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")
):
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.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("pairkat")
HTML | R Script | using-pairkat |
Reference Manual | ||
Text | NEWS |
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 |
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 |
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