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GSR: Simulator - NEAT
| Attribute | Value |
|---|---|
| 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 | 8 years, 11 months ago |
| Homepage | https://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, Jan. 1, 2016 [ Abstract, cited in PMC ] |
| GSR Certification |  ✔ Accessibility |
| Last evaluated | May 30, 2018 (2663 days ago) |
| Author verification | The 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. |
| Attribute Category | Attribute |
|---|---|
| Target | |
| Type of Simulated Data | Sequencing Reads, |
| Variations | Biallelic Marker, Multiallelic Marker, Single Nucleotide Variation, Insertion and Deletion, |
| Simulation Method | Resample Existing Data, Other, |
| Input | |
| Data Type | Reference genome, |
| File format | Other, |
| Output | |
| Data Type | |
| Sequencing Reads | Illumina, |
| File Format | Fasta 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 | |
| Interface | Command-line, |
| Development | |
| Tested Platforms | Windows, Mac OS X, Linux and Unix, |
| Language | Python, |
| License | Other, |
| GSR Certification | Accessibility, 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), Feb. 1, 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, Aug. 31, 2023 [Abstract]