Please use this identifier to cite or link to this item: https://doi.org/10.1371/journal.pone.0003373
Title: MetaSim - A sequencing simulator for genomics and metagenomics
Authors: Richter D.C.
Ott F.
Auch A.F.
Schmid R.
Huson D.H. 
Keywords: article
computer interface
computer program
computer simulation
gene sequence
genetic database
genome analysis
genomics
molecular evolution
program development
sequence analysis
simulator
standardization
taxonomy
theoretical model
Databases, Genetic
Genomics
Models, Theoretical
User-Computer Interface
Issue Date: 2008
Citation: Richter D.C., Ott F., Auch A.F., Schmid R., Huson D.H. (2008). MetaSim - A sequencing simulator for genomics and metagenomics. PLoS ONE 3 (10) : e3373. ScholarBank@NUS Repository. https://doi.org/10.1371/journal.pone.0003373
Rights: Attribution 4.0 International
Abstract: Background: The new research field of metagenomics is providing exciting insights into various, previously unclassified ecological systems. Next-generation sequencing technologies are producing a rapid increase of environmental data in public databases. There is great need for specialized software solutions and statistical methods for dealing with complex metagenome data sets. Methodology/Principal Findings: To facilitate the development and improvement of metagenomic tools and the planning of metagenomic projects, we introduce a sequencing simulator called MetaSim. Our software can be used to generate collections of synthetic reads that reflect the diverse taxonomical composition of typical metagenome data sets. Based on a database of given genomes, the program allows the user to design a metagenome by specifying the number of genomes present at different levels of the NCBI taxonomy, and then to collect reads from the metagenome using a simulation of a number of different sequencing technologies. A population sampler optionally produces evolved sequences based on source genomes and a given evolutionary tree. Conclusions/Significance: MetaSim allows the user to simulate individual read datasets that can be used as standardized test scenarios for planning sequencing projects or for benchmarking metagenomic software. � 2008 Richter et al.
Source Title: PLoS ONE
URI: https://scholarbank.nus.edu.sg/handle/10635/161847
ISSN: 19326203
DOI: 10.1371/journal.pone.0003373
Rights: Attribution 4.0 International
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