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首页> 外文期刊>BMC Bioinformatics >BugSeq: a highly accurate cloud platform for long-read metagenomic analyses
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BugSeq: a highly accurate cloud platform for long-read metagenomic analyses

机译:Bugseq:一种高度准确的云平台,用于长读的Metagenomic分析

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摘要

As the use of nanopore sequencing for metagenomic analysis increases, tools capable of performing long-read taxonomic classification (ie. determining the composition of a sample) in a fast and accurate manner are needed. Existing tools were either designed for short-read data (eg. Centrifuge), take days to analyse modern sequencer outputs (eg. MetaMaps) or suffer from suboptimal accuracy (eg. CDKAM). Additionally, all tools require command line expertise and do not scale in the cloud. We present BugSeq, a novel, highly accurate metagenomic classifier for nanopore reads. We evaluate BugSeq on simulated data, mock microbial communities and real clinical samples. On the ZymoBIOMICS Even and Log communities, BugSeq (F1?=?0.95 at species level) offers better read classification than MetaMaps (F1?=?0.89–0.94) in a fraction of the time. BugSeq significantly improves on the accuracy of Centrifuge (F1?=?0.79–0.93) and CDKAM (F1?=?0.91–0.94) while offering competitive run times. When applied to 41 samples from patients with lower respiratory tract infections, BugSeq produces greater concordance with microbiological culture and qPCR compared with “What’s In My Pot” analysis. BugSeq is deployed to the cloud for easy and scalable long-read metagenomic analyses. BugSeq is freely available for non-commercial use at https://bugseq.com/free .
机译:由于使用纳米孔测序进行偏见分析,因此需要以快速和准确的方式执行长读分类分类分类的工具(即确定样品的组成)。现有工具设计用于短读数据(例如离心机),需要数天才能分析现代定序器输出(例如,Metapaps)或遭受次优准确度(例如CDKAM)。此外,所有工具都需要命令行专业知识,并不在云中缩放。我们呈现Bugseq,一种新型高精度的纳米孔读数的均衡器。我们评估模拟数据,模拟微生物群落和真实临床样品的Bugseq。在ZyMoomics偶数和日志社区中,Bugseq(F1?= 0.95,物种级别)提供比Metamaps(F1?= 0.89-0.94)更好地读取分类。 BUGSEQ显着提高了离心机的准确性(F1?= 0.79-0.93)和CDKAM(F1?= 0.91-0.94),同时提供竞争运行时间。当患有患者患者患者患者的41个样本时,BUGSEQ与微生物培养和QPCR产生更大的一致性,而QPCR与“我的锅中有什么”分析相比。 Bugseq部署到云以实现简单且可扩展的长读元焦虑分析。 Bugseq在https://bugseq.com/free上自由地提供非商业用途。

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