Suppr超能文献

宏基因组分析工具的准确性和速度评估。

An evaluation of the accuracy and speed of metagenome analysis tools.

作者信息

Lindgreen Stinus, Adair Karen L, Gardner Paul P

机构信息

Biomolecular Interaction Centre, University of Canterbury, Christchurch, New Zealand.

School of Biological Sciences, University of Canterbury, Christchurch, New Zealand.

出版信息

Sci Rep. 2016 Jan 18;6:19233. doi: 10.1038/srep19233.

Abstract

Metagenome studies are becoming increasingly widespread, yielding important insights into microbial communities covering diverse environments from terrestrial and aquatic ecosystems to human skin and gut. With the advent of high-throughput sequencing platforms, the use of large scale shotgun sequencing approaches is now commonplace. However, a thorough independent benchmark comparing state-of-the-art metagenome analysis tools is lacking. Here, we present a benchmark where the most widely used tools are tested on complex, realistic data sets. Our results clearly show that the most widely used tools are not necessarily the most accurate, that the most accurate tool is not necessarily the most time consuming, and that there is a high degree of variability between available tools. These findings are important as the conclusions of any metagenomics study are affected by errors in the predicted community composition and functional capacity. Data sets and results are freely available from http://www.ucbioinformatics.org/metabenchmark.html.

摘要

宏基因组研究正变得越来越普遍,为微生物群落提供了重要见解,这些群落涵盖了从陆地和水生生态系统到人类皮肤和肠道等各种环境。随着高通量测序平台的出现,大规模鸟枪法测序方法的使用现在已经很常见。然而,缺乏对最先进的宏基因组分析工具进行全面独立的基准测试。在这里,我们展示了一个基准测试,其中最广泛使用的工具在复杂、现实的数据集上进行了测试。我们的结果清楚地表明,使用最广泛的工具不一定是最准确的,最准确的工具不一定是最耗时的,并且现有工具之间存在高度变异性。这些发现很重要,因为任何宏基因组学研究的结论都会受到预测群落组成和功能能力错误的影响。数据集和结果可从http://www.ucbioinformatics.org/metabenchmark.html免费获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a627/4726098/c7fc208ecc5f/srep19233-f1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验