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Tax4Fun：从宏基因组16S rRNA数据预测功能概况。

Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data.

作者信息

Aßhauer Kathrin P, Wemheuer Bernd, Daniel Rolf, Meinicke Peter

机构信息

Department of Bioinformatics and.

Department of Genomic and Applied Microbiology and Göttingen Genomics Laboratory, Institute of Microbiology and Genetics, Georg-August-University Göttingen, 37077 Göttingen, Germany.

出版信息

Bioinformatics. 2015 Sep 1;31(17):2882-4. doi: 10.1093/bioinformatics/btv287. Epub 2015 May 7.

DOI:10.1093/bioinformatics/btv287
PMID:25957349
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4547618/
Abstract

MOTIVATION

The characterization of phylogenetic and functional diversity is a key element in the analysis of microbial communities. Amplicon-based sequencing of marker genes, such as 16S rRNA, is a powerful tool for assessing and comparing the structure of microbial communities at a high phylogenetic resolution. Because 16S rRNA sequencing is more cost-effective than whole metagenome shotgun sequencing, marker gene analysis is frequently used for broad studies that involve a large number of different samples. However, in comparison to shotgun sequencing approaches, insights into the functional capabilities of the community get lost when restricting the analysis to taxonomic assignment of 16S rRNA data.

RESULTS

Tax4Fun is a software package that predicts the functional capabilities of microbial communities based on 16S rRNA datasets. We evaluated Tax4Fun on a range of paired metagenome/16S rRNA datasets to assess its performance. Our results indicate that Tax4Fun provides a good approximation to functional profiles obtained from metagenomic shotgun sequencing approaches.

AVAILABILITY AND IMPLEMENTATION

Tax4Fun is an open-source R package and applicable to output as obtained from the SILVAngs web server or the application of QIIME with a SILVA database extension. Tax4Fun is freely available for download at http://tax4fun.gobics.de/.

CONTACT

kasshau@gwdg.de

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

摘要

动机

系统发育和功能多样性的表征是微生物群落分析的关键要素。基于扩增子的标记基因测序，如16S rRNA测序，是一种强大的工具，可用于在高系统发育分辨率下评估和比较微生物群落的结构。由于16S rRNA测序比全宏基因组鸟枪法测序更具成本效益，标记基因分析经常用于涉及大量不同样本的广泛研究。然而，与鸟枪法测序方法相比，将分析局限于16S rRNA数据的分类学归属时，会丢失对群落功能能力的洞察。

结果

Tax4Fun是一个基于16S rRNA数据集预测微生物群落功能能力的软件包。我们在一系列配对的宏基因组/16S rRNA数据集上评估了Tax4Fun，以评估其性能。我们的结果表明，Tax4Fun能很好地近似从宏基因组鸟枪法测序方法获得的功能谱。

可用性和实现方式

Tax4Fun是一个开源R包，适用于从SILVAngs网络服务器获得的输出或应用带有SILVA数据库扩展的QIIME得到的输出。Tax4Fun可在http://tax4fun.gobics.de/免费下载。

联系方式

kasshau@gwdg.de

补充信息

补充数据可在《生物信息学》在线获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22b9/4547618/043e7e68eeed/btv287f1p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22b9/4547618/043e7e68eeed/btv287f1p.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22b9/4547618/043e7e68eeed/btv287f1p.jpg

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