pathwayPCA
This is the released version of pathwayPCA; for the devel version, see pathwayPCA.
All Bioconductor versions of pathwayPCA
3.24 (devel), 3.23 (release), 3.22, 3.21, 3.20, 3.19, 3.18, 3.17, 3.16, 3.15, 3.14, 3.13, 3.12, 3.11, 3.10, 3.9
Integrative Pathway Analysis with Modern PCA Methodology and Gene Selection
Bioconductor version: 3.23 · Package version: 1.28.0
pathwayPCA is an integrative analysis tool that implements the principal component analysis (PCA) based pathway analysis approaches described in Chen et al. (2008), Chen et al. (2010), and Chen (2011). pathwayPCA allows users to: (1) Test pathway association with binary, continuous, or survival phenotypes. (2) Extract relevant genes in the pathways using the SuperPCA and AES-PCA approaches. (3) Compute principal components (PCs) based on the selected genes. These estimated latent variables represent pathway activities for individual subjects, which can then be used to perform integrative pathway analysis, such as multi-omics analysis. (4) Extract relevant genes that drive pathway significance as well as data corresponding to these relevant genes for additional in-depth analysis. (5) Perform analyses with enhanced computational efficiency with parallel computing and enhanced data safety with S4-class data objects. (6) Analyze studies with complex experimental designs, with multiple covariates, and with interaction effects, e.g., testing whether pathway association with clinical phenotype is different between male and female subjects. Citations: Chen et al. (2008) <https://doi.org/10.1093/bioinformatics/btn458>; Chen et al. (2010) <https://doi.org/10.1002/gepi.20532>; and Chen (2011) <https://doi.org/10.2202/1544-6115.1697>.
Author: Gabriel Odom [aut, cre], James Ban [aut], Lizhong Liu [aut], Lily Wang [aut], Steven Chen [aut]
Maintainer: Gabriel Odom <gabriel.odom at med.miami.edu>
Citation
From within R, enter citation("pathwayPCA"):
Gabriel Odom, James Ban, Lizhong Liu, Lily Wang, Steven Chen. pathwayPCA: Integrative Pathway Analysis with Modern PCA Methodology and Gene Selection. doi:10.18129/B9.bioc.pathwayPCA, R package version 1.28.0, https://bioconductor.org/packages/pathwayPCA.
Generated from the package metadata; it may differ from the package's own citation.
Installation
To install this package, start R (version "4.6") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("pathwayPCA")For older versions of R, please refer to the appropriate Bioconductor release.
Details
| Version | 1.28.0 |
| License | GPL-3 |
| URL | <https://gabrielodom.github.io/pathwayPCA/> |
| Bug Reports | https://github.com/gabrielodom/pathwayPCA/issues |
| Last updated | 2026-04-28 |
| In Bioconductor since | BioC 3.9 (R-3.6) (7 years) |
| Downloads rank | 1235 of 2,418 |
| Source branch | RELEASE_3_23 |
| Build report | Bioconductor build system, r-universe |
| biocViews | CellBiology, Classification, CopyNumberVariation, DNAMethylation, DimensionReduction, Epigenetics, FeatureExtraction, FunctionalGenomics, GeneExpression, GenePrediction, GeneSetEnrichment, GeneSignaling, GeneTarget, Genetics, GenomeWideAssociation, GenomicVariation, Lipidomics, Metabolomics, MultipleComparison, Pathways, PrincipalComponent, Proteomics, Regression, SNP, Software, Survival, SystemsBiology, Transcription, Transcriptomics |
| Package Short Url | https://bioconductor.org/packages/pathwayPCA/ |
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("pathwayPCA")| Integrative Pathway Analysis with pathwayPCA | HTML | R Script |
| Suppl. Ch. 1 - Quickstart Guide for New R Users | HTML | R Script |
| Suppl. Ch. 2 - Import and Tidy Data | HTML | R Script |
| Suppl. Ch. 3 - Creating Data Objects | HTML | R Script |
| Suppl. Ch. 4 - Test Pathway Significance | HTML | R Script |
| Suppl. Ch. 5 - Visualizing the Results | HTML | R Script |
| Reference Manual | ||
| NEWS | Text |
Download
Follow the installation instructions to use this package in your R session.
| Source package | pathwayPCA_1.28.0.tar.gz |
| Windows binary (x86_64) | pathwayPCA_1.28.0.zip |
| macOS binary (arm64) | pathwayPCA_1.28.0.tgz |
| macOS binary (x86_64) | pathwayPCA_1.28.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/pathwayPCA |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/pathwayPCA |
| Package Downloads Report | Download Stats |