Package Recipe 'bioconductor-plsdabatch'

recipe bioconductor-plsdabatch

PLSDA-batch

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/PLSDAbatch.html
License:: GPL-3
Recipe:: /bioconductor-plsdabatch/meta.yaml

A novel framework to correct for batch effects prior to any downstream analysis in microbiome data based on Projection to Latent Structures Discriminant Analysis. The main method is named “PLSDA-batch”. It first estimates treatment and batch variation with latent components, then subtracts batch-associated components from the data whilst preserving biological variation of interest. PLSDA-batch is highly suitable for microbiome data as it is non-parametric, multivariate and allows for ordination and data visualisation. Combined with centered log-ratio transformation for addressing uneven library sizes and compositional structure, PLSDA-batch addresses all characteristics of microbiome data that existing correction methods have ignored so far. Two other variants are proposed for 1/ unbalanced batch x treatment designs that are commonly encountered in studies with small sample sizes, and for 2/ selection of discriminative variables amongst treatment groups to avoid overfitting in classification problems. These two variants have widened the scope of applicability of PLSDA-batch to different data settings.

package bioconductor-plsdabatch¶

Versions:

1.6.0-0, 1.2.0-0

Depends:

on bioconductor-biobase >=2.70.0,<2.71.0
on bioconductor-biocstyle >=2.38.0,<2.39.0
on bioconductor-mixomics >=6.34.0,<6.35.0
on bioconductor-treesummarizedexperiment >=2.18.0,<2.19.0
on r-base >=4.5,<4.6.0a0
on r-ggplot2
on r-ggpubr
on r-gridextra
on r-lmertest
on r-performance
on r-pheatmap
on r-rdpack
on r-scales
on r-vegan

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-plsdabatch

to add into an existing workspace instead, run:

pixi add bioconductor-plsdabatch

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-plsdabatch

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-plsdabatch

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-plsdabatch:<tag>

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