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pgca

This is the released version of pgca; for the devel version, see pgca.

All versions 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, 3.8, 3.7, 3.6, 3.5

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


Bioconductor version: Release (3.23)

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")):

Gabriela Cohen-Freue. pgca: PGCA: An Algorithm to Link Protein Groups Created from MS/MS Data. doi:10.18129/B9.bioc.pgca, R package version 1.36.0, https://bioconductor.org/packages/pgca.

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("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 ManualPDF

Details

biocViews AssayDomain, ImmunoOncology, MassSpectrometry, Proteomics, Software, WorkflowStep
Version1.36.0
In Bioconductor sinceBioC 3.5 (R-3.4) (9.5 years)
License GPL (>= 2)
Depends
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_1.36.0.tar.gz
Windows Binary (x86_64) pgca_1.36.0.zip
macOS Binary (big-sur-x86_64) pgca_1.36.0.tgz
macOS Binary (sonoma-arm64) pgca_1.36.0.tgz
Source Repositorygit clone https://git.bioconductor.org/packages/pgca
Source Repository (Developer Access)git clone git@git.bioconductor.org:packages/pgca
Package Short Url https://bioconductor.org/packages/pgca/
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