Puller Vadim, Plaza Oñate Florian, Prifti Edi, de Lahondès Raynald
GMT Science 75 route de Lyons-La-Foret, Rouen F-76000, France.
IRD, Sorbonne Universit, Unit de Modlisation Mathmatique et Informatique des Systmes Complexes, UMMISCO, 32 Avenue Henri Varagnat, Bondy F-93143, France.
Microb Genom. 2025 Jan;11(1). doi: 10.1099/mgen.0.001330.
Microbiome profiling tools rely on reference catalogues, which significantly affect their performance. Comparing them is, however, challenging, mainly due to differences in their native catalogues. In this study, we present a novel standardized benchmarking framework that makes such comparisons more accurate. We decided not to customize databases but to translate results to a common reference to use the tools with their native environment. Specifically, we conducted two realistic simulations of gut microbiome samples, each based on a specific taxonomic profiler, and used two different taxonomic references to project their results, namely the Genome Taxonomy Database and the Unified Human Gastrointestinal Genome. To demonstrate the importance of using such a framework, we evaluated four established profilers as well as the impact of the simulations and that of the common taxonomic references on the perceived performance of these profilers. Finally, we provide guidelines to enhance future profiler comparisons for human microbiome ecosystems: (i) use or create realistic simulations tailored to your biological context (BC), (ii) identify a common feature space suited to your BC and independent of the catalogues used by the profilers and (iii) apply a comprehensive set of metrics covering accuracy (sensitivity/precision), overall representativity (richness/Shannon) and quantification (UniFrac and/or Aitchison distance).
微生物群落分析工具依赖于参考目录,这会显著影响其性能。然而,对它们进行比较具有挑战性,主要是由于其原生目录存在差异。在本研究中,我们提出了一种新颖的标准化基准框架,使此类比较更加准确。我们决定不定制数据库,而是将结果转换为通用参考,以便在工具的原生环境中使用。具体而言,我们对肠道微生物群落样本进行了两次逼真的模拟,每次模拟基于一种特定的分类分析器,并使用两种不同的分类参考来呈现其结果,即基因组分类数据库和统一人类胃肠道基因组。为了证明使用这种框架的重要性,我们评估了四种既定的分析器,以及模拟和通用分类参考对这些分析器性能感知的影响。最后,我们提供了一些指导方针,以加强未来对人类微生物群落生态系统分析器的比较:(i)使用或创建适合您的生物学背景(BC)的逼真模拟,(ii)确定适合您的BC且独立于分析器所使用目录的通用特征空间,以及(iii)应用一套全面的指标,涵盖准确性(敏感性/精确性)、整体代表性(丰富度/香农指数)和量化(非加权组平均法和/或艾奇逊距离)。