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. 2024 Nov 2;15:9468. doi: 10.1038/s41467-024-53666-8

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© The Author(s) 2024

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, 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 you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. 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-nc-nd/4.0/.

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Fig. 1 — a Setup of a case-control single-cell experiment, in which cells of a given cell type in control samples are labeled as unaffected, while cells in case samples can be either affected or unaffected by the perturbation. b Standard clustering can produce clusters containing cells with mixed case-control sample-level labels while the subset of truly affected cells can be hidden. Colors as defined in A. c Representative violin plots of the average log normalized expression of perturbation markers split by sample-level labels (left) and highlighting the difference in the distributions of affected and unaffected cells within the case sample (right). Colors as defined in A. Area not scaled to count. d Overview of the HiDDEN label refinement framework. First, gene expression profiles are summarized through a dimensionality reduction method. Then, a prediction model takes the reduced expression profiles and the sample-level binary labels and transforms them into per cell continuous perturbation scores. Finally, the continuous scores of cells originating from the case samples can be binarized through a classification method into HiDDEN-refined binary labels (Methods). e Representative scatterplot of -log10 adjusted p values per gene computed using differential expression (DE) on case-control sample labels (x-axis) and HiDDEN-refined binary labels (y-axis). P values are calculated using a one-sided Wilcoxon rank sum test with Benjamini-Hochberg correction. Horizontal and vertical dashed lines drawn at -log10(0.05) significance threshold. Ground truth DE genes colored in green. Standard DE analysis on case-control labels captures only a small number of ground truth markers, while HiDDEN successfully recovers many of them. Figure 1 panel a Created in BioRender. Lab, M. (2024) BioRender.com/f66p361. Figure 1 panel B created in BioRender. Lab, M. (2024) BioRender.com/j24d711. Figure 1 panel d created in BioRender. Lab, M. (2024) BioRender.com/z12o210.