Package: MOSim 2.9.0

Sonia Tarazona

MOSim: Multi-Omics Simulation (MOSim)

MOSim package simulates multi-omic experiments that mimic regulatory mechanisms within the cell, allowing flexible experimental design including time course and multiple groups.

Authors:Carolina Monzó [aut], Carlos Martínez [aut], Sonia Tarazona [cre, aut]

MOSim_2.9.0.tar.gz
MOSim_2.9.0.zip(r-4.7)MOSim_2.9.0.zip(r-4.6)MOSim_2.9.0.zip(r-4.5)
MOSim_2.9.0.tgz(r-4.6-arm64)MOSim_2.9.0.tgz(r-4.6-x86_64)MOSim_2.9.0.tgz(r-4.5-x86_64)MOSim_2.9.0.tgz(r-4.5-arm64)
MOSim_2.9.0.tar.gz(r-4.7-arm64)MOSim_2.9.0.tar.gz(r-4.7-x86_64)MOSim_2.9.0.tar.gz(r-4.6-arm64)MOSim_2.9.0.tar.gz(r-4.6-x86_64)
MOSim_2.9.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
MOSim/json (API)
NEWS

# Install 'MOSim' in R:

install.packages('MOSim', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/conesalab/mosim/issues

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

associationList - Data to showcase scRNA and scATAC-seq association
sampleData - Default data
scatac - Data to test scMOSim
scrna - Data to test scMOSim
TF_human - Data to extract human TF

On BioConductor:MOSim-2.9.0(bioc 3.24)MOSim-2.8.0(bioc 3.23)

software timecourse experimentaldesign rnaseq cpp

6.76 score 12 stars 10 scripts 377 downloads 4 mentions 28 exports 186 dependencies

Last updated from:76f9819e90. Checks:1 ERROR, 10 WARNING, 2 OK. Indexed: yes.

Target	Result	Time
bioc-checks	ERROR	222
linux-devel-arm64	WARNING	734
linux-devel-x86_64	WARNING	752
source / vignettes	OK	605
linux-release-arm64	WARNING	736
linux-release-x86_64	WARNING	753
macos-release-arm64	WARNING	419
macos-oldrel-arm64	WARNING	411
macos-oldrel-x86_64	WARNING	1907
windows-devel	WARNING	987
windows-release	WARNING	1152
windows-oldrel	WARNING	947
wasm-release	OK	213

Exports:calculate_mean_per_list_df check_patterns discretize experimentalDesign make_association_dataframe make_cluster_patterns match_gene_regulator match_gene_regulator_cluster mosim omicData omicResults omicSettings omicSim plotProfile random_unif_interval sc_mosim sc_omicData sc_omicResults sc_omicSettings sc_param_estimation shuffle_group_matrix simulate_coexpression sparsim_create_simulation_parameter sparsim_estimate_intensity sparsim_estimate_library_size sparsim_estimate_parameter_from_data sparsim_estimate_variability sparsim_simulation

Dependencies:abind askpass assorthead base64enc beachmat BH Biobase BiocGenerics BiocNeighbors BiocParallel BiocSingular Biostrings bitops bluster bslib cachem caTools cli cluster codetools commonmark cowplot cpp11 crayon crosstalk curl data.table DelayedArray deldir digest dotCall64 dplyr dqrng edgeR evaluate farver fastDummies fastmap fastmatch fitdistrplus FNN fontawesome formatR fs futile.logger futile.options future future.apply generics GenomeInfoDb GenomicRanges ggplot2 ggrepel ggridges globals glue goftest gplots gridExtra gtable gtools here HiddenMarkov highr htmltools htmlwidgets httpuv httr ica igraph IRanges irlba isoband jquerylib jsonlite KernSmooth knitr labeling lambda.r later lattice lazyeval lifecycle limma listenv lmtest locfit magrittr MASS Matrix MatrixGenerics matrixStats memoise metapod mime miniUI nlme openssl otel parallelly patchwork pbapply pillar pkgconfig plotly plyr png polyclip progressr promises purrr R6 RANN rappdirs RColorBrewer Rcpp RcppAnnoy RcppArmadillo RcppEigen RcppHNSW RcppProgress RcppRoll RcppTOML reshape2 reticulate Rhtslib rlang rmarkdown ROCR rprojroot Rsamtools RSpectra rsvd Rtsne S4Arrays S4Vectors S7 sass ScaledMatrix scales scattermore scran sctransform scuttle Seqinfo Seurat SeuratObject shiny Signac SingleCellExperiment sitmo snow sourcetools sp spam SparseArray sparseMatrixStats spatstat.data spatstat.explore spatstat.geom spatstat.random spatstat.sparse spatstat.univar spatstat.utils statmod stringi stringr SummarizedExperiment survival sys tensor tibble tidyr tidyselect tinytex UCSC.utils utf8 uwot vctrs viridisLite withr xfun xtable XVector yaml zoo

