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. 2023 Jul 24;10:9. doi: 10.1186/s40575-023-00132-1

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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. 1 — Mixed linear model association analysis. A: A Manhattan plot displaying the MLMA performed in GCTA. The association analysis was based on 94,697 SNP markers and 731 dogs (324 cases and 407 controls). The significance level (blue line) was set to 1.24 × 10^–05 using Bonferroni correction to adjust for multiple testing considering the LD, haploblock structure and number of independent SNPs after pruning the data. A second significance level (red line) was set to 5.28 × 10^–07, using Bonferroni correction to adjust for all markers in the data. B: A quantile–quantile (q-q) plot showing the expected p value against the observed p-values of the MLMA