Package: scMultiSim 1.3.0

Hechen Li

scMultiSim: Simulation of Multi-Modality Single Cell Data Guided By Gene Regulatory Networks and Cell-Cell Interactions

scMultiSim simulates paired single cell RNA-seq, single cell ATAC-seq and RNA velocity data, while incorporating mechanisms of gene regulatory networks, chromatin accessibility and cell-cell interactions. It allows users to tune various parameters controlling the amount of each biological factor, variation of gene-expression levels, the influence of chromatin accessibility on RNA sequence data, and so on. It can be used to benchmark various computational methods for single cell multi-omics data, and to assist in experimental design of wet-lab experiments.

Authors:Hechen Li [aut, cre], Xiuwei Zhang [aut], Ziqi Zhang [aut], Michael Squires [aut]

scMultiSim_1.3.0.tar.gz
scMultiSim_1.3.0.zip(r-4.5)scMultiSim_1.3.0.zip(r-4.4)scMultiSim_1.1.10.zip(r-4.3)
scMultiSim_1.3.0.tgz(r-4.4-any)scMultiSim_1.1.10.tgz(r-4.3-any)
scMultiSim_1.3.0.tar.gz(r-4.5-noble)scMultiSim_1.3.0.tar.gz(r-4.4-noble)
scMultiSim_1.3.0.tgz(r-4.4-emscripten)scMultiSim_1.1.10.tgz(r-4.3-emscripten)
scMultiSim.pdf |scMultiSim.html✨
scMultiSim/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/zhanglabgt/scmultisim/issues

Datasets:
  • GRN_params_100 - 100_gene_GRN is a matrix of GRN params consisting of 100 genes where: # - column 1 is the target gene ID, # - column 2 is the gene ID which acts as a transcription factor for the target (regulated) gene # - column 3 is the effect of the column 2 gene ID on the column 1 gene ID
  • GRN_params_1139 - GRN_params_1139 is a matrix of GRN params consisting of 1139 genes where: # - column 1 is the target gene ID, # - column 2 is the gene ID which acts as a transcription factor for the target (regulated) gene # - column 3 is the effect of the column 2 gene ID on the column 1 gene ID
  • dens_nonzero - This is the density function of log(x+1), where x is the non-zero values for ATAC-SEQ data

On BioConductor:scMultiSim-1.3.0(bioc 3.21)scMultiSim-1.2.0(bioc 3.20)

singlecelltranscriptomicsgeneexpressionsequencingexperimentaldesign

7.40 score 22 stars 13 scripts 142 downloads 26 exports 99 dependencies

Last updated 23 days agofrom:2e6a4fcebc. Checks:OK: 1 WARNING: 4 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 18 2024
R-4.5-winWARNINGNov 18 2024
R-4.5-linuxWARNINGNov 18 2024
R-4.4-winWARNINGNov 18 2024
R-4.4-macWARNINGNov 18 2024
R-4.3-winNOTESep 27 2024
R-4.3-macNOTESep 27 2024

Exports:add_expr_noiseadd_outlierscci_cell_type_paramsdivide_batchesgen_cluttergene_corr_ccigene_corr_regulatorGet_1region_ATAC_correlationGet_ATAC_correlationPhyla1Phyla3Phyla5plot_cell_locplot_gene_module_cor_heatmapplot_gridplot_grnplot_phylaplot_rna_velocityplot_tsnerun_shinyscmultisim_helpsim_examplesim_example_spatialsim_true_countsTrue2ObservedATACTrue2ObservedCounts

Dependencies:abindapeaskpassassertthatBHBiobaseBiocGenericsBiocParallelbitopscaToolscliclusterGenerationcodacodetoolscolorspacecombinatcommonmarkcpp11crayoncurlDelayedArrayDEoptimdigestdoParalleldplyrexpmfansifarverfastmatchforeachformatRfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2gluegplotsgtablegtoolshttrigraphIRangesisobanditeratorsjsonliteKernelKnnKernSmoothlabelinglambda.rlatticelifecyclemagrittrmapsmarkdownMASSMatrixMatrixGenericsmatrixStatsmgcvmimemnormtmunsellnlmenumDerivopenssloptimParallelphangornphytoolspillarpkgconfigquadprogR6RColorBrewerRcppRcppArmadillorlangRtsneS4ArraysS4Vectorsscalesscatterplot3dsnowSparseArraySummarizedExperimentsystibbletidyselectUCSC.utilsutf8vctrsviridisLitewithrxfunXVectorzeallotzlibbioc

Getting Started

Rendered fromworkflow.Rmdusingknitr::knitron Nov 18 2024.

Last update: 2024-09-02
Started: 2024-08-29

Simulating Multimodal Single-cell Datasets

Rendered frombasics.Rmdusingknitr::knitron Nov 18 2024.

Last update: 2024-09-02
Started: 2023-05-18

Simulating Spatial Cell-Cell Interactions

Rendered fromspatialCCI.Rmdusingknitr::knitron Nov 18 2024.

Last update: 2024-09-26
Started: 2024-09-26

Parameter Guide

Rendered fromoptions.Rmdusingknitr::knitron Nov 18 2024.

Last update: 2024-09-02
Started: 2024-08-29

Readme and manuals

Help Manual

Help pageTopics
Add experimental noise to true countsadd_expr_noise
Add outliers to the observed countsadd_outliers
Generate cell-type level CCI parameterscci_cell_type_params
this is the density function of log(x+1), where x is the non-zero values for ATAC-SEQ datadens_nonzero
Divide batches for observed countsdivide_batches
generate a clutter of cells by growing from the centergen_clutter
Plot the ligand-receptor correlation summarygene_corr_cci
Print the correlations between targets of each regulatorgene_corr_regulator
This function gets the average correlation rna seq counts and region effect on genes for genes which are only associated with 1 chromatin regionGet_1region_ATAC_correlation
This function gets the average correlation rna seq counts and chromatin region effect on genesGet_ATAC_correlation
100_gene_GRN is a matrix of GRN params consisting of 100 genes where: # - column 1 is the target gene ID, # - column 2 is the gene ID which acts as a transcription factor for the target (regulated) gene # - column 3 is the effect of the column 2 gene ID on the column 1 gene IDGRN_params_100
GRN_params_1139 is a matrix of GRN params consisting of 1139 genes where: # - column 1 is the target gene ID, # - column 2 is the gene ID which acts as a transcription factor for the target (regulated) gene # - column 3 is the effect of the column 2 gene ID on the column 1 gene IDGRN_params_1139
Creating a linear example treePhyla1
Creating an example tree with 3 tipsPhyla3
Creating an example tree with 5 tipsPhyla5
Plot cell locationsplot_cell_loc
Plot the gene module correlation heatmapplot_gene_module_cor_heatmap
Plot the CCI gridplot_grid
Plot the GRN networkplot_grn
Plot a R phylogenic treeplot_phyla
Plot RNA velocity as arrows on tSNE plotplot_rna_velocity
Plot t-SNE visualization of a data matrixplot_tsne
Launch the Shiny App to configure the simulationrun_shiny
Show detailed documentations of scMultiSim's parametersscmultisim_help
Simulate a small example dataset with 200 cells and the 100-gene GRNsim_example
Simulate a small example dataset with 200 cells and the 100-gene GRN, with CCI enabledsim_example_spatial
Simulate true scRNA and scATAC counts from the parameterssim_true_counts
The class for spatial grids.SpatialGrid spatialGrid-class
Simulate observed ATAC-seq matrix given technical noise and the true countsTrue2ObservedATAC
Simulate observed count matrix given technical biases and the true countsTrue2ObservedCounts