Package: scMultiSim 1.1.0

Hechen i

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 i [aut, cre], Xiuwei Zhang [aut], Michael Squires [aut]

scMultiSim_1.1.0.tar.gz
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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
  • gene_len_pool - A pool of gene lengths to sample from
  • len2nfrag - From transcript length to number of fragments
  • match_params - Distribution of kinetic parameters learned from the Zeisel UMI cortex datasets

On BioConductor:scMultiSim-1.1.0(bioc 3.20)scMultiSim-1.0.0(bioc 3.19)

bioconductor-package

23 exports 1.69 score 92 dependencies

Last updated 2 months agofrom:18614db9c4

Exports:add_expr_noisecci_cell_type_paramsdivide_batchesgene_corr_ccigene_corr_regulatorGet_1region_ATAC_correlationGet_ATAC_correlationPhyla1Phyla3Phyla5plot_cell_locplot_gene_module_cor_heatmapplot_gridplot_grnplot_phylaplot_rna_velocityplot_tsnescmultisim_helpsim_examplesim_example_spatialsim_true_countsTrue2ObservedATACTrue2ObservedCounts

Dependencies:abindapeaskpassassertthatBiobaseBiocGenericsbitopscaToolscliclusterGenerationcodacodetoolscolorspacecombinatcommonmarkcpp11crayoncurlDelayedArrayDEoptimdigestdoParalleldplyrexpmfansifarverfastmatchforeachgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2gluegplotsgtablegtoolshttrigraphIRangesisobanditeratorsjsonliteKernelKnnKernSmoothlabelinglatticelifecyclemagrittrmapsmarkdownMASSMatrixMatrixGenericsmatrixStatsmgcvmimemnormtmunsellnlmenumDerivopenssloptimParallelphangornphytoolspillarpkgconfigquadprogR6RColorBrewerRcppRcppArmadillorlangRtsneS4ArraysS4Vectorsscalesscatterplot3dSparseArraySummarizedExperimentsystibbletidyselectUCSC.utilsutf8vctrsviridisLitewithrxfunXVectorzeallotzlibbioc

scMultiSim Basics

Rendered frombasics.Rmdusingknitr::knitron Jun 30 2024.

Last update: 2024-01-16
Started: 2023-05-18

Simulating Spatial Cell-Cell Interactions

Rendered fromspatialCCI.rmdusingknitr::knitron Jun 30 2024.

Last update: 2024-01-16
Started: 2023-05-18

Readme and manuals

Help Manual

Help pageTopics
This function simulates the amplification, library prep, and the sequencing processes..amplifyOneCell
Simulate technical biases.calAmpBias
Generates cifs for cells sampled along the trajectory of cell development.continuousCIF
Divide the observed counts into multiple batches by adding batch effect to each batch.divideBatchesImpl
expand transcript counts to a vector of binaries of the same length of as the number of transcripts.expandToBinary
This function finds the correlation between every pair of genes.getCountCorrMatrix
Get Kineic Parameters for all cells and genes.getParams
Rename the original gene IDs in the GRN table to integers..normalizeGRNParams
sample from truncated normal distribution.rnormTrunc
Add experimental noise to true countsadd_expr_noise
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 true transcript counts for linear structuregen_1branch
Plot the ligand-receptor correlation summarygene_corr_cci
Print the correlations between targets of each regulatorgene_corr_regulator
a pool of gene lengths to sample fromgene_len_pool
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
from transcript length to number of fragments (for the nonUMI protocol)len2nfrag
distribution of kinetic parameters learned from the Zeisel UMI cortex datasetsmatch_params
Get option from an object in the current environmentOP
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
sample from smoothed density functionSampleDen
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