title: Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data.
abstract: BACKGROUND
  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.
  
  
  METHODS
  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/.
  
  
  BACKGROUND
  kasshau@gwdg.de
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Department of Bioinformatics and.
authors.forename: Kathrin P
authors.initials: KP
authors.lastname: Aßhauer
authors.affiliation: Department of Genomic and Applied Microbiology and Göttingen Genomics Laboratory, Institute of Microbiology and Genetics, Georg-August-University Göttingen, 37077 Göttingen, Germany.
authors.forename: Bernd
authors.initials: B
authors.lastname: Wemheuer
authors.affiliation: Department of Genomic and Applied Microbiology and Göttingen Genomics Laboratory, Institute of Microbiology and Genetics, Georg-August-University Göttingen, 37077 Göttingen, Germany.
authors.forename: Rolf
authors.initials: R
authors.lastname: Daniel
authors.affiliation: Department of Bioinformatics and.
authors.forename: Peter
authors.initials: P
authors.lastname: Meinicke
mesh_terms: D001419:Bacteria / Q000145:classification / Q000235:genetics*; D019295:Computational Biology / Q000379:methods*; D016208:Databases, Factual; D030561:Databases, Nucleic Acid; D005798:Genes, Bacterial / Q000235:genetics*; D005819:Genetic Markers; D054892:Metagenome; D056186:Metagenomics / Q000379:methods*; D010802:Phylogeny; D012329:RNA, Bacterial / Q000235:genetics; D012336:RNA, Ribosomal, 16S / Q000235:genetics*; D017423:Sequence Analysis, RNA / Q000379:methods*; D012984:Software
chemical_list: D005819:Genetic Markers; D012329:RNA, Bacterial; D012336:RNA, Ribosomal, 16S