Package Recipe 'bioconductor-systempiper'

recipe bioconductor-systempiper

systemPipeR: Workflow Environment for Data Analysis and Report Generation

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/systemPipeR.html
License:: Artistic-2.0
Recipe:: /bioconductor-systempiper/meta.yaml
Links:: biotools: systempiper

systemPipeR is a multipurpose data analysis workflow environment that unifies R with command-line tools. It enables scientists to analyze many types of large- or small-scale data on local or distributed computer systems with a high level of reproducibility, scalability and portability. At its core is a command-line interface (CLI) that adopts the Common Workflow Language (CWL). This design allows users to choose for each analysis step the optimal R or command-line software. It supports both end-to-end and partial execution of workflows with built-in restart functionalities. Efficient management of complex analysis tasks is accomplished by a flexible workflow control container class. Handling of large numbers of input samples and experimental designs is facilitated by consistent sample annotation mechanisms. As a multi-purpose workflow toolkit, systemPipeR enables users to run existing workflows, customize them or design entirely new ones while taking advantage of widely adopted data structures within the Bioconductor ecosystem. Another important core functionality is the generation of reproducible scientific analysis and technical reports. For result interpretation, systemPipeR offers a wide range of plotting functionality, while an associated Shiny App offers many useful functionalities for interactive result exploration. The vignettes linked from this page include (1) a general introduction, (2) a description of technical details, and (3) a collection of workflow templates.

package bioconductor-systempiper¶

Versions:

2.16.3-0, 2.12.0-0, 2.8.0-0, 2.6.3-0, 2.4.0-0, 2.0.0-0, 1.26.2-0, 1.24.3-0, 1.24.2-0,

2.16.3-0, 2.12.0-0, 2.8.0-0, 2.6.3-0, 2.4.0-0, 2.0.0-0, 1.26.2-0, 1.24.3-0, 1.24.2-0, 1.22.0-0, 1.20.0-0, 1.18.2-0, 1.16.0-0, 1.14.0-0, 1.12.0-0, 1.10.2-0, 1.9.0-0, 1.4.8-0, 1.4.7-0

Depends:

on bioconductor-biocgenerics >=0.56.0,<0.57.0
on bioconductor-biostrings >=2.78.0,<2.79.0
on bioconductor-genomicranges >=1.62.0,<1.63.0
on bioconductor-rsamtools >=2.26.0,<2.27.0
on bioconductor-s4vectors >=0.48.0,<0.49.0
on bioconductor-shortread >=1.68.0,<1.69.0
on bioconductor-summarizedexperiment >=1.40.0,<1.41.0
on r-base >=4.5,<4.6.0a0
on r-crayon
on r-ggplot2
on r-htmlwidgets
on r-magrittr
on r-stringr
on r-yaml

Additional platforms:

Installation¶

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi¶

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install bioconductor-systempiper

to add into an existing workspace instead, run:

pixi add bioconductor-systempiper

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda¶

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install bioconductor-systempiper

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-systempiper

with envname being the name of the desired environment.

Container¶

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

docker pull quay.io/biocontainers/bioconductor-systempiper:<tag>

(see bioconductor-systempiper/tags for valid values for <tag>).

Integrated deployment¶

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

Download stats¶

Link to this page¶

Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-systempiper/README.html)