Package: MOSim 2.1.0

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_2.1.0.tar.gz
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MOSim.pdf |MOSim.html✨
MOSim/json (API)
NEWS

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

Peer review:

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

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On BioConductor:MOSim-2.1.0(bioc 3.20)MOSim-2.0.0(bioc 3.19)

bioconductor-package

28 exports 2.50 score 189 dependencies 4 mentions

Last updated 6 days agofrom:66e0f58a6a

Exports:calculate_mean_per_list_dfcheck_patternsdiscretizeexperimentalDesignmake_association_dataframemake_cluster_patternsmatch_gene_regulatormatch_gene_regulator_clustermosimomicDataomicResultsomicSettingsomicSimplotProfilerandom_unif_intervalsc_omicDatasc_param_estimationscMOSimscOmicResultsscOmicSettingsshuffle_group_matrixsimulate_coexpressionsparsim_create_simulation_parametersparsim_estimate_intensitysparsim_estimate_library_sizesparsim_estimate_parameter_from_datasparsim_estimate_variabilitysparsim_simulation

Dependencies:abindaskpassbase64encbeachmatBHBiobaseBiocGenericsBiocNeighborsBiocParallelBiocSingularBiostringsbitopsblusterbslibcachemcaToolscliclustercodetoolscolorspacecommonmarkcowplotcpp11crayoncrosstalkcurldata.tableDelayedArrayDelayedMatrixStatsdeldirdigestdotCall64dplyrdqrngedgeRevaluatefansifarverfastDummiesfastmapfastmatchfitdistrplusFNNfontawesomeformatRfsfutile.loggerfutile.optionsfuturefuture.applygenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2ggrepelggridgesglobalsgluegoftestgplotsgridExtragtablegtoolshereHiddenMarkovhighrhtmltoolshtmlwidgetshttpuvhttricaigraphIRangesirlbaisobandjquerylibjsonliteKernSmoothknitrlabelinglambda.rlaterlatticelazyevalleidenlifecyclelimmalistenvlmtestlocfitmagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemetapodmgcvmimeminiUImunsellnlmeopensslparallellypatchworkpbapplypillarpkgconfigplotlyplyrpngpolyclipprogressrpromisespurrrR6RANNrappdirsRColorBrewerRcppRcppAnnoyRcppArmadilloRcppEigenRcppHNSWRcppProgressRcppRollRcppTOMLreshape2reticulateRhtslibrlangrmarkdownROCRrprojrootRsamtoolsRSpectrarsvdRtsneS4ArraysS4VectorssassScaledMatrixscalesscattermorescransctransformscuttleSeuratSeuratObjectshinySignacSingleCellExperimentsitmosnowsourcetoolsspspamSparseArraysparseMatrixStatsspatstat.dataspatstat.explorespatstat.geomspatstat.randomspatstat.sparsespatstat.utilsstatmodstringistringrSummarizedExperimentsurvivalsystensortibbletidyrtidyselecttinytexUCSC.utilsutf8uwotvctrsviridisLitewithrxfunxtableXVectoryamlzlibbioczoo

MOSim

Rendered fromMOSim.Rnwusingknitr::knitron Jul 05 2024.

Last update: 2024-06-13
Started: 2017-05-24

Simulating Single-Cell Multi-Omics Data with MOSim

Carolina Monzó, Ángeles Arzalluz-Luque, Arianna Febbo, Sonia Tarazona

Rendered fromscMOSim.Rmdusingknitr::knitron Jul 05 2024.

Last update: 2024-04-15
Started: 2023-07-21

Readme and manuals

Help Manual

Help pageTopics
Data to showcase scRNA and scATAC-seq associationassociationList
calculate_mean_per_list_dfcalculate_mean_per_list_df
check_patternscheck_patterns
Discretize ChIP-Seq counts to simulate a binary datasetdiscretize
Retrieves the experimental designexperimentalDesign
Check if a variable is declared.is.declared
make_association_dataframemake_association_dataframe
make_cluster_patternsmake_cluster_patterns
match_gene_regulatormatch_gene_regulator
match_gene_regulator_clustermatch_gene_regulator_cluster
mosimmosim
Set customized data for an omic.omicData
Retrieves the simulated data.omicResults
Retrieves the settings used in a simulationomicSettings
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 datasampleData
sc_omicDatasc_omicData
sc_param_estimationsc_param_estimation
Data to test scMOSimscatac
scMOSimscMOSim
scOmicResultsscOmicResults
scOmicSettingsscOmicSettings
Data to test scMOSimscrna
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 coexpressionsimulate_coexpression
Simulate technical variabilitysimulate_hyper
Create SPARSim simulation parametersparsim_create_simulation_parameter
Estimate SPARSIm "intensity" parametersparsim_estimate_intensity
Estimate SPARSim "library size" parametersparsim_estimate_library_size
Estimate SPARSim simulation parameter from a given count tablesparsim_estimate_parameter_from_data
Estimate SPARSim "variability" parametersparsim_estimate_variability
Function to simulate a raw count tablesparsim_simulation
Data to extract human TFTF_human