pathwayPCA: an R package for integrative pathway analysis with modern PCA methodology and gene selection
Initial Date: 2017-10-19
With the advance in high-throughput technology for molecular assays, multi-omics datasets have become increasingly available. However, most currently available pathway analysis software do not provide estimates on sample-specific pathway activities, and provide little or no functionalities for analyzing multiple types of omics data simultaneously. To address these challenges, we present pathwayPCA, a unique integrative pathway analysis software that utilizes modern statistical methodology on principal component analysis (PCA) and gene selection.
The main features of pathwayPCA include:
The stable build of our package will be available on Bioconductor in May of 2019. To access Bioconductor packages, first install BiocManager, then use BiocManager to install this package:
Because we are currently in the development phase for version 2 of this package, you can install the package from GitHub. In order to install a package from GitHub, you will need the
devtools:: package (https://github.com/r-lib/devtools) and either Rtools (for Windows) or Xcode (for Mac). Then you can install the development version of the
pathwayPCA package from GitHub:
If you are using R version 3.5 or later, and want access to the frozen build for this version, please use
If you find bugs in our code, or you feel that some functionality is poorly explained, please submit an issue ticket here: https://github.com/gabrielodom/pathwayPCA/issues. Helpful issue tickets give a minimum working and reproducible example whenever possible. Please peruse the included links for advice on writing good help ticket requests.
We aim to write a package to collect, organize, and document a suite of existing
R scripts and files. The purpose of this is to ensure that biologists and bioinformaticians will be easily able to apply our work to their existing data. This package will address pathway to response attribution only. Our core values for this project are as follows: