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MegaPath-Nano: Accurate Compositional Analysis and Drug-level Antimicrobial Resistance Detection Software for Oxford Nanopore Long-read Metagenomics

机译:Megapath-nano:用于牛津纳米孔长读偏心眼学的准确的组成分析和药物水平抗菌性检测软件

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Accurate and sensitive taxonomic profiling is essential for any metagenomic analysis to reveal microbial community structure and for potential functional prediction. Antimicrobial resistance (AMR) detection is also a critical task in the clinical diagnosis of infection and antimicrobial therapy. By incorporating Oxford Nanopore Technologies (ONT) sequencing, users benefit from the high-confidence alignment of long reads for taxonomic classification, even among bacteria with similar genomes. Portable ONT devices, such as VolTRAX with MinION, allow short turnaround time for detection and can be used in a lightweight laboratory setting. However, error-prone ONT sequencing reads are still challenging for existing software for accurate taxonomic classification of microbes and detection of AMR down to the drug level. In this paper, we present MegaPath-Nano, the successor to NGS-based MegaPath. It is a high-precision compositional analysis software with drug-level AMR detection for ONT metagenomic sequencing data. MegaPath-Nano performs 1) thorough multi-level filtering against decoy and human reads while removing noisy alignments, 2) alignment-based taxonomic classification with RefSeq down to strain-level, with an alignment-reassignment algorithm to tackle the challenge of non-unique alignments, based on global alignment distribution, and 3) comprehensive downstream drug-level AMR detection, integrating five AMR databases. In our benchmarks using the Zymo metagenomic dataset, MegaPath-Nano performed better than other existing software for taxonomic classification. We also sequenced five real patient isolates using MinION to benchmark its performance of AMR detection. MegaPath-Nano was the most accurate and provided the most comprehensive output at both the drug and class level of AMR prediction against other state-of-the-art software. MegaPath-Nano is open-source and available at https://github.com/HKU-BAL/MegaPath-Nano.
机译:准确和敏感的分类分析性分析对于揭示微生物群落结构和潜在的功能预测来说是必不可少的偏见分析。抗微生物抗性(AMR)检测也是感染和抗微生物治疗的临床诊断中的关键任务。通过纳入牛津纳米孔技术(ONT)测序,即使在具有类似基因组的细菌中,用户也可以从长期读取的高度读取对分类分类的高置信对准。便携式ONT设备,例如Voltrax与矿物,允许短周转时间进行检测,可用于轻量级实验室设置。然而,容易出错的ONT测序读数仍然挑战现有的软件,以准确分类分类分类和检测到药物水平的AMR。在本文中,我们展示了基于NGS的Megapath的继承者的Megapath-nano。它是一种高精度的成分分析软件,具有用于ONT均衡数据的药水级AMR检测。 Megapath-nano执行1)彻底的多级过滤对诱饵和人类读取,同时消除嘈杂的对齐,2)将基于对准的分类分类分类与Refseq Down到应变级别,具有对准 - 重新分配算法来解决非唯一的挑战基于全局对准分布和3)综合下游药物级AMR检测,整合五个AMR数据库。在使用Zymo Metagenomic DataSet的基准中,Megapath-nano比其他现有的分类专用软件更好地执行。我们还使用小组测序五个真实患者隔离物,以基准其对AMR检测的性能进行基准。 Megapath-nano是最准确的,并提供了AMR预测的药物和阶级最全面的输出,对抗其他最先进的软件。 Megapath-nano是开源,可在https://github.com/hku-bal/megapath-nano提供。

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