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PECA

Probe-level Expression Change Averaging

Bioconductor version: Release (3.17)

Calculates Probe-level Expression Change Averages (PECA) to identify differential expression in Affymetrix gene expression microarray studies or in proteomic studies using peptide-level mesurements respectively.

Author: Tomi Suomi, Jukka Hiissa, Laura L. Elo

Maintainer: Tomi Suomi <tomi.suomi at utu.fi>

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

Installation

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

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

BiocManager::install("PECA")

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("PECA")
PECA: Probe-level Expression Change Averaging PDF R Script
Reference Manual PDF
NEWS Text

Details

biocViews DifferentialExpression, DifferentialSplicing, ExonArray, GeneExpression, Microarray, Proteomics, Software
Version 1.36.0
In Bioconductor since BioC 2.14 (R-3.1) (9.5 years)
License GPL (>= 2)
Depends R (>= 3.3)
Imports ROTS, limma, affy, genefilter, preprocessCore, aroma.affymetrix, aroma.core
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Package Archives

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

Source Package PECA_1.36.0.tar.gz
Windows Binary PECA_1.36.0.zip (64-bit only)
macOS Binary (x86_64) PECA_1.36.0.tgz
macOS Binary (arm64) PECA_1.36.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/PECA
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/PECA
Bioc Package Browser https://code.bioconductor.org/browse/PECA/
Package Short Url https://bioconductor.org/packages/PECA/
Package Downloads Report Download Stats