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. 2023 Mar 27;41(12):1746–1757. doi: 10.1038/s41587-023-01716-9

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© The Author(s) 2023

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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Extended Data Fig. 6 — A. Metacell cell-type purity (fraction of the maximally represented cell-type amongst the cells assigned to a metacell) computed by different methods on PBMC data. Wilcoxon rank-sum test was used to assess the significance of differences (** 0.001 < P < 0.01, *** 0.0001 < P < 0.0001, **** P < 0.0001). B. Left: UMAPs of 10x Genomics PBMC CITE-seq dataset⁵, colored by coarse cell-types. Right: Comparison of cell-type purity between SEACells and MetaCell-2 metacells. Metacells were identified using the RNA modality whereas cell types were determined using cell-surface protein profiles. C. Same as (A), for finer resolution cell-types. Box plots display median, 25^th(Q1) and 75^th (Q3) percentiles; whiskers extend to the furthest datapoint within the range 1.5 *(Q3-Q1); points beyond that are denoted as outliers. Number of metacells = 109.