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. 2021 Sep 14;7:85. doi: 10.1038/s41421-021-00314-w

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© The Author(s) 2021

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. 2 — a UMAP plot displaying 4133 B cells from two MG patients and two HCs separated into 9 subtypes. b Violin plots showing key gene markers across B cell subsets. c Gene set enrichment revealed differences in pathway activities and cell identity of naive, memory, switched B cells, and plasma B cells. d B cells were sorted using the DDRTree algorithm and projected onto the different cell states using the color in a. Transcriptional activity was estimated by measuring the ratio between unspliced and spliced mRNAs. The length of the arrow represents the transcriptional activity. e UMAP plots showing the expression of BCL3 and POU2AF1 genes in B cells (top) and the AUC of the estimated regulon activity of the corresponding TFs, predicting the degree of expression regulation of their target genes (bottom). f Heatmap of the AUC scores of expression regulation by transcription factors (regulon activity), as estimated using SCENIC, followed by comparisons between two groups using the t-test. The twenty transcription factors with the highest upregulated expression in MG are shown.