Package: PECA 1.49.0

Tomi Suomi

PECA: Probe-level Expression Change Averaging

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.

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

PECA_1.49.0.tar.gz
PECA_1.49.0.zip(r-4.7)PECA_1.49.0.zip(r-4.6)PECA_1.49.0.zip(r-4.5)
PECA_1.49.0.tgz(r-4.6-any)PECA_1.49.0.tgz(r-4.5-any)
PECA_1.49.0.tar.gz(r-4.7-any)PECA_1.49.0.tar.gz(r-4.6-any)
PECA_1.49.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
PECA/json (API)

# Install 'PECA' in R:

install.packages('PECA', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

On BioConductor:PECA-1.49.0(bioc 3.24)PECA-1.48.0(bioc 3.23)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

software proteomics microarray differentialexpression geneexpression exonarray differentialsplicing

4.30 score 10 scripts 17 mentions 5 exports 91 dependencies

Last updated from:f9e612ca97. Checks:1 ERROR, 7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
bioc-checks	ERROR	216
linux-devel-x86_64	NOTE	317
source / vignettes	OK	308
linux-release-x86_64	NOTE	338
macos-release-arm64	NOTE	134
macos-oldrel-arm64	NOTE	228
windows-devel	NOTE	211
windows-release	NOTE	165
windows-oldrel	NOTE	193
wasm-release	OK	209