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Research article - Peer-reviewed, 2016

MetLab: An In Silico Experimental Design, Simulation and Analysis Tool for Viral Metagenomics Studies

Norling, Martin; Karlsson-Lindsjö, Oskar E.; Karlsson Lindsjö, Oskar; Gourlé, Hadrien; Bongcam-Rudloff, Erik; Hayer, Juliette

Abstract

Metagenomics, the sequence characterization of all genomes within a sample, is widely used as a virus discovery tool as well as a tool to study viral diversity of animals. Metagenomics can be considered to have three main steps; sample collection and preparation, sequencing and finally bioinformatics. Bioinformatic analysis of metagenomic datasets is in itself a complex process, involving few standardized methodologies, thereby hampering comparison of metagenomics studies between research groups. In this publication the new bioinformatics framework MetLab is presented, aimed at providing scientists with an integrated tool for experimental design and analysis of viral metagenomes. MetLab provides support in designing the metagenomics experiment by estimating the sequencing depth needed for the complete coverage of a species. This is achieved by applying a methodology to calculate the probability of coverage using an adaptation of Stevens' theorem. It also provides scientists with several pipelines aimed at simplifying the analysis of viral metagenomes, including; quality control, assembly and taxonomic binning. We also implement a tool for simulating metagenomics datasets from several sequencing platforms. The overall aim is to provide virologists with an easy to use tool for designing, simulating and analyzing viral metagenomes. The results presented here include a benchmark towards other existing software, with emphasis on detection of viruses as well as speed of applications. This is packaged, as comprehensive software, readily available for Linux and OSX users at https://github.com/norling/metlab.

Published in

PLoS ONE
2016, volume: 11, number: 8, article number: e0160334
Publisher: Public Library of Science

Authors' information

Norling, Martin
Uppsala University
Karlsson-Lindsjö, Oskar E. (Karlsson-Lindsjö, Oskar E.)
Swedish University of Agricultural Sciences, Department of Animal Breeding and Genetics
Karlsson Lindsjö, Oskar
Swedish University of Agricultural Sciences, Department of Biomedical Science and Veterinary Public Health
Gourlé, Hadrien
Swedish University of Agricultural Sciences, Department of Animal Breeding and Genetics
Bongcam-Rudloff, Erik (Bongcam Rudloff, Erik)
Swedish University of Agricultural Sciences, Department of Animal Breeding and Genetics
Swedish University of Agricultural Sciences, Department of Animal Breeding and Genetics

UKÄ Subject classification

Bioinformatics and Systems Biology
Genetics and Breeding
Bioinformatics (Computational Biology)

Publication Identifiers

DOI: https://doi.org/10.1371/journal.pone.0160334

URI (permanent link to this page)

https://res.slu.se/id/publ/77063