Impact of simulation and reference catalogues on the evaluation of taxonomic profiling pipelines.

IF 4 2区 生物学 Q1 GENETICS & HEREDITY
Vadim Puller, Florian Plaza Oñate, Edi Prifti, Raynald de Lahondès
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引用次数: 0

Abstract

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).

模拟目录和参考目录对分类分析管道评价的影响。
微生物组图谱分析工具依赖于参考目录,这对其性能有很大影响。然而,对它们进行比较具有挑战性,这主要是由于它们的本地目录存在差异。在本研究中,我们提出了一个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,而是将结果转化为通用参考,以便在其本地环境中使用这些工具。具体来说,我们对肠道微生物组样本进行了两次实际模拟,每次模拟都基于特定的分类剖析器,并使用两种不同的分类参考来预测其结果,即基因组分类数据库和人类胃肠道统一基因组。为了证明使用这种框架的重要性,我们评估了四种已建立的剖析器,以及模拟和共同分类参考对这些剖析器感知性能的影响。最后,我们提供了加强未来人类微生物组生态系统剖析器比较的指导原则:(i) 使用或创建适合您的生物环境(BC)的现实模拟;(ii) 确定适合您的 BC 且独立于剖析器所用目录的共同特征空间;(iii) 应用一套全面的指标,涵盖准确性(灵敏度/精确度)、总体代表性(丰富度/香农)和量化(UniFrac 和/或艾奇逊距离)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Microbial Genomics
Microbial Genomics Medicine-Epidemiology
CiteScore
6.60
自引率
2.60%
发文量
153
审稿时长
12 weeks
期刊介绍: Microbial Genomics (MGen) is a fully open access, mandatory open data and peer-reviewed journal publishing high-profile original research on archaea, bacteria, microbial eukaryotes and viruses.
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