PathoScope 2.0: a complete computational framework for strain identification in environmental or clinical sequencing samples.
PathoScope 2.0: a complete computational framework for strain identification in environmental or clinical sequencing samples.
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DOI：
10.1186/2049-2618-2-33
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发表时间：
2014
期刊：
影响因子：
15.5
通讯作者：
Johnson WE
中科院分区：
文献类型：
--
作者：
Hong C;Manimaran S;Shen Y;Perez-Rogers JF;Byrd AL;Castro-Nallar E;Crandall KA;Johnson WE
测序技术的最新创新为研究人员提供了以前所未有的分辨率快速表征环境或临床样品中微生物含量的能力。这些方法产生了丰富的信息，为环境和人类健康的微生物生态学提供了新的见解。然而，这些基于测序的方法产生需要高效且敏感的计算分析工作流程的大型且复杂的数据集。最近出现了许多用于分析宏基因组测序数据的工具，然而，这些方法经常受到特异性、效率的问题的困扰，并且通常不包括完整的宏基因组分析框架。我们提出了PathoScope 2.0，这是一个完整的生物信息学框架，用于快速准确地定量环境或临床样本宏基因组测序数据中存在的单个微生物菌株的读数比例。流水线执行所有必要的计算分析步骤;包括参考基因组文库提取和索引、读段质量控制和比对、菌株鉴定以及结果的总结和注释。我们使用模拟数据和2011年志贺菌大肠杆菌O 104：H4爆发的数据对PathoScope 2.0进行了严格评估。结果表明，PathoScope 2.0是一种完整、高灵敏度和高效的宏基因组分析方法，在范围、速度和准确性方面优于其他方法。PathoScope 2.0管道软件可在http://sourceforge.net/projects/pathoscope/免费下载。
Recent innovations in sequencing technologies have provided researchers with the ability to rapidly characterize the microbial content of an environmental or clinical sample with unprecedented resolution. These approaches are producing a wealth of information that is providing novel insights into the microbial ecology of the environment and human health. However, these sequencing-based approaches produce large and complex datasets that require efficient and sensitive computational analysis workflows. Many recent tools for analyzing metagenomic-sequencing data have emerged, however, these approaches often suffer from issues of specificity, efficiency, and typically do not include a complete metagenomic analysis framework. We present PathoScope 2.0, a complete bioinformatics framework for rapidly and accurately quantifying the proportions of reads from individual microbial strains present in metagenomic sequencing data from environmental or clinical samples. The pipeline performs all necessary computational analysis steps; including reference genome library extraction and indexing, read quality control and alignment, strain identification, and summarization and annotation of results. We rigorously evaluated PathoScope 2.0 using simulated data and data from the 2011 outbreak of Shiga-toxigenic Escherichia coli O104:H4. The results show that PathoScope 2.0 is a complete, highly sensitive, and efficient approach for metagenomic analysis that outperforms alternative approaches in scope, speed, and accuracy. The PathoScope 2.0 pipeline software is freely available for download at: http://sourceforge.net/projects/pathoscope/.
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影响因子：
48
作者：
Langmead, Ben;Salzberg, Steven L.
通讯作者：
Salzberg, Steven L.
DOI：
10.1093/bioinformatics/btt389
发表时间：
2013-09-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Ames SK;Hysom DA;Gardner SN;Lloyd GS;Gokhale MB;Allen JE
通讯作者：
Allen JE
影响因子：
48
作者：
Segata, Nicola;Waldron, Levi;Ballarini, Annalisa;Narasimhan, Vagheesh;Jousson, Olivier;Huttenhower, Curtis
通讯作者：
Huttenhower, Curtis
DOI：
10.1056/nejmoa1211115
发表时间：
2013-08-08
期刊：
The New England journal of medicine
影响因子：
--
作者：
Bhatt AS;Freeman SS;Herrera AF;Pedamallu CS;Gevers D;Duke F;Jung J;Michaud M;Walker BJ;Young S;Earl AM;Kostic AD;Ojesina AI;Hasserjian R;Ballen KK;Chen YB;Hobbs G;Antin JH;Soiffer RJ;Baden LR;Garrett WS;Hornick JL;Marty FM;Meyerson M
通讯作者：
Meyerson M
影响因子：
120.7
作者：
Loman, Nicholas J.;Constantinidou, Chrystala;Pallen, Mark J.
通讯作者：
Pallen, Mark J.