{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T07:27:24Z","timestamp":1758266844291,"version":"3.37.3"},"reference-count":29,"publisher":"Oxford University Press (OUP)","issue":"21","license":[{"start":{"date-parts":[[2021,7,1]],"date-time":"2021-07-01T00:00:00Z","timestamp":1625097600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2017YFA0102600"],"award-info":[{"award-number":["2017YFA0102600"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["32030022","31970642","31721003","31900491"],"award-info":[{"award-number":["32030022","31970642","31721003","31900491"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018619","name":"National Program for Support of Top-notch Young Professionals","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100018619","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2018M642073"],"award-info":[{"award-number":["2018M642073"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Major Program of Development Fund for Shanghai Zhangjiang National Innovation Demonstration Zone","award":["ZJ2018-ZD-004"],"award-info":[{"award-number":["ZJ2018-ZD-004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,11,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>The increasing amount of time-series single-cell RNA sequencing (scRNA-seq) data raises the key issue of connecting cell states (i.e. cell clusters or cell types) to obtain the continuous temporal dynamics of transcription, which can highlight the unified biological mechanisms involved in cell state transitions. However, most existing trajectory methods are specifically designed for individual cells, so they can hardly meet the needs of accurately inferring the trajectory topology of the cell state, which usually contains cells assigned to different branches.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Here, we present CStreet, a computed Cell State trajectory inference method for time-series scRNA-seq data. It uses time-series information to construct the k-nearest neighbor connections between cells within each time point and between adjacent time points. Then, CStreet estimates the connection probabilities of the cell states and visualizes the trajectory, which may include multiple starting points and paths, using a force-directed graph. By comparing the performance of CStreet with that of six commonly used cell state trajectory reconstruction methods on simulated data and real data, we demonstrate the high accuracy and high tolerance of CStreet.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>CStreet is written in Python and freely available on the web at https:\/\/github.com\/TongjiZhanglab\/CStreet and https:\/\/doi.org\/10.5281\/zenodo.4483205<\/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\/btab488","type":"journal-article","created":{"date-parts":[[2021,6,30]],"date-time":"2021-06-30T19:22:52Z","timestamp":1625080972000},"page":"3774-3780","source":"Crossref","is-referenced-by-count":7,"title":["CStreet: a computed <u>C<\/u>ell <u>S<\/u>tate <u>tr<\/u>ajectory inf<u>e<\/u>r<u>e<\/u>nce method for <u>t<\/u>ime-series single-cell RNA sequencing data"],"prefix":"10.1093","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8454-6347","authenticated-orcid":false,"given":"Chengchen","family":"Zhao","sequence":"first","affiliation":[{"name":"Institute for Regenerative Medicine, Shanghai East Hospital, Shanghai Key Laboratory of Signaling and Disease Research, Frontier Science Center for Stem Cell Research, School of Life Science and Technology, Tongji University , Shanghai 200092, China"}]},{"given":"Wenchao","family":"Xiu","sequence":"additional","affiliation":[{"name":"Institute for Regenerative Medicine, Shanghai East Hospital, Shanghai Key Laboratory of Signaling and Disease Research, Frontier Science Center for Stem Cell Research, School of Life Science and Technology, Tongji University , Shanghai 200092, China"}]},{"given":"Yuwei","family":"Hua","sequence":"additional","affiliation":[{"name":"Institute for Regenerative Medicine, Shanghai East Hospital, Shanghai Key Laboratory of Signaling and Disease Research, Frontier Science Center for Stem Cell Research, School of Life Science and Technology, Tongji University , Shanghai 200092, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0800-0016","authenticated-orcid":false,"given":"Naiqian","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, Shandong University at Weihai , Weihai 264209, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6316-2734","authenticated-orcid":false,"given":"Yong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute for Regenerative Medicine, Shanghai East Hospital, Shanghai Key Laboratory of Signaling and Disease Research, Frontier Science Center for Stem Cell Research, School of Life Science and Technology, Tongji University , Shanghai 200092, China"}]}],"member":"286","published-online":{"date-parts":[[2021,7,1]]},"reference":[{"key":"2023051608254278500_btab488-B1","doi-asserted-by":"crossref","first-page":"eaar5780","DOI":"10.1126\/science.aar5780","article-title":"The dynamics of gene expression in vertebrate embryogenesis at single-cell resolution","volume":"360","author":"Briggs","year":"2018","journal-title":"Science"},{"key":"2023051608254278500_btab488-B2","doi-asserted-by":"crossref","first-page":"496","DOI":"10.1038\/s41586-019-0969-x","article-title":"The single-cell transcriptional landscape of mammalian organogenesis","volume":"566","author":"Cao","year":"2019","journal-title":"Nature"},{"key":"2023051608254278500_btab488-B3","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1038\/s41587-019-0088-0","article-title":"Inferring population dynamics from single-cell RNA-sequencing time series data","volume":"37","author":"Fischer","year":"2019","journal-title":"Nat. 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