recipe r-sbpiper

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>.

Homepage:

https://github.com/pdp10/sbpiper

License:

MIT / MIT

Recipe:

/r-sbpiper/meta.yaml

Links:

doi: 10.1186/s12918-017-0423-3

package r-sbpiper

(downloads) docker_r-sbpiper

versions:
1.9.0-9,  1.9.0-8,  1.9.0-7,  1.9.0-6,  1.9.0-5,  1.9.0-4,  1.9.0-3,  1.9.0-2,  1.9.0-1, 

1.9.0-9,  1.9.0-8,  1.9.0-7,  1.9.0-6,  1.9.0-5,  1.9.0-4,  1.9.0-3,  1.9.0-2,  1.9.0-1,  1.8.0-0

depends r-base:

>=4.4,<4.5.0a0

depends r-colorramps:

depends r-data.table:

depends r-factoextra:

depends r-factominer:

depends r-ggplot2:

>=2.2.0

depends r-hmisc:

depends r-reshape2:

depends r-scales:

depends r-stringr:

requirements:

additional platforms:

Installation

You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install r-sbpiper

and update with::

   mamba update r-sbpiper

To create a new environment, run:

mamba create --name myenvname r-sbpiper

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull quay.io/biocontainers/r-sbpiper:<tag>

(see `r-sbpiper/tags`_ for valid values for ``<tag>``)

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