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GSR: Simulator - OmicsSIMLA
| Attribute | Value |
|---|---|
| Title | OmicsSIMLA |
| Short Description | A simulation tool for generating multi-omics data with disease status |
| Long Description | OmicsSIMLA is a simulation tool for generating multi-omics data with disease status. Currently, OmicsSIMLA has four main modules: SeqSIMLA, pWGBSSimla, RNA-Seq, and RPPA. SeqSIMLA can simulate sequence data in families with multiple affected and unaffected siblings or unrelated case-control samples under different disease models. pWGBSSimla is a profile-based whole-genome bisulphite sequencing data simulator, which can simulate whole-genome DNA methylation (WGBS), reduced representation bisulfite sequencing (RRBS), and oxidative bisulfite sequencing (oxBS-seq) data while modeling methylation quantitative trait loci, allele-specific methylations, and differentially methylated regions. RNA-Seq uses a negative binomial distribution to simulate NGS read counts for gene expression. Finally, RPPA uses a mass-action kinetic action model to simulate protein expression data. |
| Version | 0.6 |
| Project Started | 2019 |
| Homepage | |
| Citations | Chung RH, Kang CY, A multi-omics data simulator for complex disease studies and its application to evaluate multi-omics data analysis methods for disease classification., Gigascience, May 1, 2019 [ Abstract, cited in PMC ] |
| GSR Certification | Accessibility |
| Last evaluated | Sept. 30, 2021 (1445 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 | Haploid DNA Sequence, Protein Sequence, |
| Variations | Biallelic Marker, Other, |
| Simulation Method | |
| Input | |
| Data Type | Reference genome, |
| 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 | |
| Development | |
| Tested Platforms | |
| Language | C or C++, R, |
| License | |
| GSR Certification | Documentation, Application, |
Number of Primary Citations: 1
Number of Non-Primary Citations: 2
The following 2 publications are selected examples of applications that used OmicsSIMLA.
2023
Snajder R, Leger A, Stegle O, Bonder MJ, pycoMeth: a toolbox for differential methylation testing from Nanopore methylation calls., Genome Biol, April 20, 2023 [Abstract]
2022
Pierre-Jean M, Mauger F, Deleuze JF, Le Floch E, PIntMF: Penalized Integrative Matrix Factorization method for multi-omics data., Bioinformatics, Jan. 27, 2022 [Abstract]