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pgca

PGCA: An Algorithm to Link Protein Groups Created from MS/MS Data


Bioconductor version: Release (3.18)

Protein Group Code Algorithm (PGCA) is a computationally inexpensive algorithm to merge protein summaries from multiple experimental quantitative proteomics data. The algorithm connects two or more groups with overlapping accession numbers. In some cases, pairwise groups are mutually exclusive but they may still be connected by another group (or set of groups) with overlapping accession numbers. Thus, groups created by PGCA from multiple experimental runs (i.e., global groups) are called "connected" groups. These identified global protein groups enable the analysis of quantitative data available for protein groups instead of unique protein identifiers.

Author: Gabriela Cohen-Freue <gcohen at stat.ubc.ca>

Maintainer: Gabriela Cohen-Freue <gcohen at stat.ubc.ca>

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

Installation

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


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

BiocManager::install("pgca")

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("pgca")
Introduction HTML R Script
Reference Manual PDF

Details

biocViews AssayDomain, ImmunoOncology, MassSpectrometry, Proteomics, Software, WorkflowStep
Version 1.26.0
In Bioconductor since BioC 3.5 (R-3.4) (7 years)
License GPL (>= 2)
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Imports utils, stats
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Suggests knitr, testthat, rmarkdown
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Package Archives

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

Source Package pgca_1.26.0.tar.gz
Windows Binary pgca_1.26.0.zip
macOS Binary (x86_64) pgca_1.26.0.tgz
macOS Binary (arm64) pgca_1.26.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/pgca
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/pgca
Bioc Package Browser https://code.bioconductor.org/browse/pgca/
Package Short Url https://bioconductor.org/packages/pgca/
Package Downloads Report Download Stats