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However, due to the minimal amount of unspliced RNA contents, the estimation of RNA velocity suffers from high noise and may result in less reliable trajectories. Here, we present Velocity Autoencoder (VeloAE), a tailored autoencoder to denoise RNA velocity for more accurate quantification of cell transitions. Through various biological systems, we demonstrate its effectiveness for correcting the inferred trajectory and its interpretability for linking the learned dimensions to underlying biological processes.<\/jats:p>","DOI":"10.1073\/pnas.2105859118","type":"journal-article","created":{"date-parts":[[2021,12,6]],"date-time":"2021-12-06T13:37:10Z","timestamp":1638797830000},"update-policy":"https:\/\/doi.org\/10.1073\/pnas.cm10313","source":"Crossref","is-referenced-by-count":68,"title":["Representation learning of RNA velocity reveals robust cell transitions"],"prefix":"10.1073","volume":"118","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4382-3221","authenticated-orcid":false,"given":"Chen","family":"Qiao","sequence":"first","affiliation":[{"name":"School of Biomedical Sciences, University of Hong Kong, Hong Kong S.A.R., China;"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuanhua","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Biomedical Sciences, University of Hong Kong, Hong Kong S.A.R., China;"},{"name":"Department of Statistics and Actuarial Science, University of Hong Kong, Hong Kong S.A.R., China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"341","published-online":{"date-parts":[[2021,12,3]]},"reference":[{"key":"e_1_3_4_1_2","doi-asserted-by":"publisher","DOI":"10.1101\/gr.190595.115"},{"key":"e_1_3_4_2_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41587-019-0071-9"},{"key":"e_1_3_4_3_2","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth.4402"},{"key":"e_1_3_4_4_2","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth.3971"},{"key":"e_1_3_4_5_2","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-018-1440-2"},{"key":"e_1_3_4_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2019.01.006"},{"key":"e_1_3_4_7_2","doi-asserted-by":"publisher","DOI":"10.1038\/nbt.3269"},{"key":"e_1_3_4_8_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-018-0414-6"},{"key":"e_1_3_4_9_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41587-020-0591-3"},{"key":"e_1_3_4_10_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-020-0935-4"},{"key":"e_1_3_4_11_2","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-021-02461-5"},{"key":"e_1_3_4_12_2","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-017-1334-8"},{"key":"e_1_3_4_13_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-018-07931-2"},{"key":"e_1_3_4_14_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-018-0229-2"},{"key":"e_1_3_4_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.gpb.2018.08.003"},{"key":"e_1_3_4_16_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.50"},{"key":"e_1_3_4_17_2","volume-title":"3rd International Conference on Learning Representations","author":"Bahdanau D.","year":"2015","unstructured":"D. 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