To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("pgca")

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pgca

DOI: 10.18129/B9.bioc.pgca    

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

Bioconductor version: Release (3.6)

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 and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("pgca")

Documentation

HTML R Script Introduction
PDF   Reference Manual

Details

biocViews AssayDomain, MassSpectrometry, Proteomics, Software, WorkflowStep
Version 1.2.0
In Bioconductor since BioC 3.5 (R-3.4) (0.5 years)
License GPL (>= 2)
Depends
Imports utils, stats
LinkingTo
Suggests knitr, testthat
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Source Package pgca_1.2.0.tar.gz
Windows Binary pgca_1.2.0.zip
Mac OS X 10.11 (El Capitan) pgca_1.2.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/pgca
Package Short Url http://bioconductor.org/packages/pgca/
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