GSR: Simulator - nanosim
Attribute | Value |
---|---|
Title | nanosim |
Short Description | Nanopore sequence read simulator |
Long Description | NanoSim is a fast and scalable read simulator that captures the technology-specific features of ONT data, and allows for adjustments upon improvement of nanopore sequencing technology. |
Keywords | Nanopore |
Version | 3 |
Project Started | 2021 |
Last Release | 8 years, 8 months ago |
Homepage | https://github.com/bcgsc/NanoSim |
Citations | Yang C, Chu J, Warren RL, Birol I, NanoSim: nanopore sequence read simulator based on statistical characterization., Gigascience, April 1, 2017 [ Abstract, cited in PMC ] |
GSR Certification | ![]() ✔ Accessibility |
Last evaluated | Sept. 30, 2021 (1421 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 | Genotype or Sequencing Error, |
Simulation Method | Resample Existing Data, |
Input | |
Data Type | |
File format | |
Output | |
Data Type | |
Sequencing Reads | Nanopore, |
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 | Mac OS X, Linux and Unix, |
Language | Python, |
License | GNU Public License, |
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 nanosim.
2023
Mikalsen AJ, Zola J, Coriolis: enabling metagenomic classification on lightweight mobile devices., Bioinformatics, June 30, 2023 [Abstract]
Pardo-Palacios FJ, Wang D, Reese F, Diekhans M, Carbonell-Sala S, Williams B, Loveland JE, De María M, Adams MS, Balderrama-Gutierrez G, et al., Systematic assessment of long-read RNA-seq methods for transcript identification and quantification., bioRxiv, July 27, 2023 [Abstract]