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. 2023 Sep 18;24:347. doi: 10.1186/s12859-023-05481-z

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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/. 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. 3 — Impact of genomic features on the inference of LOF intolerance. a Association of genomic features with LOF intolerance. We define the contribution score of a genomic feature as the negative weight of the feature in the linear DeepLOF model. The absolute value of a contribution score indicates the strength of association between a feature and LOF intolerance, whereas the sign of a contribution score indicates the direction of association. b DeepLOF automatically adjusts the relative importance of genomic features in a gene length-dependent manner. The x axis represents the expected number of LOF variants. The y axis represents the absolute difference in DeepLOF score between the linear DeepLOF model with genomic features and the counterpart model without genomic features. A higher absolute difference in DeepLOF score indicates a stronger impact of genomic features on the inference of LOF intolerance. Each dot represents a gene. The blue and grey curves represent the fit of the generalized additive model with integrated smoothness and its 95% confidence interval [66]