Package Recipe 'bioconductor-granie'

recipe bioconductor-granie

GRaNIE: Reconstruction cell type specific gene regulatory networks including enhancers using single-cell or bulk chromatin accessibility and RNA-seq data

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/GRaNIE.html
License:: Artistic-2.0
Recipe:: /bioconductor-granie/meta.yaml

Genetic variants associated with diseases often affect non-coding regions, thus likely having a regulatory role. To understand the effects of genetic variants in these regulatory regions, identifying genes that are modulated by specific regulatory elements (REs) is crucial. The effect of gene regulatory elements, such as enhancers, is often cell-type specific, likely because the combinations of transcription factors (TFs) that are regulating a given enhancer have cell-type specific activity. This TF activity can be quantified with existing tools such as diffTF and captures differences in binding of a TF in open chromatin regions. Collectively, this forms a gene regulatory network (GRN) with cell-type and data-specific TF-RE and RE-gene links. Here, we reconstruct such a GRN using single-cell or bulk RNAseq and open chromatin (e.g., using ATACseq or ChIPseq for open chromatin marks) and optionally (Capture) Hi-C data. Our network contains different types of links, connecting TFs to regulatory elements, the latter of which is connected to genes in the vicinity or within the same chromatin domain (TAD). We use a statistical framework to assign empirical FDRs and weights to all links using a permutation-based approach.

package bioconductor-granie¶

Versions:

1.14.0-0, 1.10.0-0, 1.6.1-0, 1.4.1-0, 1.2.0-0

Depends:

on bioconductor-annotationhub >=4.0.0,<4.1.0
on bioconductor-biomart >=2.66.0,<2.67.0
on bioconductor-biostrings >=2.78.0,<2.79.0
on bioconductor-complexheatmap >=2.26.0,<2.27.0
on bioconductor-deseq2 >=1.50.0,<1.51.0
on bioconductor-ensembldb >=2.34.0,<2.35.0
on bioconductor-genomeinfodb >=1.46.0,<1.47.0
on bioconductor-genomicranges >=1.62.0,<1.63.0
on bioconductor-limma >=3.66.0,<3.67.0
on bioconductor-s4vectors >=0.48.0,<0.49.0
on bioconductor-summarizedexperiment >=1.40.0,<1.41.0
on bioconductor-topgo >=2.62.0,<2.63.0
on r-base >=4.5,<4.6.0a0
on r-checkmate
on r-circlize
on r-colorspace
on r-data.table
on r-dplyr
on r-forcats
on r-futile.logger
on r-ggplot2
on r-gridextra
on r-igraph
on r-magrittr
on r-matrix
on r-matrixstats
on r-patchwork >=1.2.0
on r-progress
on r-rcolorbrewer
on r-readr
on r-reshape2
on r-rlang
on r-scales
on r-stringr
on r-tibble
on r-tidyr >=1.3.0
on r-tidyselect
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 bioconductor-granie

to add into an existing workspace instead, run:

pixi add bioconductor-granie

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-granie

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-granie

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-granie:<tag>

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