Package Recipe 'bioconductor-mina'

recipe bioconductor-mina

Microbial community dIversity and Network Analysis

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/mina.html
License:: GPL
Recipe:: /bioconductor-mina/meta.yaml

An increasing number of microbiome datasets have been generated and analyzed with the help of rapidly developing sequencing technologies. At present, analysis of taxonomic profiling data is mainly conducted using composition-based methods, which ignores interactions between community members. Besides this, a lack of efficient ways to compare microbial interaction networks limited the study of community dynamics. To better understand how community diversity is affected by complex interactions between its members, we developed a framework (Microbial community dIversity and Network Analysis, mina), a comprehensive framework for microbial community diversity analysis and network comparison. By defining and integrating network-derived community features, we greatly reduce noise-to-signal ratio for diversity analyses. A bootstrap and permutation-based method was implemented to assess community network dissimilarities and extract discriminative features in a statistically principled way.

package bioconductor-mina¶

Versions:

1.18.0-0, 1.14.0-0, 1.10.0-1, 1.10.0-0, 1.8.0-0, 1.6.0-1, 1.6.0-0, 1.2.0-2, 1.2.0-1,

1.18.0-0, 1.14.0-0, 1.10.0-1, 1.10.0-0, 1.8.0-0, 1.6.0-1, 1.6.0-0, 1.2.0-2, 1.2.0-1, 1.2.0-0, 1.0.0-0

Depends:

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-apcluster
on r-base >=4.5,<4.6.0a0
on r-biganalytics
on r-bigmemory
on r-foreach
on r-ggplot2
on r-hmisc
on r-mcl
on r-paralleldist
on r-plyr
on r-rcpp
on r-rcpparmadillo
on r-rcppparallel
on r-reshape2
on r-rspectra
on r-stringr
on tbb-devel >=2022.3.0,<2022.4.0a0

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-mina

to add into an existing workspace instead, run:

pixi add bioconductor-mina

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-mina

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-mina

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-mina:<tag>

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