Package Recipe 'bioconductor-rmspc'

recipe bioconductor-rmspc

Multiple Sample Peak Calling

Homepage:: https://bioconductor.org/packages/3.18/bioc/html/rmspc.html
License:: GPL-3
Recipe:: /bioconductor-rmspc/meta.yaml

The rmspc package runs MSPC (Multiple Sample Peak Calling) software using R. The analysis of ChIP-seq samples outputs a number of enriched regions (commonly known as "peaks"), each indicating a protein-DNA interaction or a specific chromatin modification. When replicate samples are analyzed, overlapping peaks are expected. This repeated evidence can therefore be used to locally lower the minimum significance required to accept a peak. MSPC uses combined evidence from replicated experiments to evaluate peak calling output, rescuing peaks, and reduce false positives. It takes any number of replicates as input and improves sensitivity and specificity of peak calling on each, and identifies consensus regions between the input samples.

package bioconductor-rmspc¶

Versions:

1.16.0-0, 1.8.0-0, 1.6.0-0, 1.4.0-0, 1.0.0-0

Depends:

on bioconductor-genomicranges >=1.62.0,<1.63.0
on bioconductor-rtracklayer >=1.70.0,<1.71.0
on r-base >=4.5,<4.6.0a0
on r-biocmanager
on r-processx
on r-stringr

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-rmspc

to add into an existing workspace instead, run:

pixi add bioconductor-rmspc

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-rmspc

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-rmspc

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-rmspc:<tag>

(see bioconductor-rmspc/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-rmspc/README.html)