The goal of simpipe is to establish a standard pipeline to estimating parameters from real datasets, simulating single-cell RNA-seq datasets and evaluating the simulated data from general and functional perspectives.

You can install the development version of simpipe from GitHub with:

# install.packages("devtools")
devtools::install_github("duohongrui/simmethods")
devtools::install_github("duohongrui/simpipe")

if you want to use simpipe to simulate datasets with trajectory information, please install tislingshot first by:

# install.packages("devtools")
devtools::install_github("dynverse/ti_slingshot/package/")

The documentation of simpipe is availabel at our Simsite. In addition, you can also learn the usage of every simulation methods we have collected.

Users can also download our simpipe Docker Image and use simpipe2docker package for linking R environmrnt and the Docker container. For more details, please refer to Simsite.

If you have any question, please email to Hongrui Duo ([email protected]) or raise an issue for that.

Duo H, Li Y, Lan Y, et al. Systematic evaluation with practical guidelines for single-cell and spatially resolved transcriptomics data simulation under multiple scenarios. Genome Biology, 2024, 25(1): 145.