Package Recipe 'bioconductor-bdmmacorrect'

recipe bioconductor-bdmmacorrect

Meta-analysis for the metagenomic read counts data from different cohorts

Homepage:: https://bioconductor.org/packages/3.17/bioc/html/BDMMAcorrect.html
License:: GPL (>= 2)
Recipe:: /bioconductor-bdmmacorrect/meta.yaml
Links:: biotools: bdmmacorrect

Metagenomic sequencing techniques enable quantitative analyses of the microbiome. However, combining the microbial data from these experiments is challenging due to the variations between experiments. The existing methods for correcting batch effects do not consider the interactions between variables—microbial taxa in microbial studies—and the overdispersion of the microbiome data. Therefore, they are not applicable to microbiome data. We develop a new method, Bayesian Dirichlet-multinomial regression meta-analysis (BDMMA), to simultaneously model the batch effects and detect the microbial taxa associated with phenotypes. BDMMA automatically models the dependence among microbial taxa and is robust to the high dimensionality of the microbiome and their association sparsity.

package bioconductor-bdmmacorrect¶

Versions:

1.18.1-1, 1.18.1-0, 1.16.0-1, 1.16.0-0, 1.12.0-2, 1.12.0-1, 1.12.0-0, 1.10.0-0, 1.8.0-1,

1.18.1-1, 1.18.1-0, 1.16.0-1, 1.16.0-0, 1.12.0-2, 1.12.0-1, 1.12.0-0, 1.10.0-0, 1.8.0-1, 1.8.0-0, 1.6.0-0, 1.4.0-0, 1.2.0-1, 1.0.0-0

Depends:

on bioconductor-summarizedexperiment >=1.32.0,<1.33.0
on bioconductor-summarizedexperiment >=1.32.0,<1.33.0a0
on libblas >=3.9.0,<4.0a0
on libgcc-ng >=12
on liblapack >=3.9.0,<4.0a0
on libstdcxx-ng >=12
on r-ape
on r-base >=4.3,<4.4.0a0
on r-ellipse
on r-ggplot2
on r-rcpp >=0.12.12
on r-rcpparmadillo
on r-rcppeigen
on r-vegan

Additional platforms:

linux-aarch64

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-bdmmacorrect

to add into an existing workspace instead, run:

pixi add bioconductor-bdmmacorrect

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-bdmmacorrect

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-bdmmacorrect

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-bdmmacorrect:<tag>

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