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. 2021 Jan 6;22:6. doi: 10.1186/s12859-020-03921-8

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© The Author(s) 2021

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. 5 — Comparison of extracted features by DIABLO (mixOmics), multi-WGCNA (MiBiOmics) and multiple co-inertia analyses (MiBiOmics). To compare the performance of each method, a gene enrichment analysis was performed using ClusterProfiler [28] and the DisGenNet (DGM) database [29]. a Diseases annotations from the DGM database and their corresponding genes associated to each subset of mRNA extracted features (DIABLO in yellow, multi-WGCNA in pink and Multiple co-inertia analysis in blue). b Diseases annotations from the DGM database associated to each subset of validated targeted genes by miRNA extracted features (DIABLO in yellow, multi-WGCNA in pink and multiple co-inertia analysis in blue). c Disease annotations from the DGM database and their corresponding proteins associated to each subset of protein extracted features (DIABLO in yellow, multi-WGCNA in pink and Multiple co-inertia analysis in blue). In each plot, the side bar plot indicates the proportion of breast cancer related annotations compare to the other pathologies associated terms