GSR: Simulator - NEAT

Basic Package Attributes
AttributeValue
Title NEAT
Short Description NEAT read simulation tools
Long Description NEAT-genReads is a fine-grained read simulator. GenReads simulates real-looking data using models learned from specific datasets. There are several supporting utilities for generating models used for simulation.
Version 2.0
Project Started 2016
Last Release 7 years, 5 months ago
Homepagehttps://github.com/zstephens/neat-genreads
Citations Stephens ZD, Hudson ME, Mainzer LS, Taschuk M, Weber MR, Iyer RK, Simulating Next-Generation Sequencing Datasets from Empirical Mutation and Sequencing Models., PLoS One, 01-01-2016 [ Abstract, cited in PMC ]
GSR CertificationGSR-certified

Accessibility
Documentation
Application
Support

Last evaluated05-30-2018 (2145 days ago)
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 DataSequencing Reads,
VariationsBiallelic Marker, Multiallelic Marker, Single Nucleotide Variation, Insertion and Deletion,
Simulation MethodResample Existing Data, Other,
Input
Data TypeReference genome,
File formatOther,
Output
Data Type
Sequencing ReadsIllumina,
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
InterfaceCommand-line,
Development
Tested PlatformsWindows, Mac OS X, Linux and Unix,
LanguagePython,
LicenseOther,
GSR CertificationAccessibility, Documentation, Application, Support,

Number of Primary Citations: 1

Number of Non-Primary Citations: 2

The following 2 publications are selected examples of applications that used NEAT.

2023

Milhaven M, Pfeifer SP, Performance evaluation of six popular short-read simulators., Heredity (Edinb), 02-01-2023 [Abstract]

Roder AE, Johnson KEE, Knoll M, Khalfan M, Wang B, Schultz-Cherry S, Banakis S, Kreitman A, Mederos C, Youn JH, et al., Optimized quantification of intra-host viral diversity in SARS-CoV-2 and influenza virus sequence data., mBio, 08-31-2023 [Abstract]


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