847332,"version":"4.4.0"},"reference-count":18,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2015,1,8]],"date-time":"2015-01-08T00:00:00Z","timestamp":1420675200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"name":"Agency for Innovation by Science and Technology (IWT); Ghent University Multidisciplinary Research Partnership Bioinformatics"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cytometry Pt A"],"published-print":{"date-parts":[[2015,7]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>The number of markers measured in both flow and mass cytometry keeps increasing steadily. Although this provides a wealth of information, it becomes infeasible to analyze these datasets manually. When using 2D scatter plots, the number of possible plots increases exponentially with the number of markers and therefore, relevant information that is present in the data might be missed. In this article, we introduce a new visualization technique, called FlowSOM, which analyzes Flow or mass cytometry data using a Self\u2010Organizing Map. Using a two\u2010level clustering and star charts, our algorithm helps to obtain a clear overview of how all markers are behaving on all cells, and to detect subsets that might be missed otherwise. R code is available at <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/github.com\/SofieVG\/FlowSOM\">https:\/\/github.com\/SofieVG\/FlowSOM<\/jats:ext-link> and will be made available at Bioconductor. \u00a9 2015 International Society for Advancement of Cytometry<\/jats:p>","DOI":"10.1002\/cyto.a.22625","type":"journal-article","created":{"date-parts":[[2015,1,8]],"date-time":"2015-01-08T21:22:13Z","timestamp":1420752133000},"page":"636-645","source":"Crossref","is-referenced-by-count":2036,"title":["FlowSOM: Using self\u2010organizing maps for visualization and interpretation of cytometry data"],"prefix":"10.1002","volume":"87","author":[{"given":"Sofie","family":"Van Gassen","sequence":"first","affiliation":[{"name":"Department of Information Technology Ghent University, iMinds Ghent Belgium"},{"name":"Inflammation Research Center, VIB Ghent Belgium"},{"name":"Department of Respiratory Medicine Ghent University Hospital Ghent Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Britt","family":"Callebaut","sequence":"additional","affiliation":[{"name":"Department of Information Technology Ghent University, iMinds Ghent Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mary J.","family":"Van Helden","sequence":"additional","affiliation":[{"name":"Inflammation Research Center, VIB Ghent Belgium"},{"name":"Department of Respiratory Medicine Ghent University Hospital Ghent Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bart N.","family":"Lambrecht","sequence":"additional","affiliation":[{"name":"Inflammation Research Center, VIB Ghent Belgium"},{"name":"Department of Respiratory Medicine Ghent University Hospital Ghent Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Piet","family":"Demeester","sequence":"additional","affiliation":[{"name":"Department of Information Technology Ghent University, iMinds Ghent Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tom","family":"Dhaene","sequence":"additional","affiliation":[{"name":"Department of Information Technology Ghent University, iMinds Ghent Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yvan","family":"Saeys","sequence":"additional","affiliation":[{"name":"Inflammation Research Center, VIB Ghent Belgium"},{"name":"Department of Respiratory Medicine Ghent University Hospital Ghent Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2015,1,8]]},"reference":[{"key":"e_1_2_13_2_1","doi-asserted-by":"publisher","DOI":"10.1038\/nbt.2594"},{"key":"e_1_2_13_3_1","doi-asserted-by":"publisher","DOI":"10.1038\/nbt.1991"},{"key":"e_1_2_13_4_1","doi-asserted-by":"publisher","DOI":"10.1002\/cyto.a.20531"},{"key":"e_1_2_13_5_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0903028106"},{"key":"e_1_2_13_6_1","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-10-145"},{"key":"e_1_2_13_7_1","doi-asserted-by":"publisher","DOI":"10.1155\/2009\/247646"},{"key":"e_1_2_13_8_1","doi-asserted-by":"publisher","DOI":"10.1002\/cyto.a.21007"},{"key":"e_1_2_13_9_1","doi-asserted-by":"publisher","DOI":"10.1002\/cyto.a.22446"},{"key":"e_1_2_13_10_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1003130"},{"key":"e_1_2_13_11_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0100334"},{"key":"e_1_2_13_12_1","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth.2365"},{"key":"e_1_2_13_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/5.58325"},{"key":"e_1_2_13_14_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v021.i05","article-title":"Self\u2010 and super\u2010organising maps in r: The kohonen package","volume":"21","author":"Wehrens R","year":"2007","journal-title":"J Stat Softw"},{"key":"e_1_2_13_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/361284.361299"},{"key":"e_1_2_13_16_1","article-title":"The igraph software package for complex network research. 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