pairkat

DOI: 10.18129/B9.bioc.pairkat  

PaIRKAT

Bioconductor version: Release (3.17)

PaIRKAT is model framework for assessing statistical relationships between networks of metabolites (pathways) and an outcome of interest (phenotype). PaIRKAT queries the KEGG database to determine interactions between metabolites from which network connectivity is constructed. This model framework improves testing power on high dimensional data by including graph topography in the kernel machine regression setting. Studies on high dimensional data can struggle to include the complex relationships between variables. The semi-parametric kernel machine regression model is a powerful tool for capturing these types of relationships. They provide a framework for testing for relationships between outcomes of interest and high dimensional data such as metabolomic, genomic, or proteomic pathways. PaIRKAT uses known biological connections between high dimensional variables by representing them as edges of ‘graphs’ or ‘networks.’ It is common for nodes (e.g. metabolites) to be disconnected from all others within the graph, which leads to meaningful decreases in testing power whether or not the graph information is included. We include a graph regularization or ‘smoothing’ approach for managing this issue.

Author: Charlie Carpenter [aut], Cameron Severn [aut], Max McGrath [cre, aut]

Maintainer: Max McGrath <max.mcgrath at ucdenver.edu>

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

Installation

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

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

BiocManager::install("pairkat")

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("pairkat")

 

HTML R Script using-pairkat
PDF   Reference Manual
Text   NEWS

Details

biocViews GraphAndNetwork, KEGG, Metabolomics, Network, Pathways, Regression, Software
Version 1.6.0
In Bioconductor since BioC 3.14 (R-4.1) (2 years)
License GPL-3
Depends R (>= 4.1)
Imports SummarizedExperiment, KEGGREST, igraph, data.table, methods, stats, magrittr, CompQuadForm, tibble
LinkingTo
Suggests rmarkdown, knitr, BiocStyle, dplyr
SystemRequirements
Enhances
URL
BugReports https://github.com/Ghoshlab/pairkat/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

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

Source Package pairkat_1.6.0.tar.gz
Windows Binary pairkat_1.6.0.zip
macOS Binary (x86_64) pairkat_1.6.0.tgz
macOS Binary (arm64) pairkat_1.6.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/pairkat
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/pairkat
Bioc Package Browser https://code.bioconductor.org/browse/pairkat/
Package Short Url https://bioconductor.org/packages/pairkat/
Package Downloads Report Download Stats
Old Source Packages for BioC 3.17 Source Archive

Documentation »

Bioconductor

R / CRAN packages and documentation

Support »

Please read the posting guide. Post questions about Bioconductor to one of the following locations: