Package Recipe 'r-strainspy' — Bioconda documentation

recipe r-strainspy

Strain level microbiome wide association studies

Homepage:: gtonkinhill/strainspy
License:: MIT / MIT
Recipe:: /r-strainspy/meta.yaml

Fits statistical models to detect microbial strains associated with a phenotype. For small sample sizes, models can be fitted using empirical Bayes maximum a posteriori (MAP) priors to improve detection power. Supports various experimental design scenarios, including repeated measures.

package r-strainspy#

Versions:

0.99.3-0, 0.99.1-0

Depends:

on bioconductor-biocparallel
on bioconductor-ggtree
on bioconductor-s4vectors
on bioconductor-summarizedexperiment
on r-ape
on r-base >=4.5,<4.6.0a0
on r-data.table
on r-dplyr
on r-ggforce
on r-ggplot2
on r-ggrepel
on r-ggthemes
on r-glmmtmb
on r-harmonicmeanp
on r-lmertest
on r-magrittr
on r-matrix
on r-patchwork
on r-purrr
on r-r.utils >=2.13.0
on r-rlang
on r-stringr
on r-tibble
on r-tidyr
on r-viridis

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 r-strainspy

to add into an existing workspace instead, run:

pixi add r-strainspy

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 r-strainspy

Alternatively, to install into a new environment, run:

conda create -n envname r-strainspy

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/r-strainspy:<tag>

(see r-strainspy/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

.. Create all the necessary plots for each package by loading all the correct specs and data. Important points on the place and implementation of this script block: 1. It is here, and not in a separate HTML file, as it needs to have the `package.name` rendered in for each package. 2. All packages are handled in one `window.onload` function, as multiple instances of this throughout a (rendered) HTML just overwrite each other.

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/r-strainspy/README.html)