GSR: Simulator - SPsimSeq

Basic Package Attributes
AttributeValue
Title SPsimSeq
Short Description SPsimSeq simulates datasets from estimated marginal distributions with Gaussian-copulas.
Long Description SPsimSeq uses an exponential family for density estimation to construct distributions of gene expression levels from RNA sequencing data, thereby simulating a new dataset from marginal distributions with Gaussian-copulas in order to retain the dependence between genes. It also allows for the simulation of multiple groups and batches with any required sample size and library size.
Version v2.0.0
Project Started 2019
Last Release 5 years, 8 months ago
Homepagehttps://github.com/CenterForStatistics-UGent/SPsimSeq
Citations Assefa AT, Vandesompele J, Thas O, SPsimSeq: semi-parametric simulation of bulk and single-cell RNA-sequencing data., Bioinformatics, May 1, 2020 [ Abstract, cited in PMC ]
GSR CertificationGSR-certified

Accessibility
Documentation
Application
Support

Last evaluatedSept. 30, 2022 (932 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 DataRNA, Gene Expression, Single-Cell Sequencing, Bulk Sequencing,
Variations
Simulation Method
Input
Data Type
File format
Output
Data TypeGene Expression,
Sequencing Reads
File Format
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 Platforms
LanguageR,
LicenseBSD,
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 SPsimSeq.

2023

Crowell HL, Morillo Leonardo SX, Soneson C, Robinson MD, The shaky foundations of simulating single-cell RNA sequencing data., Genome Biol, March 29, 2023 [Abstract]

2020

Takele Assefa A, Vandesompele J, Thas O, On the utility of RNA sample pooling to optimize cost and statistical power in RNA sequencing experiments., BMC Genomics, April 19, 2020 [Abstract]


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