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分类学家:一个用于通用病原体检测和宿主mRNA表达谱分析的交互式宏基因组学分析门户。

Taxonomer: an interactive metagenomics analysis portal for universal pathogen detection and host mRNA expression profiling.

作者信息

Flygare Steven, Simmon Keith, Miller Chase, Qiao Yi, Kennedy Brett, Di Sera Tonya, Graf Erin H, Tardif Keith D, Kapusta Aurélie, Rynearson Shawn, Stockmann Chris, Queen Krista, Tong Suxiang, Voelkerding Karl V, Blaschke Anne, Byington Carrie L, Jain Seema, Pavia Andrew, Ampofo Krow, Eilbeck Karen, Marth Gabor, Yandell Mark, Schlaberg Robert

机构信息

Department of Human Genetics, University of Utah, Salt Lake City, UT, USA.

Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA.

出版信息

Genome Biol. 2016 May 26;17(1):111. doi: 10.1186/s13059-016-0969-1.

Abstract

BACKGROUND

High-throughput sequencing enables unbiased profiling of microbial communities, universal pathogen detection, and host response to infectious diseases. However, computation times and algorithmic inaccuracies have hindered adoption.

RESULTS

We present Taxonomer, an ultrafast, web-tool for comprehensive metagenomics data analysis and interactive results visualization. Taxonomer is unique in providing integrated nucleotide and protein-based classification and simultaneous host messenger RNA (mRNA) transcript profiling. Using real-world case-studies, we show that Taxonomer detects previously unrecognized infections and reveals antiviral host mRNA expression profiles. To facilitate data-sharing across geographic distances in outbreak settings, Taxonomer is publicly available through a web-based user interface.

CONCLUSIONS

Taxonomer enables rapid, accurate, and interactive analyses of metagenomics data on personal computers and mobile devices.

摘要

背景

高通量测序能够对微生物群落进行无偏分析、检测通用病原体以及宿主对传染病的反应。然而,计算时间和算法不准确阻碍了其应用。

结果

我们展示了Taxonomer,这是一个用于全面宏基因组数据分析和交互式结果可视化的超快速网络工具。Taxonomer的独特之处在于提供基于核苷酸和蛋白质的综合分类以及同时进行宿主信使核糖核酸(mRNA)转录本分析。通过实际案例研究,我们表明Taxonomer能检测到先前未识别的感染,并揭示抗病毒宿主mRNA表达谱。为便于在疫情爆发环境中跨地理距离共享数据,Taxonomer可通过基于网络的用户界面公开获取。

结论

Taxonomer能够在个人电脑和移动设备上对宏基因组数据进行快速、准确和交互式分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed29/4880956/709b0c1e674a/13059_2016_969_Fig1_HTML.jpg

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