Under the current deluge of omics, module networks distinctively emerge as methods capable of not only identifying inherently coherent groups (modules), thus reducing dimensionality, but also hypothesizing cause–effect relationships between modules and their regulators. Module networks were first designed in the transcriptomic era and further exploited in the multi-omic context to assess (for example) miRNA regulation of gene expression. Despite a number of available implementations, expansion of module networks to other omics is constrained by a limited characterization of the solutions' (modules plus regulators) accuracy and stability – an immediate need for the better characterization of molecular biology complexity in silico. We hence carefully assessed for LemonTree – a popular and open source module network implementation – the dependency of the software performances (sensitivity, specificity, false discovery rate, solutions' stability) on the input parameters and on the data quality (sample size, expression noise) based on synthetic and real data. In the process, we uncovered and fixed an issue in the code for the regulator assignment procedure. We concluded this evaluation with a table of recommended parameter settings. Finally, we applied these recommended settings to gut-intestinal metagenomic data from rheumatoid arthritis patients, to characterize the evolution of the gut-intestinal microbiome under different pharmaceutical regimens (methotrexate and prednisone) and we inferred innovative clinical recommendations with therapeutic potential, based on the computed module network.

中文翻译：

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剖析模块网络实现“ LemonTree”：增强宏基因组学的应用以及自身免疫性疾病的翻译

在当前的组学泛滥中，模块网络作为一种方法不仅可以识别固有相关的组（模块），从而降低了维数，而且还可以假设模块及其调节器之间的因果关系，因此脱颖而出。首先在转录组时代设计模块网络，然后在多组学背景下进一步利用它来评估（例如）miRNA对基因表达的调控。尽管有许多可用的实现方式，但模块网络向其他组学的扩展受到解决方案（模块加调节器）准确性和稳定性的有限表征的限制-迫切需要更好地表征分子生物学在计算机上的复杂性。因此，我们仔细评估了LemonTree（一种流行的开源模块网络实施方案）是否依赖于软件性能（灵敏度，特异性，错误发现率，解决方案的稳定性）对输入参数和数据质量（样本量，表达噪声）的依赖性。 ）基于综合和真实数据。在此过程中，我们发现并修复了调节器分配程序代码中的一个问题。我们以推荐参数设置表结束了该评估。最后，我们将这些推荐设置应用于类风湿性关节炎患者的肠-肠宏基因组学数据，以表征不同药物疗法（甲氨蝶呤和泼尼松）下肠-肠微生物组的演变，并推断出具有治疗潜力的创新性临床建议，