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Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
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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
PubMed
Summary
This summary is machine-generated.

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.

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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.