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Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
Published on: October 15, 2019
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Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data.
Kathrin P Aßhauer1, Bernd Wemheuer2, Rolf Daniel2
1Department of Bioinformatics and.
Bioinformatics (Oxford, England)
|May 10, 2015
Summary
Tax4Fun predicts microbial community functions from 16S rRNA gene sequencing data. This cost-effective method approximates functional profiles derived from metagenomic shotgun sequencing, aiding microbial ecology research.
Area of Science:
- Microbial ecology and bioinformatics.
- Computational biology and genomics.
Background:
- Characterizing microbial community phylogenetic and functional diversity is crucial.
- 16S rRNA gene sequencing offers cost-effective phylogenetic resolution for large sample studies.
- 16S rRNA analysis alone limits insights into functional capabilities compared to shotgun sequencing.
Purpose of the Study:
- To introduce Tax4Fun, a software package for predicting microbial community functional capabilities.
- To evaluate the performance of Tax4Fun using paired metagenomic and 16S rRNA datasets.
Main Methods:
- Tax4Fun is an open-source R package.
- It processes 16S rRNA data, compatible with SILVAngs and QIIME outputs using SILVA databases.
- The software predicts functional profiles based on taxonomic assignments.
Main Results:
- Tax4Fun was evaluated on paired metagenome/16S rRNA datasets.
- The results demonstrate that Tax4Fun provides a good approximation of functional profiles.
- It effectively estimates functional capabilities comparable to metagenomic shotgun sequencing.
Conclusions:
- Tax4Fun enables functional prediction from 16S rRNA data, bridging a gap in microbial community analysis.
- It offers a cost-effective alternative for inferring functional potential in large-scale studies.
- The tool enhances the utility of 16S rRNA sequencing for functional insights.
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