README.md

BioPlex

R-side access to PPI data from Gygi lab

Citation

If you use the BioPlex R package in published research, please cite:

Ludwig Geistlinger, Roger Vargas Jr, Tyrone Lee, Joshua Pan, Edward Huttlin, Robert Gentleman (2023) BioPlexR and BioPlexPy: integrated data products for the analysis of human protein interactions. Bioinformatics. doi: 10.1093/bioinformatics/btad091.

Installation

Installation from Bioconductor

Users interested in using the stable release version of the BioPlex package: please follow the installation instructions here. This is the recommended way of installing the package.

Installation from GitHub

It is also possible to install the package directly from GitHub. This is for users/developers interested in using the latest development version of the BioPlex package.

Make sure to have the latest release version of R and Bioconductor installed.

Then proceed from within R via:

BiocManager::install("ccb-hms/BioPlex") 

NOTE: you will need the remotes package to install from github.

To build the package vignettes upon installation use:

BiocManager::install("ccb-hms/BioPlex",
                     build_vignettes = TRUE,
                     dependencies = TRUE)

Once you have the package installed, you can inspect the vignettes from within R via:

browseVignettes("BioPlex")

Cleaning your cache

Note that calling functions like getCorum or getBioPlex with argument cache = FALSE will automatically overwrite the corresponding object in your cache. It is thus typically not required for a user to interact with the cache.

For more extended control of the cache, use from within R:

cache.dir <- tools::R_user_dir("BioPlex", which = "cache") 
bfc <- BiocFileCache::BiocFileCache(cache.dir)

and then proceed as described in the BiocFileCache vignette, Section 1.10

either via cleanbfc() to clean or removebfc() to remove your cache.

To do a hard reset (use with caution!):

BiocFileCache::removebfc(bfc)


ccb-hms/BioPlex documentation built on Aug. 5, 2023, 9:15 p.m.