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. 2022 Jun 27;23:139. doi: 10.1186/s13059-022-02706-x

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© The Author(s) 2022

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 3 — The results of scDART and baseline methods on the mouse endothelial cell development dataset. a–c Latent embedding of scDART, visualized using PCA. Cells are colored with (a) cell type annotation from original data paper, (b) data batches, and (c) inferred pseudotime. Red lines in (a) show the inferred trajectory backbone. d The latent embedding of Seurat, Liger, and UnionCom where cells are colored with cell type annotation from original data paper. All plots share the same legend as in the Liger plot. e The latent embedding of Seurat, Liger, and UnionCom where cells are colored with data batches. All plots share the same legend as in the Liger plot