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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 (3.19)

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")):


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biocViews GenomeWideAssociation, GraphAndNetwork, KEGG, Metabolomics, Network, Reactome, SNP, Software
Version 1.5.0
In Bioconductor since BioC 3.16 (R-4.2) (1.5 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
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Suggests testthat (>= 3.0.0), BiocStyle, knitr, rmarkdown, networkD3
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Source Package PanViz_1.5.0.tar.gz
Windows Binary PanViz_1.5.0.zip
macOS Binary (x86_64) PanViz_1.5.0.tgz
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Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/PanViz
Bioc Package Browser https://code.bioconductor.org/browse/PanViz/
Package Short Url https://bioconductor.org/packages/PanViz/
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