scMultiSim: simulation of multi-modality single cell data guided by cell-cell interactions and gene regulatory networks

Simulated single-cell data is widely used to aid in designing and benchmarking computational methods due to the scarcity of experimental ground truth. Recently, an increasing number of computational methods have been developed to address various computational problems with single-cell data, including cell clustering, trajectory inference, integration of data from multiple batches and modalities, inference of gene regulatory networks (GRNs) and cell-cell interactions. Simulators that are designed to test a certain computational problem model only the particular factors that affect the output data; whereas modelling as many biological factors as possible into the simulation allows the generated data to have realistic complexity and can be used to benchmark a wider range of computational methods. Here, we present scMultiSim, an in silico simulator that generates multi-modality data of single-cells, including gene expression, chromatin accessibility, RNA velocity, and spatial cell locations while accounting for the relationships between modalities. We proposed a unified framework to jointly model biological factors including cell-cell interactions, with-in-cell GRNs and chromatin accessibility, so all their effects simultaneously present in the output data. Users enjoy unprecedented flexibility by having full control of the cell population and the ability to fine-tune each factor’s effect on the underlying model. We also provide options to simulate technical variations including batch effects to make the output resemble real data. We verified the simulated biological effects and demonstrated scMultiSim’s applications by benchmarking four computational tasks on single-cell multi-omics data: GRN inference, RNA velocity estimation, integration of single-cell datasets from multiple batches and modalities, and analysis of cell-cell interaction using the cell spatial location data. To our knowledge, scMultiSim is the only simulator of single cell data that can perform benchmarking for all these four challenging computational tasks.