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. 2024 Feb 26;25:57. doi: 10.1186/s13059-024-03185-y

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© The Author(s) 2024

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. 2 — Performance of various methods on four different datasets. A Accuracies for variable panel sizes. B Macro F1-scores for variable panel sizes. C Confusion matrices for scGIST for panel size = 60. D t-SNE plots using the gene panel of size 60 selected by scGIST for (i) PBMC 3K, (ii) Head and Neck Cancer, (iii) Tabula Sapiens, and (iv) Mouse Endoderm datasets