MOSim: Multi-Omics Simulation in R
As multi-omics sequencing technologies advance, the need for simulation tools capable of generating realistic and diverse (bulk and single-cell) multi-omics datasets for method testing and benchmarking becomes increasingly important. We present MOSim, an R package that simulates both bulk (via mosim function) and single-cell (via sc_mosim function) multi-omics data. The mosim function generates bulk transcriptomics data (RNA-seq) and additional regulatory omics layers (ATAC-seq, miRNA-seq, ChIP-seq, Methyl-seq and Transcription Factors), while sc_mosim simulates single-cell transcriptomics data (scRNA-seq) with scATAC-seq and Transcription Factors as regulatory layers. The tool supports various experimental designs, including simulation of gene co-expression patterns, biological replicates, and differential expression between conditions. MOSim enables users to generate quantification matrices for each simulated omics data type, capturing the heterogeneity and complexity of bulk and single-cell multi-omics datasets. Furthermore, MOSim provides differentially abundant features within each omics layer and elucidates the active regulatory relationships between regulatory omics and gene expression data at both bulk and single-cell levels. By leveraging MOSim, researchers will be able to generate realistic and customizable bulk and single-cell multi-omics datasets to benchmark and validate analytical methods specifically designed for the integrative analysis of diverse regulatory omics data. Key PointsO_LIMOSim is capable of generating synthetic datasets for a broad spectrum of omics types, supporting bulk RNA-seq, ChIP-seq, ATAC-seq, miRNA-seq, Methyl-seq, and transcription factor data, as well as single-cell omics, including scRNA-seq, scATAC-seq, and transcription factors. C_LIO_LIMOSim enables the robust simulation of complex, many-to-many regulatory relationships across molecular layers, faithfully capturing intricate regulatory patterns. C_LIO_LIOffering extensive options for customization, MOSims flexible experimental design and parameterization empowers users to simulate count matrices and multilayer regulatory networks, tailoring simulations to diverse experimental scenarios and omics types. C_LI