Package Recipe 'bioconductor-tbsignatureprofiler'

recipe bioconductor-tbsignatureprofiler

Profile RNA-Seq Data Using TB Pathway Signatures

Homepage:: https://bioconductor.org/packages/3.18/bioc/html/TBSignatureProfiler.html
License:: MIT + file LICENSE
Recipe:: /bioconductor-tbsignatureprofiler/meta.yaml

Gene signatures of TB progression, TB disease, and other TB disease states have been validated and published previously. This package aggregates known signatures and provides computational tools to enlist their usage on other datasets. The TBSignatureProfiler makes it easy to profile RNA-Seq data using these signatures and includes common signature profiling tools including ASSIGN, GSVA, and ssGSEA. Original models for some gene signatures are also available. A shiny app provides some functionality alongside for detailed command line accessibility.

package bioconductor-tbsignatureprofiler¶

Versions:

1.22.0-0, 1.14.0-0, 1.12.0-0, 1.10.0-0, 1.6.0-0, 1.2.0-1, 1.2.0-0, 1.0.0-0

Depends:

on bioconductor-assign >=1.46.0,<1.47.0
on bioconductor-biocparallel >=1.44.0,<1.45.0
on bioconductor-complexheatmap >=2.26.0,<2.27.0
on bioconductor-deseq2 >=1.50.0,<1.51.0
on bioconductor-edger >=4.8.0,<4.9.0
on bioconductor-gsva >=2.4.0,<2.5.0
on bioconductor-s4vectors >=0.48.0,<0.49.0
on bioconductor-singscore >=1.30.0,<1.31.0
on bioconductor-summarizedexperiment >=1.40.0,<1.41.0
on r-base >=4.5,<4.6.0a0
on r-dt
on r-gdata
on r-ggplot2
on r-glmnet
on r-hgnchelper
on r-magrittr
on r-proc
on r-rcolorbrewer
on r-reshape2
on r-rocit
on r-tibble

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-tbsignatureprofiler

to add into an existing workspace instead, run:

pixi add bioconductor-tbsignatureprofiler

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-tbsignatureprofiler

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-tbsignatureprofiler

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-tbsignatureprofiler:<tag>

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