MeSS和assembly_finder：一个用于计算机模拟宏基因组样本生成的工具包。

MeSS and assembly_finder: a toolkit for in silico metagenomic sample generation.

作者信息

Chaabane Farid, Pillonel Trestan, Bertelli Claire

机构信息

Institute of Microbiology, Lausanne University Hospital and University of Lausanne, Lausanne, 1011, Switzerland.

出版信息

Bioinformatics. 2024 Dec 26;41(1). doi: 10.1093/bioinformatics/btae760.

DOI:10.1093/bioinformatics/btae760

PMID:39739308

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11755095/

Abstract

SUMMARY

The intrinsic complexity of the microbiota combined with technical variability render shotgun metagenomics challenging to analyze for routine clinical or research applications. In silico data generation offers a controlled environment allowing for example to benchmark bioinformatics tools, to optimize study design, statistical power, or to validate targeted applications. Here, we propose assembly_finder and the Metagenomic Sequence Simulator (MeSS), two easy-to-use Bioconda packages, as part of a benchmarking toolkit to download genomes and simulate shotgun metagenomics samples, respectively. Outperforming existing tools in speed while requiring less memory, MeSS reproducibly generates accurate complex communities based on a list of taxonomic ranks and their abundance.

AVAILABILITY AND IMPLEMENTATION

All code is released under MIT License and is available on https://github.com/metagenlab/MeSS and https://github.com/metagenlab/assembly_finder.

摘要

微生物群的内在复杂性加上技术变异性，使得鸟枪法宏基因组学在常规临床或研究应用中的分析具有挑战性。计算机模拟数据生成提供了一个可控环境，例如可用于对生物信息学工具进行基准测试、优化研究设计、统计功效，或验证靶向应用。在这里，我们提出了assembly_finder和宏基因组序列模拟器（MeSS）这两个易于使用的Bioconda软件包，作为基准测试工具包的一部分，分别用于下载基因组和模拟鸟枪法宏基因组学样本。MeSS在速度上优于现有工具，同时所需内存更少，它能根据分类等级及其丰度列表可重复地生成准确的复杂群落。