Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data

被引：1340

作者：

Asshauer, Kathrin P. ^{[1
]}

Wemheuer, Bernd ^{[2
,3
]}

Daniel, Rolf ^{[2
,3
]}

Meinicke, Peter ^{[1
]}

机构：

[1] Univ Gottingen, Inst Microbiol & Genet, Dept Bioinformat, D-37077 Gottingen, Germany

[2] Univ Gottingen, Inst Microbiol & Genet, Dept Genom & Appl Microbiol, D-37077 Gottingen, Germany

[3] Univ Gottingen, Inst Microbiol & Genet, Gottingen Genom Lab, D-37077 Gottingen, Germany

来源：

BIOINFORMATICS | 2015年 / 31卷 / 17期

关键词：

MICROBIAL COMMUNITIES;

D O I：

10.1093/bioinformatics/btv287

中图分类号：

Q5 [生物化学];

学科分类号：

070307 [化学生物学];

摘要：

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.

引用

页码：2882 / 2884

页数：3

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