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. 2023 Oct 9;14:6317. doi: 10.1038/s41467-023-42016-9

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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 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/.

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Fig. 4 — a Upper row: average change in chromatin state at transcription start site from iPSC to definitive endoderm cells for D-ASE genes and non-D-ASE genes; Error bars represent 95% confidence intervals (mean ± 1.96 standard error). Lower row: distribution of chromatin stage change (possible values: 0, 0.2, 0.4, 0.6, 0.8, 1) among D-ASE genes and non-D-ASE genes. At FDR < 0.05, the number of D-ASE genes is 324 for DAESC-BB, 657 for DAESC-Mix, and 532 for GLMM. For each method, the genes that do not reach FDR < 0.05 are considered non-D-ASE genes (see “Methods” for details). Chromatin states are from ChromHMM analysis of the Roadmap Epigenomics data and recoded to 0 (inactive) or 1 (active). D is the difference between D-ASE and non-D-ASE genes, and P values are calculated using linear regression: chromatin state change ~ I (the gene shows D-ASE) + total read depth of the gene. Here I(.) is the indicator function. b Upper: correlation between D-ASE effect size (β₁) and change of chromatin state (n = 4102 genes). Error bars represent 95% confidence intervals (estimated correlation coefficient ± 1.96 standard error). Lower: scatter plot from which the correlation is derived; trend curves are generated using ggplot2::geom_smooth(), and shadings represent 95% confidence bands. c Top 30 genes identified by DAESC-Mix (smallest P values) and average allelic ratio of iPSCs vs definitive endoderm cells estimated by DAESC-Mix, computed as $1 / (1 + \exp (- (β_{0} + β_{1} t)))$ where t is the average pseudotime of the cell type. The dashed line corresponds to allelic ratio=0.5. d Types of D-ASE genes and their proportions. See “Methods” for details. e Enrichment of top D-ASE 30 genes identified by DAESC-Mix in Gene Ontology Biological Processes gene sets. Only gene sets with FDR < 0.05 are shown. Source data are provided as a Source Data file.