GRaNIE

DOI: 10.18129/B9.bioc.GRaNIE  

This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see GRaNIE.

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

Bioconductor version: 3.17

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 celltype 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 bulk RNAseq and open chromatin (e.g., using ATACseq or ChIPseq for open chromatin marks) and optionally TF activity 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.

Author: Christian Arnold [cre, aut], Judith Zaugg [aut], Rim Moussa [aut], Armando Reyes-Palomares [ctb], Giovanni Palla [ctb], Maksim Kholmatov [ctb]

Maintainer: Christian Arnold <chrarnold at web.de>

Installation

To install this package, start R (version "4.3") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("GRaNIE")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("GRaNIE")

 

HTML	R Script	Package Details
HTML	R Script	Single-cell eGRN inference
HTML	R Script	Workflow example
PDF		Reference Manual
Text		NEWS

Details

biocViews	ATACSeq, BiomedicalInformatics, ChIPSeq, GeneExpression, GeneRegulation, GeneSetEnrichment, Genetics, GraphAndNetwork, NetworkInference, RNASeq, Regression, Software, Transcription, Transcriptomics
Version	1.4.1
In Bioconductor since	BioC 3.15 (R-4.2) (1.5 years)
License	Artistic-2.0
Depends	R (>= 4.2.0)
Imports	futile.logger, checkmate, patchwork, reshape2, data.table, matrixStats, Matrix, GenomicRanges, RColorBrewer, ComplexHeatmap, DESeq2, circlize, progress, utils, methods, stringr, scales, igraph, S4Vectors, ggplot2, rlang, Biostrings, GenomeInfoDb(>= 1.34.8), SummarizedExperiment, forcats, gridExtra, limma, tidyselect, readr, grid, tidyr, dplyr, stats, grDevices, graphics, magrittr, tibble, viridis, colorspace, biomaRt, topGO, AnnotationHub, ensembldb
LinkingTo
Suggests	knitr, BSgenome.Hsapiens.UCSC.hg19, BSgenome.Hsapiens.UCSC.hg38, BSgenome.Mmusculus.UCSC.mm10, BSgenome.Mmusculus.UCSC.mm9, BSgenome.Rnorvegicus.UCSC.rn6, BSgenome.Rnorvegicus.UCSC.rn7, BSgenome.Dmelanogaster.UCSC.dm6, BSgenome.Mmulatta.UCSC.rheMac10, TxDb.Hsapiens.UCSC.hg19.knownGene, TxDb.Hsapiens.UCSC.hg38.knownGene, TxDb.Mmusculus.UCSC.mm10.knownGene, TxDb.Mmusculus.UCSC.mm9.knownGene, TxDb.Rnorvegicus.UCSC.rn6.refGene, TxDb.Rnorvegicus.UCSC.rn7.refGene, TxDb.Dmelanogaster.UCSC.dm6.ensGene, TxDb.Mmulatta.UCSC.rheMac10.refGene, org.Hs.eg.db, org.Mm.eg.db, org.Rn.eg.db, org.Dm.eg.db, org.Mmu.eg.db, IHW, clusterProfiler, ReactomePA, DOSE, BiocFileCache, ChIPseeker, testthat (>= 3.0.0), BiocStyle, csaw, BiocParallel, WGCNA, variancePartition, purrr, EDASeq, JASPAR2022, TFBSTools, motifmatchr, rbioapi
SystemRequirements
Enhances
URL	https://grp-zaugg.embl-community.io/GRaNIE
BugReports	https://git.embl.de/grp-zaugg/GRaNIE/issues
Depends On Me
Imports Me
Suggests Me
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Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package	GRaNIE_1.4.1.tar.gz
Windows Binary	GRaNIE_1.4.1.zip (64-bit only)
macOS Binary (x86_64)	GRaNIE_1.4.1.tgz
macOS Binary (arm64)	GRaNIE_1.4.1.tgz
Source Repository	git clone https://git.bioconductor.org/packages/GRaNIE
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/GRaNIE
Bioc Package Browser	https://code.bioconductor.org/browse/GRaNIE/
Package Short Url	https://bioconductor.org/packages/GRaNIE/
Package Downloads Report	Download Stats