PanViz

This package is deprecated. It will probably be removed from Bioconductor. Please refer to the package end-of-life guidelines for more information.

This is the development version of PanViz; for the stable release version, see PanViz.

Integrating Multi-Omic Network Data With Summay-Level GWAS Data


Bioconductor version: Development (3.21)

This pacakge integrates data from the Kyoto Encyclopedia of Genes and Genomes (KEGG) with summary-level genome-wide association (GWAS) data, such as that provided by the GWAS Catalog or GWAS Central databases, or a user's own study or dataset, in order to produce biological networks, termed IMONs (Integrated Multi-Omic Networks). IMONs can be used to analyse trait-specific polymorphic data within the context of biochemical and metabolic reaction networks, providing greater biological interpretability for GWAS data.

Author: Luca Anholt [cre, aut]

Maintainer: Luca Anholt <la1317 at ic.ac.uk>

Citation (from within R, enter citation("PanViz")):

Installation

To install this package, start R (version "4.5") and enter:


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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("PanViz")

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

Documentation

Reference Manual PDF

Details

biocViews GenomeWideAssociation, GraphAndNetwork, KEGG, Metabolomics, Network, Reactome, SNP, Software
Version 1.9.1
In Bioconductor since BioC 3.16 (R-4.2) (2 years)
License Artistic-2.0
Depends R (>= 4.2.0)
Imports tidyr, stringr, dplyr, tibble, magrittr, futile.logger, utils, easycsv, rentrez, igraph, RColorBrewer, data.table, colorspace, grDevices, rlang, methods
System Requirements
URL https://github.com/LucaAnholt/PanViz
Bug Reports https://github.com/LucaAnholt/PanViz/issues
See More
Suggests testthat (>= 3.0.0), BiocStyle, knitr, rmarkdown, networkD3
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Package Archives

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

Source Package
Windows Binary (x86_64)
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/PanViz
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/PanViz
Package Short Url https://bioconductor.org/packages/PanViz/
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