GSR: Simulator - GARLIC

Basic Package Attributes
AttributeValue
Title GARLIC
Short Description Artificial DNA sequence generator
Long Description A common practice in computational genomic analysis is to use a set of 'background' sequences as negative controls for evaluating the false-positive rates of prediction tools, such as gene identification programs and algorithms for detection of cis-regulatory elements. Such 'background' sequences are generally taken from regions of the genome presumed to be intergenic, or generated synthetically by 'shuffling' real sequences. This last method can lead to underestimation of false-positive rates. We developed a new method for generating artificial sequences that are modeled after real intergenic sequences in terms of composition, complexity and interspersed repeat content. These artificial sequences can serve as an inexhaustible source of high-quality negative controls. We used artificial sequences to evaluate the false-positive rates of a set of programs for detecting interspersed repeats, ab initio prediction of coding genes, transcribed regions and non-coding genes. We found that RepeatMasker is more accurate than PClouds, Augustus has the lowest false-positive rate of the coding gene prediction programs tested, and Infernal has a low false-positive rate for non-coding gene detection. A web service, source code and the models for human and many other species are freely available at http://repeatmasker.org/garlic/.
Project Started 2011
Last Release 1 year, 9 months ago
Homepagehttps://github.com/caballero/Garlic
Citations Caballero J, Smit AF, Hood L, Glusman G, Realistic artificial DNA sequences as negative controls for computational genomics., Nucleic Acids Res, 07-01-2014 [ Abstract, cited in PMC ]
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Author verificationThe basic description provided was derived from a website or publications by the GSR team and has not yet been verified by the simulation author. To modify this entry or add more information, propose changes to this simulator.
Detailed Attributes
Attribute CategoryAttribute
Target
Type of Simulated DataHaploid DNA Sequence,
Variations
Simulation MethodOther,
Input
Data TypeReference genome,
File format
Output
Data TypeGenotype or Sequence,
Sequencing Reads
File FormatFasta or Fastq,
Sample Type
Phenotype
Trait Type
Determinants
Evolutionary Features
Demographic
Population Size Changes
Gene Flow
Spatiality
Life Cycle
Mating System
Fecundity
Natural Selection
Determinant
Models
Recombination
Mutation Models
Events Allowed
Other
InterfaceScript-based, Web-based,
Development
Tested PlatformsLinux and Unix,
LanguagePerl,
LicenseGNU Public License,
GSR Certification

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