New bioinformatic resources for taxonomic assignment of metagenomic NGS data: BioMaS, ITSoneDB and SARMA
Update: 2014-03-31
Description
Co-authors: Bruno Fosso (Institute of Biomembranes and Bioenergetics, CNR, via Amendola 165/A, 70126 Bari, Italy), Mattia D’Antonio (CINECA, Roma), Gabriel Valiente (Algorithms, Bioinformatics, Complexity and Formal Methods Research Group, Technical University of Catalonia, E-08034, Barcelona, Spain), Giacinto Donvito (Institute national of Nuclear Physics, Via Orabona, 4, 70126 Bari, Italy), Alfonso Monaco (Institute national of Nuclear Physics, Via Orabona, 4, 70126 Bari, Italy), Pasquale Notarangelo (Institute national of Nuclear Physics, Via Orabona, 4, 70126 Bari, Italy), Giorgio Pietro Maggi (Institute national of Nuclear Physics, Via Orabona, 4, 70126 Bari, Italy and Politecnico of Bari, Via Orabona, 4, 70126 Bari), Graziano Pesole (Institute of Biomembranes and Bioenergetics, CNR, via Amendola 165/A, 70126 Bari, Italy and Department of Biosciences, Biotechnology and Pharmacological Sciences, University of Bari, Bari)
Substantial advances in molecular microbiology have been carried out in recent years thanks to Metagenomics. Next Generation Sequencing (NGS) technologies are massively supporting this approach but imply, at the same time, new hard challenges concerning the analysis of the huge amount of data they produce. In this scenario we present three new bioinformatic resources aimed at supporting molecular researches in advanced analyses of NGS metagenomic data. The first one is BioMaS (Bioinformatic analysis of Metagenomic ampliconS), a comprehensive pipeline for the taxonomic analyses of meta-barcode sequences. BioMaS, in its current version, allows the analysis of both bacterial and fungal populations through the processing of data obtained by Roche 454 or Illumina platforms. BioMaS will be soon implemented as a very friendly publicly available web-service. The second one is ITSoneDB, a curated collection of taxonomically annotated ITS1 sequences suitable for metagenomic studies of fungal communities. ITSoneDB is available at http://itsonedb.ba.itb.cnr.it/. Finally, SARMA (Species Assignment of Reads from Metagenomic Analysis), whose construction is still ongoing, has been designed for the taxonomic characterization of metagenomic data produced by shotgun NGS, particularly oriented towards the study of human or other host microbiomes. The pipeline in the first step carries out serial searches against human, bacteria, fungi, protozoa and virus reference sequences, and then reads uniquely mapping to the host are removed. In the second step the taxon assignment of all reads uniquely mapping to the above life domains is carried out. A webservice/Galaxy implementation of SARMA is currently in progress, enabling the usage of several heterogeneous computing infrastructure thus remarkably optimizing the computational load and run time.
Substantial advances in molecular microbiology have been carried out in recent years thanks to Metagenomics. Next Generation Sequencing (NGS) technologies are massively supporting this approach but imply, at the same time, new hard challenges concerning the analysis of the huge amount of data they produce. In this scenario we present three new bioinformatic resources aimed at supporting molecular researches in advanced analyses of NGS metagenomic data. The first one is BioMaS (Bioinformatic analysis of Metagenomic ampliconS), a comprehensive pipeline for the taxonomic analyses of meta-barcode sequences. BioMaS, in its current version, allows the analysis of both bacterial and fungal populations through the processing of data obtained by Roche 454 or Illumina platforms. BioMaS will be soon implemented as a very friendly publicly available web-service. The second one is ITSoneDB, a curated collection of taxonomically annotated ITS1 sequences suitable for metagenomic studies of fungal communities. ITSoneDB is available at http://itsonedb.ba.itb.cnr.it/. Finally, SARMA (Species Assignment of Reads from Metagenomic Analysis), whose construction is still ongoing, has been designed for the taxonomic characterization of metagenomic data produced by shotgun NGS, particularly oriented towards the study of human or other host microbiomes. The pipeline in the first step carries out serial searches against human, bacteria, fungi, protozoa and virus reference sequences, and then reads uniquely mapping to the host are removed. In the second step the taxon assignment of all reads uniquely mapping to the above life domains is carried out. A webservice/Galaxy implementation of SARMA is currently in progress, enabling the usage of several heterogeneous computing infrastructure thus remarkably optimizing the computational load and run time.
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