Package: PECA 1.43.0

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_1.43.0.tar.gz
PECA_1.43.0.zip(r-4.5)PECA_1.43.0.zip(r-4.4)PECA_1.43.0.zip(r-4.3)
PECA_1.43.0.tgz(r-4.4-any)PECA_1.43.0.tgz(r-4.3-any)
PECA_1.43.0.tar.gz(r-4.5-noble)PECA_1.43.0.tar.gz(r-4.4-noble)
PECA_1.43.0.tgz(r-4.4-emscripten)PECA_1.43.0.tgz(r-4.3-emscripten)
PECA.pdf |PECA.html✨
PECA/json (API)
NEWS

# Install 'PECA' in R:

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

On BioConductor:PECA-1.43.0(bioc 3.21)PECA-1.42.0(bioc 3.20)

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

4.34 score 11 scripts 250 downloads 17 mentions 5 exports 79 dependencies

Last updated 2 months agofrom:a4a29d4311. Checks:OK: 1 NOTE: 6. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Dec 03 2024
R-4.5-win	NOTE	Dec 03 2024
R-4.5-linux	NOTE	Dec 03 2024
R-4.4-win	NOTE	Dec 03 2024
R-4.4-mac	NOTE	Dec 03 2024
R-4.3-win	NOTE	Dec 03 2024
R-4.3-mac	NOTE	Dec 03 2024