{"id":5552,"date":"2022-02-11T04:00:00","date_gmt":"2022-01-30T03:15:59","guid":{"rendered":"https:\/\/www.ibs.re.kr\/bimag\/?post_type=tribe_events&p=5552"},"modified":"2022-02-08T14:48:47","modified_gmt":"2022-02-08T05:48:47","slug":"2022-02-11","status":"publish","type":"tribe_events","link":"https:\/\/www.ibs.re.kr\/bimag\/event\/2022-02-11\/","title":{"rendered":"Phiclust: a clusterability measure for single-cell transcriptomics reveals phenotypic subpopulations"},"content":{"rendered":"

We will discuss about “Phiclust: a clusterability measure for single-cell transcriptomics reveals phenotypic subpopulations”, Mircea et al., 2022, Genome Biology<\/em><\/p>\n

The ability to discover new cell phenotypes by unsupervised clustering of single-cell transcriptomes has revolutionized biology. Currently, there is no principled way to decide whether a cluster of cells contains meaningful subpopulations that should be further resolved. Here, we present phiclust (\u03d5<\/em>_clust), a clusterability measure derived from random matrix theory that can be used to identify cell clusters with non-random substructure, testably leading to the discovery of previously overlooked phenotypes.<\/p>\n","protected":false},"excerpt":{"rendered":"

We will discuss about “Phiclust: a clusterability measure for single-cell transcriptomics reveals phenotypic subpopulations”, Mircea et al., 2022, Genome Biology The ability to discover new cell phenotypes by unsupervised clustering … <\/p>\n

Continue reading “Phiclust: a clusterability measure for single-cell transcriptomics reveals phenotypic subpopulations”<\/span><\/a><\/p>\n","protected":false},"author":3,"featured_media":0,"template":"","meta":{"_editorskit_title_hidden":false,"_editorskit_reading_time":0,"_editorskit_is_block_options_detached":false,"_editorskit_block_options_position":"{}","_uag_custom_page_level_css":"","_tribe_events_status":"","_tribe_events_status_reason":"","footnotes":""},"tags":[],"tribe_events_cat":[219],"class_list":["post-5552","tribe_events","type-tribe_events","status-publish","hentry","tribe_events_cat-journal-club","cat_journal-club"],"yoast_head":"\nPhiclust: a clusterability measure for single-cell transcriptomics reveals phenotypic subpopulations - Biomedical Mathematics Group<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.ibs.re.kr\/bimag\/event\/2022-02-11\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Phiclust: a clusterability measure for single-cell transcriptomics reveals phenotypic subpopulations - Biomedical Mathematics Group\" \/>\n<meta property=\"og:description\" content=\"We will discuss about “Phiclust: a clusterability measure for single-cell transcriptomics reveals phenotypic subpopulations”, Mircea et al., 2022, Genome Biology The ability to discover new cell phenotypes by unsupervised clustering … Continue reading "Phiclust: a clusterability measure for single-cell transcriptomics reveals phenotypic subpopulations"\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.ibs.re.kr\/bimag\/event\/2022-02-11\/\" \/>\n<meta property=\"og:site_name\" content=\"Biomedical Mathematics Group\" \/>\n<meta property=\"article:modified_time\" content=\"2022-02-08T05:48:47+00:00\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/event\\\/2022-02-11\\\/\",\"url\":\"https:\\\/\\\/www.ibs.re.kr\\\/bimag\\\/event\\\/2022-02-11\\\/\",\"name\":\"Phiclust: a clusterability measure for single-cell transcriptomics reveals phenotypic subpopulations - 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