pdp10/sbpiper: Data Analysis Functions for 'SBpipe' Package

Provides an API for analysing repetitive parameter estimations and simulations of mathematical models. Examples of mathematical models are Ordinary Differential equations (ODEs) or Stochastic Differential Equations (SDEs) models. Among the analyses for parameter estimation 'sbpiper' calculates statistics and generates plots for parameter density, PCA of the best fits, parameter profile likelihood estimations (PLEs), and 2D parameter PLEs. These results can be generated using all or a subset of the best computed parameter sets. Among the analyses for model simulation 'sbpiper' calculates statistics and generates plots for deterministic and stochastic time courses via cartesian and heatmap plots. Plots for the scan of one or two model parameters can also be generated. This package is primarily used by the software 'SBpipe'. Citation: Dalle Pezze P, Le Novère N. SBpipe: a collection of pipelines for automating repetitive simulation and analysis tasks. BMC Systems Biology. 2017;11:46. <doi:10.1186/s12918-017-0423-3>.

Getting started

Package details

Maintainer
LicenseMIT + file LICENSE
Version1.9.0
URL https://github.com/pdp10/sbpiper
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("pdp10/sbpiper")
pdp10/sbpiper documentation built on July 8, 2018, 11:12 a.m.