GSR: Simulator - ESCO

Basic Package Attributes
AttributeValue
Title ESCO
Short Description ESCO: single cell expression simulation incorporating gene co-expression
Long Description Ensemble Single-cell expression simulator incorporating gene CO-expression, ESCO, is constructed as an ensemble of the best features among current simulators to preserve the marginal performance, while allowing easily incorporating co-expression structure among genes using a copula. Particularly, ESCO allows realistic simulation of a homogeneous cell group, heterogeneous cell groups, as well as complex cell group relationships such as tree and trajectory structure, together with a flexible input of co-expression. As for technical noise, ESCO integrates the parametric and non-parametric approaches in current literature and gives the user flexibility to choose. In order to mimic a specific real dataset, ESCO can estimate all the hyperparameters in a feasible way for both a homogeneous cell group or heterogeneous cell groups. ESCO is implemented in the R package ESCO, which is built upon the R package Splatter (Zappia et al., 2017), in order to provide a unified software framework.
Keywords single-cell RNA sequencing, gene co-expression, splatter, GCN recovery
Version 0.99.12
Project Started 2020
Last Release 4 years, 2 months ago
Homepagehttps://github.com/JINJINT/ESCO
Citations Tian J, Wang J, Roeder K, ESCO: single cell expression simulation incorporating gene co-expression., Bioinformatics, Feb. 24, 2021 [ Abstract, cited in PMC ]
GSR CertificationGSR-certified

Accessibility
Documentation
Application
Support

Last evaluatedSept. 28, 2022 (934 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,
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
InterfaceScript-based,
Development
Tested Platforms
LanguageR,
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 ESCO.

2021

Fujii T, Maehara K, Fujita M, Ohkawa Y, Discriminative feature of cells characterizes cell populations of interest by a small subset of genes., PLoS Comput Biol, Nov. 19, 2021 [Abstract]

Wang X, Choi D, Roeder K, Constructing local cell-specific networks from single-cell data., Proc Natl Acad Sci U S A, Dec. 21, 2021 [Abstract]


Propose changes to this simulator