18841204

From SEQwiki
Jump to: navigation, search

This reference describes MetaSim.

PMID PMID 18841204
Title MetaSim: a sequencing simulator for genomics and metagenomics.
Year 2008
Journal PLoS One
Author Richter DC, Ott F, Auch AF, Schmid R, Huson DH.
Volume 3
Start page


Error: No contents found at URL http://www.ebi.ac.uk/europepmc/webservices/rest/MED/18841204/citations/4000.

According to Europe PubMed Central, this reference has Error: no local variable "citations" was set. " Error: no local variable "citations" was set. " is not a number. citations.

For reference, you can check Google Scholar, which lacks an API because Google ...


Error: Invalid JSON. According to Almetric, this reference has an Altmetric score of Error: no local variable "altscore" was set. " Error: no local variable "altscore" was set. " is not a number..

Full text description

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.