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. 2019 Feb 28;2:83. doi: 10.1038/s42003-019-0333-6

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© The Author(s) 2019

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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 1 — Module detection algorithm. By processing the entire collection of microbial genomes considered in this study, antiSMASH predicted tens of thousands BGCs. OrthoMCL was then used for the smCOG annotation. Next, these smCOGs were organised into a network where two smCOGs are connected only if they share a significant number of adjacency or colocalization interactions. Fully connected sub-graphs (cliques) are considered as putative biosynthetic modules