GraphExperiment
This is the released version of GraphExperiment; for the devel version, see GraphExperiment.
S4 Class for Quantitative Data and Associated Networks
Bioconductor version: Release (3.23)
GraphExperiment provides users and developers with an S4 class that extends `SingleCellExperiment` by offering infrastructure to store and retrieve networks (`igraph` objects) representing how assay features and/or observations are associated with each other. The class was designed to store networks inferred from high-dimensional quantitative data, with feature-feature networks including gene coexpression networks (GCNs), gene regulatory networks (GRNs), and co-abundance networks (from proteomics and metabolomics), and observation-observation network including cell-cell distances, species-species relationships, and sample-sample similarities.
Author: Fabricio Almeida-Silva [aut, cre]
Maintainer: Fabricio Almeida-Silva <fabricio_almeidasilva at hotmail.com>
citation("GraphExperiment")):
Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M (2015). "Orchestrating high-throughput genomic analysis with Bioconductor." Nature Methods, 12(2), 115–121. doi:10.1038/nmeth.3252.
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JYH, Zhang J (2004). "Bioconductor: open software development for computational biology and bioinformatics." Genome Biology, 5(10), R80. doi:10.1186/gb-2004-5-10-r80.
Installation
To install this package, start R (version "4.6") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("GraphExperiment")
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("GraphExperiment")| Introduction to the GraphExperiment class | HTML | R Script |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | DataImport, DataRepresentation, GeneExpression, Infrastructure, Network, SingleCell, Software, Transcriptomics |
| Version | 1.0.2 |
| In Bioconductor since | BioC 3.23 (R-4.6) (< 6 months) |
| License | GPL-3 |
| Depends | SingleCellExperiment, igraph |
| Imports | methods, SummarizedExperiment, BiocBaseUtils, S4Vectors |
| System Requirements | |
| URL | https://github.com/almeidasilvaf/GraphExperiment |
| Bug Reports | https://support.bioconductor.org/tag/GraphExperiment |
See More
| Suggests | knitr, BiocStyle, testthat, rmarkdown, covr, sessioninfo |
| Linking To | |
| Enhances | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | GraphExperiment_1.0.2.tar.gz |
| Windows Binary (x86_64) | GraphExperiment_1.0.2.zip (64-bit only) |
| macOS Binary (big-sur-x86_64) | GraphExperiment_1.0.2.tgz |
| macOS Binary (sonoma-arm64) | GraphExperiment_1.0.2.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/GraphExperiment |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/GraphExperiment |
| Bioc Package Browser | https://code.bioconductor.org/browse/GraphExperiment/ |
| Package Short Url | https://bioconductor.org/packages/GraphExperiment/ |
| Package Downloads Report | Download Stats |
| Old Source Packages for BioC 3.23 | Source Archive |