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MOSim

Bulk and single-cell Multi-Omics ground truth Simulator in R

https://github.com/conesalab/mosim

Science Score: 23.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ○
    codemeta.json file
  • ○
    .zenodo.json file
  • ✓
    DOI references
    Found 2 DOI reference(s) in README
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    2 of 8 committers (25.0%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (13.3%) to scientific vocabulary

Keywords from Contributors

bioconductor-package
Last synced: 10 months ago · JSON representation

Repository

Bulk and single-cell Multi-Omics ground truth Simulator in R

Basic Info
  • Host: GitHub
  • Owner: ConesaLab
  • Language: R
  • Default Branch: devel
  • Homepage:
  • Size: 53.2 MB
Statistics
  • Stars: 10
  • Watchers: 0
  • Forks: 1
  • Open Issues: 2
  • Releases: 1
Created over 3 years ago · Last pushed over 1 year ago
Metadata Files
Readme

README.md

MOSim

MOSim is an R package for the simulation of multi-omic bulk and single cell experiments that mimic regulatory mechanisms within the cell. Gene expression (RNA-seq count data) is the central data type simulated by MOSim, while the rest of available omic data types provide gene regulation information. For bulk simulation, regulators include ATAC-seq (DNase-seq), ChIP-seq, miRNA-seq and Methyl-seq. In addition to these omics, regulation by transcription factors (TFs) can also be modeled. While for single-cell simulation, the regulators included are scATAC-seq and TFs.
MOSim has great flexibility in defining experimental designs, DEGs, and active regulators making it a versatile tool for a variety of different applications: i) validating methods aimed at modelling complex, multi-layered regulatory networks, ii) benchmarking multi-omics data integration pipelines, iii) benchmarking GRN inference tools, iv) evaluating differential expression and accessibility analysis tools, v) testing single-cell data clustering methods, vi) evaluating multi-omics visualization tools etc.

Installation

MOSim is a Bioconductor R package, and we strongly recommend that it is installed from the Bioconductor repository. To install MOSim, open the R console and run:

``` if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager")

BiocManager::install("MOSim") ```

The developer version (which now includes the sc_mosim functionalities) can be installed from GitHub using the devtools R package:

install.packages("devtools") devtools::install_github("ConesaLab/MOSim")

Documentation

Vignettes and documentation can be accessed from MOSim's Bioconductor site, or by running the following line in the R console:

browseVignettes("MOSim")

Citation

If you used MOSim for your research, please cite:

  • Monzó C, Aguerralde-Martin M, Martínez-Mira C, Arzalluz-Luque A, Conesa A, Tarazona S (2025). MOSim: bulk and single-cell multi-layer regulatory network simulator. Briefings in Bioinformatics, Volume 26, Issue 5. DOI: 10.1093/bib/bbaf110

scmosim strongly relies on functionality from SPARSim. If you use the scmosim module to simulate multi-omics single cell data, please also cite:
- Baruzzo G, Patuzzi I, Di Camillo B (2020). SPARSim single cell: a count data simulator for scRNA-seq data. Bioinformatics, Volume 36, Issue 5, Pages 1468-1475. DOI: 10.1093/bioinformatics/btz752

Owner

  • Name: ConesaLab - Genomics of gene expression
  • Login: ConesaLab
  • Kind: organization

GitHub Events

Total
  • Issues event: 3
  • Watch event: 2
  • Issue comment event: 4
  • Push event: 4
Last Year
  • Issues event: 3
  • Watch event: 2
  • Issue comment event: 4
  • Push event: 4

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 142
  • Total Committers: 8
  • Avg Commits per committer: 17.75
  • Development Distribution Score (DDS): 0.415
Past Year
  • Commits: 101
  • Committers: 5
  • Avg Commits per committer: 20.2
  • Development Distribution Score (DDS): 0.178
Top Committers
Name Email Commits
Carolina Monzó c****c@g****m 83
Carlos Martínez c****z@c****s 24
ariannafebbo a****o@y****t 14
Nitesh Turaga n****a@g****m 12
Carlos M.M c****r@g****m 5
J Wokaty j****y@s****u 2
Sonia Tarazona Campos s****m@u****s 1
Ángeles Arzalluz-Luque a****z@g****m 1
Committer Domains (Top 20 + Academic)
upv.edu.es: 1 sph.cuny.edu: 1 yahoo.it: 1 cipf.es: 1

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 6
  • Total pull requests: 2
  • Average time to close issues: 5 days
  • Average time to close pull requests: 1 minute
  • Total issue authors: 5
  • Total pull request authors: 1
  • Average comments per issue: 1.67
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 4
  • Pull requests: 0
  • Average time to close issues: about 5 hours
  • Average time to close pull requests: N/A
  • Issue authors: 4
  • Pull request authors: 0
  • Average comments per issue: 1.75
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • fanyue322 (2)
  • luyiyun (1)
  • HenrikBengtsson (1)
  • olshena (1)
  • anu-bioinfo (1)
Pull Request Authors
  • carolinamonzo (2)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • bioconductor 9,566 total
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 5
  • Total maintainers: 1
bioconductor.org: MOSim

Multi-Omics Simulation (MOSim)

  • Versions: 5
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 9,566 Total
Rankings
Dependent repos count: 0.0%
Dependent packages count: 0.0%
Stargazers count: 19.5%
Forks count: 19.8%
Average: 23.2%
Downloads: 76.9%
Maintainers (1)
sotacam@gmail.com
Last synced: 11 months ago