{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,16]],"date-time":"2025-11-16T21:53:47Z","timestamp":1763330027229,"version":"3.41.2"},"reference-count":17,"publisher":"Oxford University Press (OUP)","issue":"7","license":[{"start":{"date-parts":[[2024,7,8]],"date-time":"2024-07-08T00:00:00Z","timestamp":1720396800000},"content-version":"vor","delay-in-days":7,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Union's Horizon 2020 research and innovation programme","award":["953407"],"award-info":[{"award-number":["953407"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,7,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Understanding the dynamics of gene expression across different cellular states is crucial for discerning the mechanisms underneath cellular differentiation. Genes that exhibit variation in mean expression as a function of Pseudotime and between branching trajectories are expected to govern cell fate decisions. We introduce scMaSigPro, a method for the identification of differential gene expression patterns along Pseudotime and branching paths simultaneously.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We assessed the performance of scMaSigPro using synthetic and public datasets. Our evaluation shows that scMaSigPro outperforms existing methods in controlling the False Positive Rate and is computationally efficient.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>scMaSigPro is available as a free R package (version 4.0 or higher) under the GPL(\u22652) license on GitHub at \u2018github.com\/BioBam\/scMaSigPro\u2019 and archived with version 0.03 on Zenodo at \u2018zenodo.org\/records\/12568922\u2019.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btae443","type":"journal-article","created":{"date-parts":[[2024,7,8]],"date-time":"2024-07-08T18:22:50Z","timestamp":1720462970000},"source":"Crossref","is-referenced-by-count":1,"title":["scMaSigPro: differential expression analysis along single-cell trajectories"],"prefix":"10.1093","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2618-5296","authenticated-orcid":false,"given":"Priyansh","family":"Srivastava","sequence":"first","affiliation":[{"name":"BioBam Bioinformatics S.L. , Valencia, 46024, Spain"},{"name":"Department of Computer Science, University of Valencia , Valencia, 46100, Spain"}]},{"given":"Marta","family":"Benegas Coll","sequence":"additional","affiliation":[{"name":"BioBam Bioinformatics S.L. , Valencia, 46024, Spain"}]},{"given":"Stefan","family":"G\u00f6tz","sequence":"additional","affiliation":[{"name":"BioBam Bioinformatics S.L. , Valencia, 46024, Spain"}]},{"given":"Mar\u00eda Jos\u00e9","family":"Nueda","sequence":"additional","affiliation":[{"name":"Mathematics Department, University of Alicante , Alicante, 03690, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9597-311X","authenticated-orcid":false,"given":"Ana","family":"Conesa","sequence":"additional","affiliation":[{"name":"Institute for Integrative Systems Biology (I2SysBio), Consejo Superior de Investigaciones Cient\u0131ficas (CSIC) , Paterna, 46980, Spain"}]}],"member":"286","published-online":{"date-parts":[[2024,7,8]]},"reference":[{"key":"2024072505252383900_btae443-B1","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":"2024072505252383900_btae443-B2","doi-asserted-by":"crossref","first-page":"1096","DOI":"10.1093\/bioinformatics\/btl056","article-title":"maSigPro: a method to identify significantly differential expression profiles in timecourse microarray experiments","volume":"22","author":"Conesa","year":"2006","journal-title":"Bioinformatics"},{"key":"2024072505252383900_btae443-B3","doi-asserted-by":"crossref","first-page":"100344","DOI":"10.1016\/j.coisb.2021.05.005","article-title":"Recent advances in 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