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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, 3 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 (1059 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 |
|---|---|
| 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]