PECA

PECA (Probe-level Expression Change Averaging) is a software tool for detecting differential gene expression and splicing using data from microarray experiments that quantify gene expression levels in high throughput.

The PECA method averages expression changes at the individual probe level to robustly identify significant differences between conditions. By operating on the probe level, it can detect both gene-level expression changes and alternative splicing events.

The PECA package is cross-platform compatible and can be used on various operating systems. It provides a statistically principled approach for analyzing microarray datasets to characterize transcriptomic variations with high sensitivity and specificity.

Topic

Microarray experiment;Proteomics;Gene expression;Proteomics experiment

Detail

  • Operation: Differential gene expression analysis;Differential protein expression analysis

  • Software interface: Command-line user interface,Library

  • Language: R

  • License: GNU General Public License, version 2

  • Cost: Free

  • Version name: 1.40.0

  • Credit: -

  • Input: Raw microarray data [cel] [affymetrix] [dat] [TSV]

  • Output: P-value [TSV] [HTML] [Matrix format], Processed microarray data [TSV] [HTML] [Matrix format]

  • Contact: Tomi Suomi tomi.suomi@utu.fi

  • Collection: -

  • Maturity: Stable

Publications

  • Accurate Detection of Differential Expression and Splicing Using Low-Level Features.
  • Suomi T, Elo LL. Accurate Detection of Differential Expression and Splicing Using Low-Level Features. Methods Mol Biol. 2017;1507:141-151. doi: 10.1007/978-1-4939-6518-2_11. PMID: 27832538.
  • https://doi.org/10.1007/978-1-4939-6518-2_11
  • PMID: 27832538
  • PMC: -

Download and documentation

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