In silico benchmarking of metagenomic tools for coding sequence detection reveals the limits of sensitivity and precision.
In silico benchmarking of metagenomic tools for coding sequence detection reveals the limits of sensitivity and precision.
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DOI：
10.1186/s12859-020-03802-0
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发表时间：
2020-10-15
影响因子：
3
通讯作者：
Minot SS
中科院分区：
文献类型：
--
作者：
Golob JL;Minot SS
高通量测序可以通过对存在于微生物群落宏基因组中的蛋白质编码序列（CDS）进行编目来建立微生物群落的功能能力。用于从全基因组鸟枪测序中识别CDS的不同计算方法的相对性能尚未完全确定。 在这里，我们提出了一个自动化的基准工作流程，使用合成鸟枪测序读取，我们知道真正的CDS内容的基础社区，以确定相对性能（灵敏度，阳性预测值或PPV，和计算效率）的不同宏基因组分析工具提取的CDS内容的微生物群落。基于组装的方法受到覆盖深度的限制，在< 5X测序深度下对CDS的灵敏度差，但具有优异的PPV。基于映射的技术在低覆盖深度下更敏感，但可能与PPV斗争。我们还描述了一种基于期望最大化的迭代算法方法，我们成功地提高了PPV的映射为基础的技术，同时保持改进的灵敏度和计算效率。我们的基准测试方法揭示了组装与基于组装的方法的权衡，以及当人们希望提取微生物群落的蛋白质编码能力时特定实施的相对性能。
High-throughput sequencing can establish the functional capacity of a microbial community by cataloging the protein-coding sequences (CDS) present in the metagenome of the community. The relative performance of different computational methods for identifying CDS from whole-genome shotgun sequencing is not fully established. Here we present an automated benchmarking workflow, using synthetic shotgun sequencing reads for which we know the true CDS content of the underlying communities, to determine the relative performance (sensitivity, positive predictive value or PPV, and computational efficiency) of different metagenome analysis tools for extracting the CDS content of a microbial community. Assembly-based methods are limited by coverage depth, with poor sensitivity for CDS at < 5X depth of sequencing, but have excellent PPV. Mapping-based techniques are more sensitive at low coverage depths, but can struggle with PPV. We additionally describe an expectation maximization based iterative algorithmic approach which we show to successfully improve the PPV of a mapping based technique while retaining improved sensitivity and computational efficiency. Our benchmarking approach reveals the trade-offs of assembly versus alignment-based approaches and the relative performance of specific implementations when one wishes to extract the protein coding capacity of microbial communities.
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影响因子：
12.3
作者：
McIntyre ABR;Ounit R;Afshinnekoo E;Prill RJ;Hénaff E;Alexander N;Minot SS;Danko D;Foox J;Ahsanuddin S;Tighe S;Hasan NA;Subramanian P;Moffat K;Levy S;Lonardi S;Greenfield N;Colwell RR;Rosen GL;Mason CE
通讯作者：
Mason CE
影响因子：
64.8
作者：
通讯作者：
--
影响因子：
4.4
作者：
Schloss, Patrick D.;Westcott, Sarah L.;Weber, Carolyn F.
通讯作者：
Weber, Carolyn F.
影响因子：
7
作者：
Nayfach S;Rodriguez-Mueller B;Garud N;Pollard KS
通讯作者：
Pollard KS
影响因子：
1.7
作者：
Bankevich, Anton;Nurk, Sergey;Pevzner, Pavel A.
通讯作者：
Pevzner, Pavel A.