title: BioMaS: a modular pipeline for Bioinformatic analysis of Metagenomic AmpliconS.
abstract: BACKGROUND
  Substantial advances in microbiology, molecular evolution and biodiversity have been carried out in recent years thanks to Metagenomics, which allows to unveil the composition and functions of mixed microbial communities in any environmental niche. If the investigation is aimed only at the microbiome taxonomic structure, a target-based metagenomic approach, here also referred as Meta-barcoding, is generally applied. This approach commonly involves the selective amplification of a species-specific genetic marker (DNA meta-barcode) in the whole taxonomic range of interest and the exploration of its taxon-related variants through High-Throughput Sequencing (HTS) technologies. The accessibility to proper computational systems for the large-scale bioinformatic analysis of HTS data represents, currently, one of the major challenges in advanced Meta-barcoding projects.
  
  
  RESULTS
  BioMaS (Bioinformatic analysis of Metagenomic AmpliconS) is a new bioinformatic pipeline designed to support biomolecular researchers involved in taxonomic studies of environmental microbial communities by a completely automated workflow, comprehensive of all the fundamental steps, from raw sequence data upload and cleaning to final taxonomic identification, that are absolutely required in an appropriately designed Meta-barcoding HTS-based experiment. In its current version, BioMaS allows the analysis of both bacterial and fungal environments starting directly from the raw sequencing data from either Roche 454 or Illumina HTS platforms, following two alternative paths, respectively. BioMaS is implemented into a public web service available at https://recasgateway.ba.infn.it/ and is also available in Galaxy at http://galaxy.cloud.ba.infn.it:8080 (only for Illumina data).
  
  
  CONCLUSIONS
  BioMaS is a friendly pipeline for Meta-barcoding HTS data analysis specifically designed for users without particular computing skills. A comparative benchmark, carried out by using a simulated dataset suitably designed to broadly represent the currently known bacterial and fungal world, showed that BioMaS outperforms QIIME and MOTHUR in terms of extent and accuracy of deep taxonomic sequence assignments.
authors.affiliation: Institute of Biomembranes and Bioenergetics, Consiglio Nazionale delle Ricerche, via Amendola 165/A, Bari, 70126, Italy. b.fosso@ibbe.cnr.it.
authors.forename: Bruno
authors.initials: B
authors.lastname: Fosso
authors.affiliation: Institute of Biomembranes and Bioenergetics, Consiglio Nazionale delle Ricerche, via Amendola 165/A, Bari, 70126, Italy. m.santamaria@ibbe.cnr.it.
authors.forename: Monica
authors.initials: M
authors.lastname: Santamaria
authors.affiliation: Institute of Biomembranes and Bioenergetics, Consiglio Nazionale delle Ricerche, via Amendola 165/A, Bari, 70126, Italy. marzano.marinella@gmail.com.
authors.forename: Marinella
authors.initials: M
authors.lastname: Marzano
authors.affiliation: Algorithms, Bioinformatics, Complexity and Formal Methods Research Group, Technical University of Catalonia, E-08034, Barcelona, Spain. dalonso@cs.upc.edu.
authors.forename: Daniel
authors.initials: D
authors.lastname: Alonso-Alemany
authors.affiliation: Algorithms, Bioinformatics, Complexity and Formal Methods Research Group, Technical University of Catalonia, E-08034, Barcelona, Spain. valiente@cs.upc.edu.
authors.forename: Gabriel
authors.initials: G
authors.lastname: Valiente
authors.affiliation: National Institute of Nuclear Physics, via E. Orabona 4, Bari, 70125, Italy. giacinto.donvito@ba.infn.it.
authors.forename: Giacinto
authors.initials: G
authors.lastname: Donvito
authors.affiliation: National Institute of Nuclear Physics, via E. Orabona 4, Bari, 70125, Italy. Alfonso.Monaco@ba.infn.it.
authors.forename: Alfonso
authors.initials: A
authors.lastname: Monaco
authors.affiliation: National Institute of Nuclear Physics, via E. Orabona 4, Bari, 70125, Italy. Pasquale.Notarangelo@ba.infn.it.
authors.forename: Pasquale
authors.initials: P
authors.lastname: Notarangelo
authors.affiliation: Institute of Biomembranes and Bioenergetics, Consiglio Nazionale delle Ricerche, via Amendola 165/A, Bari, 70126, Italy. graziano.pesole@uniba.it.|Department of Biosciences, Biotechnology and Biopharmaceutics, University of Bari "A. Moro", via E. Orabona 4, Bari, 70125, Italy. graziano.pesole@uniba.it.|Center of Excellence in Comparative Genomics, University of Bari "A. Moro", via E. Orabona, 4, Bari, 70125, Italy. graziano.pesole@uniba.it.
authors.forename: Graziano
authors.initials: G
authors.lastname: Pesole
mesh_terms: D001419:Bacteria / Q000235:genetics*; D044822:Biodiversity; D019295:Computational Biology / Q000379:methods*; D005658:Fungi / Q000235:genetics*; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D056186:Metagenomics; D012984:Software