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. 2022 Jan 6;23:8. doi: 10.1186/s13059-021-02593-8

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© The Author(s) 2022

Open AccessThis 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. 4 — scDALI-Het identifies time-specific intra-lineage variation. a Scatter plot of negative log P-values for scDALI-Het versus a scDALI test for time-specific variation in the muscle population. Red circle highlights region chr2R:13675707-13676707. b Of 363 peaks identified by scDALI-Het that are accessible in the muscle, 19% showed significant temporal effects (FDR < 0.1). c The majority of peaks with a time-specific effect in the muscle did not show significant differential allelic imbalance between lineages. d Temporal order for the muscle lineage estimated by the variational autoencoder model. e, f Estimated allelic rates across time for region chr2R:13675707-13676707. Black dots denote cells with observed allele-specific counts in this region