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. 2020 Aug 31;13:123. doi: 10.1186/s12920-020-00768-z

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© The Author(s) 2020

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 — Consistent evidence of childhood-onset asthma-relevant genes based on independent datasets and techniques. a Venn diagram of three identified childhood-onset asthma-relevant gene sets: Dataset #1 based on MAGMA analysis of GWAS summary data (P value of each gene with Bonferroni correction), Dataset #2 based on Sherlock integrative analysis of integrating GWAS and Zeller et al. eQTL data (P value of each gene with FDR correction), and Dataset #3 based on Sherlock analysis of integrating GWAS and Dixon et al. eQTL data (raw P value of each gene was applied). b Computer-based permutation analysis of 10⁵ times for the comparison of genes with adjusted P-values from Dataset #2 with that from MAGMA analysis. c Computer-based permutation analysis of 10⁵ times for the comparison of genes with adjusted P-values from Dataset #2 with that from Dataset #3