{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T13:08:52Z","timestamp":1770815332866,"version":"3.50.1"},"reference-count":22,"publisher":"Oxford University Press (OUP)","issue":"11","license":[{"start":{"date-parts":[[2020,11,27]],"date-time":"2020-11-27T00:00:00Z","timestamp":1606435200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31571359"],"award-info":[{"award-number":["31571359"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31771464"],"award-info":[{"award-number":["31771464"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31970632"],"award-info":[{"award-number":["31970632"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,7,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>An important task in the analysis of single-cell RNA-Seq data is the estimation of differentiation potency, as this can help identify stem-or-multipotent cells in non-temporal studies or in tissues where differentiation hierarchies are not well established. A key challenge in the estimation of single-cell potency is the need for a fast and accurate algorithm, scalable to large scRNA-Seq studies profiling millions of cells.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Here, we present a single-cell potency measure, called Correlation of Connectome and Transcriptome (CCAT), which can return accurate single-cell potency estimates of a million cells in minutes, a 100-fold improvement over current state-of-the-art methods. We benchmark CCAT against 8 other single-cell potency models and across 28 scRNA-Seq studies, encompassing over 2 million cells, demonstrating comparable accuracy than the current state-of-the-art, at a significantly reduced computational cost, and with increased robustness to dropouts.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>CCAT is part of the SCENT R-package, freely available from https:\/\/github.com\/aet21\/SCENT.<\/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\/btaa987","type":"journal-article","created":{"date-parts":[[2020,11,13]],"date-time":"2020-11-13T20:13:22Z","timestamp":1605298402000},"page":"1528-1534","source":"Crossref","is-referenced-by-count":30,"title":["Ultra-fast scalable estimation of single-cell differentiation potency from scRNA-Seq data"],"prefix":"10.1093","volume":"37","author":[{"given":"Andrew E","family":"Teschendorff","sequence":"first","affiliation":[{"name":"CAS Key Lab of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences , Shanghai 200031, China"},{"name":"UCL Cancer Institute, University College London , London WC1E 6BT, UK"}]},{"given":"Alok K","family":"Maity","sequence":"additional","affiliation":[{"name":"CAS Key Lab of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences , Shanghai 200031, China"}]},{"given":"Xue","family":"Hu","sequence":"additional","affiliation":[{"name":"CAS Key Lab of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences , Shanghai 200031, China"}]},{"given":"Chen","family":"Weiyan","sequence":"additional","affiliation":[{"name":"CAS Key Lab of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences , Shanghai 200031, China"}]},{"given":"Matthias","family":"Lechner","sequence":"additional","affiliation":[{"name":"UCL Cancer Institute, University College London , London WC1E 6BT, UK"},{"name":"Department of Otolaryngology-Head and Neck Surgery, Stanford University School of Medicine , Palo Alto, CA 94305-5739, USA"}]}],"member":"286","published-online":{"date-parts":[[2020,11,27]]},"reference":[{"key":"2023051709453151300_btaa987-B1","doi-asserted-by":"crossref","first-page":"1241","DOI":"10.1093\/bioinformatics\/btv715","article-title":"Destiny: diffusion maps for large-scale single-cell data in r","volume":"32","author":"Angerer","year":"2016","journal-title":"Bioinformatics"},{"key":"2023051709453151300_btaa987-B2","doi-asserted-by":"crossref","first-page":"3039","DOI":"10.1038\/srep03039","article-title":"Cellular network entropy as the energy potential in Waddington\u2019s differentiation landscape","volume":"3","author":"Banerji","year":"2013","journal-title":"Sci. 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