{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,21]],"date-time":"2025-08-21T17:59:11Z","timestamp":1755799151738,"version":"3.37.3"},"reference-count":39,"publisher":"Oxford University Press (OUP)","issue":"19","license":[{"start":{"date-parts":[[2021,5,11]],"date-time":"2021-05-11T00:00:00Z","timestamp":1620691200000},"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 R&D Program of China","doi-asserted-by":"crossref","award":["2020YFA0712403","2018YFC0910500"],"award-info":[{"award-number":["2020YFA0712403","2018YFC0910500"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61932008","61772368","61503314"],"award-info":[{"award-number":["61932008","61772368","61503314"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shanghai Science and Technology Innovation Fund","award":["19511101404"],"award-info":[{"award-number":["19511101404"]}]},{"name":"Shanghai Municipal Science and Technology Major Project","award":["2018SHZDZX01"],"award-info":[{"award-number":["2018SHZDZX01"]}]},{"name":"Natural Science Foundation of Fujian Province, China","award":["2019J01041"],"award-info":[{"award-number":["2019J01041"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,10,11]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Aligning single-cell transcriptomes is important for the joint analysis of multiple single-cell RNA sequencing datasets, which in turn is vital to establishing a holistic cellular landscape of certain biological processes. Although numbers of approaches have been proposed for this problem, most of which only consider mutual neighbors when aligning the cells without taking into account known cell type annotations.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>In this work, we present MAT2 that aligns cells in the manifold space with a deep neural network employing contrastive learning strategy. Compared with other manifold-based approaches, MAT2 has two-fold advantages. Firstly, with cell triplets defined based on known cell type annotations, the consensus manifold yielded by the alignment procedure is more robust especially for datasets with limited common cell types. Secondly, the batch-effect-free gene expression reconstructed by MAT2 can better help annotate cell types. Benchmarking results on real scRNA-seq datasets demonstrate that MAT2 outperforms existing popular methods. Moreover, with MAT2, the hematopoietic stem cells are found to differentiate at different paces between human and mouse.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>MAT2 is publicly available at https:\/\/github.com\/Zhang-Jinglong\/MAT2.<\/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\/btab250","type":"journal-article","created":{"date-parts":[[2021,4,21]],"date-time":"2021-04-21T02:31:10Z","timestamp":1618972270000},"page":"3263-3269","source":"Crossref","is-referenced-by-count":8,"title":["MAT2: manifold alignment of single-cell transcriptomes with cell triplets"],"prefix":"10.1093","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6795-1423","authenticated-orcid":false,"given":"Jinglong","family":"Zhang","sequence":"first","affiliation":[{"name":"Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University , Shanghai 200433, China"},{"name":"Department of Automation, Xiamen University , Xiamen 361005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xu","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Automation, Xiamen University , Xiamen 361005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8766-5950","authenticated-orcid":false,"given":"Ying","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Automation, Xiamen University , Xiamen 361005, China"},{"name":"Xiamen Key Laboratory of Big Data Intelligent Analysis and Decision, Xiamen University , Xiamen 361005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Feng","family":"Zeng","sequence":"additional","affiliation":[{"name":"Department of Automation, Xiamen University , Xiamen 361005, China"},{"name":"Xiamen Key Laboratory of Big Data Intelligent Analysis and Decision, Xiamen University , Xiamen 361005, China"},{"name":"Department of Neuroscience, School of Medicine, Xiamen University , Xiamen 361005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4531-3970","authenticated-orcid":false,"given":"Xing-Ming","family":"Zhao","sequence":"additional","affiliation":[{"name":"Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University , Shanghai 200433, China"},{"name":"MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, and MOE Frontiers Center for Brain Science , Shanghai 200433, China"},{"name":"Research Institute of Intelligent Complex Systems, Fudan University , Shanghai 200433, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2021,5,11]]},"reference":[{"key":"2023051608283463000_btab250-B1","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1038\/nbt.4314","article-title":"Dimensionality reduction for visualizing single-cell data using UMAP","volume":"37","author":"Becht","year":"2019","journal-title":"Nat. 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