Bioconductor version: Release (3.16)
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")
):
To install this package, start R (version "4.2") 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.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("PECA")
R Script | PECA: Probe-level Expression Change Averaging | |
Reference Manual | ||
Text | NEWS |
biocViews | DifferentialExpression, DifferentialSplicing, ExonArray, GeneExpression, Microarray, Proteomics, Software |
Version | 1.34.0 |
In Bioconductor since | BioC 2.14 (R-3.1) (9 years) |
License | GPL (>= 2) |
Depends | R (>= 3.3) |
Imports | ROTS, limma, affy, genefilter, preprocessCore, aroma.affymetrix, aroma.core |
LinkingTo | |
Suggests | SpikeIn |
SystemRequirements | |
Enhances | |
URL | |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | PECA_1.34.0.tar.gz |
Windows Binary | PECA_1.34.0.zip |
macOS Binary (x86_64) | PECA_1.34.0.tgz |
macOS Binary (arm64) | PECA_1.34.0.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 |
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