GSR: Simulator - phastSim

Basic Package Attributes
AttributeValue
Title phastSim
Short Description phastSim: Efficient simulation of sequence evolution for pandemic-scale datasets
Long Description We present phastSim, a new algorithm and software for efficiently simulating sequence evolution along extremely large trees (e.g. > 100, 000 tips) when the branches of the tree are short, as is typical in genomic epidemiology. Our algorithm is based on the Gillespie approach, and it implements an efficient multi-layered search tree structure that provides high computational efficiency by taking advantage of the fact that only a small proportion of the genome is likely to mutate at each branch of the considered phylogeny. Our open source software allows easy integration with other Python packages as well as a variety of evolutionary models, including indel models and new hypermutability models that we developed to more realistically represent SARS-CoV-2 genome evolution.
Keywords large datasets, sequence evolution, genomic epidemiology, Gillespie algorithm,
Version 0.0.4
Project Started 2020
Last Release 3 years, 4 months ago
Homepagehttps://github.com/NicolaDM/phastSim
Citations De Maio N, Boulton W, Weilguny L, Walker CR, Turakhia Y, Corbett-Detig R, Goldman N, phastSim: Efficient simulation of sequence evolution for pandemic-scale datasets., PLoS Comput Biol, April 29, 2022 [ Abstract, cited in PMC ]
GSR CertificationGSR-certified

Accessibility
Documentation
Application
Support

Last evaluatedAug. 5, 2022 (988 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 Data
Variations
Simulation MethodOther,
Input
Data Type
File formatOther,
Output
Data TypeGenotype or Sequence,
Sequencing Reads
File FormatFasta or Fastq, Phylip,
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 ModelsCodon and Amino Acid Models,
Events Allowed
Other
Interface
Development
Tested Platforms
LanguagePython,
LicenseGNU Public License,
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 phastSim.

2022

Thornlow B, Kramer A, Ye C, De Maio N, McBroome J, Hinrichs AS, Lanfear R, Turakhia Y, Corbett-Detig R, Online Phylogenetics using Parsimony Produces Slightly Better Trees and is Dramatically More Efficient for Large SARS-CoV-2 Phylogenies than <i>de novo</i> and Maximum-Likelihood Approaches., bioRxiv, May 18, 2022 [Abstract]

McBroome J, Martin J, de Bernardi Schneider A, Turakhia Y, Corbett-Detig R, Identifying SARS-CoV-2 regional introductions and transmission clusters in real time., Virus Evol, June 16, 2022 [Abstract]


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