美国哈佛医学院刘洋彧、加州大学圣迭戈分校Rob Knight等研究人员合作对宏基因组分析方法进行了基准校正。2021年5月13日，《自然—方法学》杂志在线发表了这项成果。

据研究人员介绍，准确的微生物鉴定和丰度估算对于宏基因组学分析至关重要。目前已经开发出各种用于宏基因组数据的分类和分类学概况估计的方法，广泛地称为宏基因组分析法。尽管如此，宏基因组分析法的基准测试仍然具有挑战性，因为某些工具旨在报告相对序列丰度，而其他工具则报告相对生物分类丰度。

研究人员发现，在对宏基因组分析法进行基准测试时，如果忽略相对丰度类型之间的这种区别，可以得出令人误解的结论。此外，研究人员提供了令人信服的证据，即互换序列的丰度和分类学的丰度将影响每个样本的概括性统计和跨样本的比较。因此，研究人员认为，微生物组研究领域在对宏基因组分析法进行基准测试时，应注意因该问题而引起的潜在误导性生物学结论，即通过仔细考虑经过分析和解释的丰度数据的类型，并明确说明用于宏基因组分析的策略。

附：英文原文

Title: Challenges in benchmarking metagenomic profilers

Author: Zheng Sun, Shi Huang, Meng Zhang, Qiyun Zhu, Niina Haiminen, Anna Paola Carrieri, Yoshiki Vzquez-Baeza, Laxmi Parida, Ho-Cheol Kim, Rob Knight, Yang-Yu Liu

Issue&Volume: 2021-05-13

Abstract: Accurate microbial identification and abundance estimation are crucial for metagenomics analysis. Various methods for classification of metagenomic data and estimation of taxonomic profiles, broadly referred to as metagenomic profilers, have been developed. Nevertheless, benchmarking of metagenomic profilers remains challenging because some tools are designed to report relative sequence abundance while others report relative taxonomic abundance. Here we show how misleading conclusions can be drawn by neglecting this distinction between relative abundance types when benchmarking metagenomic profilers. Moreover, we show compelling evidence that interchanging sequence abundance and taxonomic abundance will influence both per-sample summary statistics and cross-sample comparisons. We suggest that the microbiome research community pay attention to potentially misleading biological conclusions arising from this issue when benchmarking metagenomic profilers, by carefully considering the type of abundance data that were analyzed and interpreted and clearly stating the strategy used for metagenomic profiling. Many computational tools for metagenomic profiling have been developed, with different algorithms and features. This analysis shows that, when comparing these tools, the distinction of different types of relative sequence abundance should be taken into consideration.

DOI: 10.1038/s41592-021-01141-3

Source: https://www.nature.com/articles/s41592-021-01141-3