GSR: Simulator - scDesign

Basic Package Attributes
AttributeValue
Title scDesign
Short Description scDesign assess scRNA-seq experimental design in the context of differential gene expression analysis.
Long Description scDesign quantitatively assesses scRNA-seq experimental design. The software also assists in computational method development by generating high-quality synthetic scRNA-seq datasets under customized experimental settings. scDesign is reproducible across biological replicates and independent studies.
Version 1.0.0
Project Started 2018
Last Release 4 years, 8 months ago
Homepagehttps://github.com/Vivianstats/scDesign
Citations Li WV, Li JJ, A statistical simulator scDesign for rational scRNA-seq experimental design., Bioinformatics, July 15, 2019 [ Abstract, cited in PMC ]
GSR CertificationGSR-certified

Accessibility
Documentation
Application
Support

Last evaluatedJune 23, 2022 (1155 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 Method
Input
Data Type
File format
Output
Data Type
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
LanguageOther,
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 scDesign.

2023

Fan S, Dang D, Ye Y, Zhang SW, Gao L, Zhang S, scHi-CSim: a flexible simulator that generates high-fidelity single-cell Hi-C data for benchmarking., J Mol Cell Biol, June 1, 2023 [Abstract]

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]


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