Motivation: Single cell RNA-seq (scRNA-seq) count data shows many differences compared to bulk RNA-seq count data, making the application of many RNA-seq preprocessing/analysis methods not straightforward or even inappropriate.
For this reason, the development of new methods for handling scRNA-seq count data is currently one of the most active research field in bioinformatics. To help the development of such new methods, the availability of simulated data could play a pivotal role. However, only few scRNA-seq count data simulators are available, often showing poor or not demonstrated similarity with real data.
Results: In this work we present SPARSim, a scRNA-seq count data simulator based on a Gamma-Multivariate Hypergeometric model. We demonstrate that SPARSim allows to generate count data that resemble real data in terms of counts intensity, variability and sparsity, performing comparable or better than one of the most used scRNA-seq simulator, Splat. In particular, SPARSim simulated count matrices well resemble the distribution of zeros across different expression intensities observed in real count data.
The last version of SPARSim R package is available on GitLab: https://gitlab.com/sysbiobig/sparsim
Previous versions of the SPARSim R package are available below.