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Successful integration of computer simulation with real world experimentation requires the relationship between simulation and the real-world system to be established. Spartan, described in our 2013 paper in PLoS Computational Biology, is a package of statistical techniques specifically designed to understand this relationship and provide novel biological insight. These techniques help reveal the influence that pathways and components have on simulation behaviour, offering valuable biological insight into aspects of the system under study.

Spartan is open source, implemented within the R statistical environment, and freely available from both the Comprehensive R Archive Network (CRAN) and on this page below. Use of the package is demonstrated via the tutorial published in the R Journal. Example simulation data for each technique described are available in the tabs below.

Getting Spartan

Install from CRAN (install.packages(“spartan”)) (Older versions of spartan are available on the CRAN archive (

Install Version 3.0.2 from source: Linux/Mac | Windows

Install from Github Repository

Instruction Vignettes:

Applying spartan to Understand Parameter Uncertainty in Simulations: Sensitivity Analysis

Analysing Netlogo Simulations Using Netlogo

Expedited and Enriched Analyses Using Emulations & Ensembles

R Journal Publication with Detailed Description and Examples of Using the Spartan Package

Techniques and Tutorial Example Data are all available from