GSR: Simulator - ESCO
Attribute | Value |
---|---|
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 |
Homepage | https://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 Certification | ![]() ✔ Accessibility |
Last evaluated | Sept. 28, 2022 (934 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 |
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Target | |
Type of Simulated Data | RNA, 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 | |
Interface | Script-based, |
Development | |
Tested Platforms | |
Language | R, |
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 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]