Dataset Information

OMSim: a simulator for optical map data.

ABSTRACT: The Bionano Genomics platform allows for the optical detection of short sequence patterns in very long DNA molecules (up to 2.5?Mbp). Molecules with overlapping patterns can be assembled to generate a consensus optical map of the entire genome. In turn, these optical maps can be used to validate or improve de novo genome assembly projects or to detect large-scale structural variation in genomes. Simulated optical map data can assist in the development and benchmarking of tools that operate on those data, such as alignment and assembly software. Additionally, it can help to optimize the experimental setup for a genome of interest. Such a simulator is currently not available.We have developed a simulator, OMSim, that produces synthetic optical map data that mimics real Bionano Genomics data. These simulated data have been tested for compatibility with the Bionano Genomics Irys software system and the Irys-scaffolding scripts. OMSim is capable of handling very large genomes (over 30 Gbp) with high throughput and low memory requirements.The Python simulation tool and a cross-platform graphical user interface are available as open source software under the GNU GPL v2 license ( http://www.bioinformatics.intec.ugent.be/omsim ).jan.fostier@ugent.be.Supplementary data are available at Bioinformatics online.

SUBMITTER: Miclotte G

PROVIDER: S-EPMC5860066 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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OMSim: a simulator for optical map data.

Miclotte Giles G Plaisance Stéphane S Rombauts Stephane S Van de Peer Yves Y Audenaert Pieter P Fostier Jan J

Bioinformatics (Oxford, England) 20170901 17

<h4>Motivation</h4>The Bionano Genomics platform allows for the optical detection of short sequence patterns in very long DNA molecules (up to 2.5 Mbp). Molecules with overlapping patterns can be assembled to generate a consensus optical map of the entire genome. In turn, these optical maps can be used to validate or improve de novo genome assembly projects or to detect large-scale structural variation in genomes. Simulated optical map data can assist in the development and benchmarking of tools ...[more]

PMID: 28472230

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Project description:BackgroundIn the last few years, 16S rRNA gene sequencing (16S rDNA-seq) has seen a surprisingly rapid increase in election rate as a methodology to perform microbial community studies. Despite the considerable popularity of this technique, an exiguous number of specific tools are currently available for proper 16S rDNA-seq count data preprocessing and simulation. Indeed, the great majority of tools have been developed adapting methodologies previously used for bulk RNA-seq data, with poor assessment of their applicability in the metagenomics field. For such tools and the few ones specifically developed for 16S rDNA-seq data, performance assessment is challenging, mainly due to the complex nature of the data and the lack of realistic simulation models. In fact, to the best of our knowledge, no software thought for data simulation are available to directly obtain synthetic 16S rDNA-seq count tables that properly model heavy sparsity and compositionality typical of these data.ResultsIn this paper we present metaSPARSim, a sparse count matrix simulator intended for usage in development of 16S rDNA-seq metagenomic data processing pipelines. metaSPARSim implements a new generative process that models the sequencing process with a Multivariate Hypergeometric distribution in order to realistically simulate 16S rDNA-seq count table, resembling real experimental data compositionality and sparsity. It provides ready-to-use count matrices and comes with the possibility to reproduce different pre-coded scenarios and to estimate simulation parameters from real experimental data. The tool is made available at http://sysbiobig.dei.unipd.it/?q=Software#metaSPARSimand https://gitlab.com/sysbiobig/metasparsim.ConclusionmetaSPARSim is able to generate count matrices resembling real 16S rDNA-seq data. The availability of count data simulators is extremely valuable both for methods developers, for which a ground truth for tools validation is needed, and for users who want to assess state of the art analysis tools for choosing the most accurate one. Thus, we believe that metaSPARSim is a valuable tool for researchers involved in developing, testing and using robust and reliable data analysis methods in the context of 16S rRNA gene sequencing.

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OMSim: a simulator for optical map data.

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OMSim: a simulator for optical map data.

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