SBpipe is an open source software tool for automating repetitive tasks in model building and simulation. Using basic YAML configuration files, SBpipe builds a sequence of repeated model simulations or parameter estimations, performs analyses from this generated sequence, and finally generates a LaTeX/PDF report. The parameter estimation pipeline offers analyses of parameter profile likelihood and parameter correlation using samples from the computed estimates. Specific pipelines for scanning of one or two model parameters at the same time are also provided. Pipelines can run on multicore computers, Sun Grid Engine (SGE), or Load Sharing Facility (LSF) clusters, speeding up the processes of model building and simulation. If desired, pipelines can also be executed via Snakemake, a powerful workflow management system. SBpipe can run models implemented in COPASI, Python or coded in any other programming language using Python as a wrapper module. Future support for other software simulators can be dynamically added without affecting the current implementation.
To install SBpipe, see the documentation: HTML or PDF.
The R functions used by SBpipe for data analysis can also be retrieved separately from CRAN (sbpiper), bioconda (r-sbpiper), or from GitHub (sbpiper).
To download the Snakemake workflows for SBpipe, visit the GitHub repository sbpipe_snake.
Citation: Dalle Pezze P, Le Novère N. SBpipe: a collection of pipelines for automating repetitive simulation and analysis tasks. BMC Systems Biology. 2017 Apr;11:46. DOI:10.1186/s12918-017-0423-3
SBpipe is a relatively young project and there is a chance that some error occurs. Issues and feature requests can be notified using the github issue tracking system for SBpipe at the web page: https://github.com/pdp10/sbpipe/issues. To help us better identify and reproduce your problem, some technical info.