Package Recipe 'bioconductor-hummingbird'

recipe bioconductor-hummingbird

Bayesian Hidden Markov Model for the detection of differentially methylated regions

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/hummingbird.html
License:: GPL (>=2)
Recipe:: /bioconductor-hummingbird/meta.yaml

A package for detecting differential methylation. It exploits a Bayesian hidden Markov model that incorporates location dependence among genomic loci, unlike most existing methods that assume independence among observations. Bayesian priors are applied to permit information sharing across an entire chromosome for improved power of detection. The direct output of our software package is the best sequence of methylation states, eliminating the use of a subjective, and most of the time an arbitrary, threshold of p-value for determining significance. At last, our methodology does not require replication in either or both of the two comparison groups.

package bioconductor-hummingbird¶

Versions:

1.20.0-0, 1.16.0-0, 1.12.0-0, 1.10.0-0, 1.8.0-1, 1.8.0-0, 1.4.0-2, 1.4.0-1, 1.4.0-0,

1.20.0-0, 1.16.0-0, 1.12.0-0, 1.10.0-0, 1.8.0-1, 1.8.0-0, 1.4.0-2, 1.4.0-1, 1.4.0-0, 1.2.0-0, 1.0.1-0, 1.0.0-1

Depends:

on bioconductor-genomicranges >=1.62.0,<1.63.0
on bioconductor-genomicranges >=1.62.1,<1.63.0a0
on bioconductor-iranges >=2.44.0,<2.45.0
on bioconductor-iranges >=2.44.0,<2.45.0a0
on bioconductor-summarizedexperiment >=1.40.0,<1.41.0
on bioconductor-summarizedexperiment >=1.40.0,<1.41.0a0
on libblas >=3.9.0,<4.0a0
on libgcc >=14
on liblapack >=3.9.0,<4.0a0
on liblzma >=5.8.2,<6.0a0
on libstdcxx >=14
on libzlib >=1.3.1,<2.0a0
on r-base >=4.5,<4.6.0a0
on r-rcpp

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-hummingbird

to add into an existing workspace instead, run:

pixi add bioconductor-hummingbird

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-hummingbird

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-hummingbird

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-hummingbird:<tag>

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