Simulating bulk Multi-Omics Data with MOSim

Carolina Monzó, Carlos Martínez, Sonia Tarazona

Rendered fromMOSim.Rmdusingknitr::rmarkdownon May 29 2026.

Last update: 2025-03-27
Started: 2017-05-24

Simulating Single-Cell Multi-Omics Data with MOSim

Carolina Monzó, Ángeles Arzalluz-Luque, Sonia Tarazona

Rendered fromscMOSim.Rmdusingknitr::rmarkdownon May 29 2026.

Last update: 2025-04-02
Started: 2023-07-21

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Data to showcase scRNA and scATAC-seq association	associationList
calculate_mean_per_list_df	calculate_mean_per_list_df
check_patterns	check_patterns
Discretize ChIP-Seq counts to simulate a binary dataset	discretize
Retrieves the experimental design	experimentalDesign
Check if a variable is declared.	is.declared
make_association_dataframe	make_association_dataframe
make_cluster_patterns	make_cluster_patterns
match_gene_regulator	match_gene_regulator
match_gene_regulator_cluster	match_gene_regulator_cluster
mosim	mosim
Set customized data for an omic.	omicData
Retrieves the simulated data.	omicResults
Retrieves the settings used in a simulation	omicSettings
Set the simulation settings for an omic.	omicSim
Generate a plot of a feature's profile for one or two omics.	plotProfile
random_unif_interval Function to call the C code This function is a copy of the `random_unif_interval` function from the `SPARSim` package (v0.9.5), originally developed by Giacomo Baruzzo, Ilaria Patuzzi, Barbara Di Camillo (2020). The original package is licensed under the GPL-3 license.	random_unif_interval
Default data	sampleData
sc_mosim	sc_mosim
sc_omicData	sc_omicData
sc_omicResults	sc_omicResults
sc_omicSettings	sc_omicSettings
sc_param_estimation	sc_param_estimation
Data to test scMOSim	scatac
Data to test scMOSim	scrna
shuffle_group_matrix, Reorder cell type-specific expression matrix during co-expression simulation. Copied from ACORDE (https://github.com/ConesaLab/acorde) to facilitate stability and running within our scripts This function is a slightly modified copy of the `shuffle_group_matrix` function from the `Acorde` package (v1.0.0), originally developed by Arzalluz-Luque A, Salguero P, Tarazona S, Conesa A. (2022). acorde unravels functionally interpretable networks of isoform co-usage from single cell data. Nature communications 1828. DOI: 10.1038/s41467-022-29497-w. The original package is licensed under the GPL-3 license.	shuffle_group_matrix
simulate coexpression	simulate_coexpression
Simulate technical variability	simulate_hyper
Create SPARSim simulation parameter	sparsim_create_simulation_parameter
Estimate SPARSIm "intensity" parameter	sparsim_estimate_intensity
Estimate SPARSim "library size" parameter	sparsim_estimate_library_size
Estimate SPARSim simulation parameter from a given count table	sparsim_estimate_parameter_from_data
Estimate SPARSim "variability" parameter	sparsim_estimate_variability
Function to simulate a raw count table	sparsim_simulation
Data to extract human TF	TF_human