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. 2022 Apr 7;13:1901. doi: 10.1038/s41467-022-29576-y

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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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 5 — a t-SNE plots for raw and imputed data. b Evaluation of batch and cell type separation in raw and imputed data by four different metrics: average Silhouette width, adjusted Rand index, normalized mutual information, and purity score. Good performance is shown as big values in both X-(cell type separation) and Y-(batch effect removal) axes.