PECA

PECA implements probe-level expression change averaging to detect differential expression and alternative splicing from Affymetrix microarray data and is distributed as an R/Bioconductor package.

Key Features:

• Probe-Level Analysis: Operates at the probe level, aggregating probe signals to produce gene-level expression change estimates.
• Probe-Level Expression Change Averaging: Applies a probe-level averaging algorithm to mitigate probe-specific noise and variability in microarray measurements.
• Differential Expression Detection: Enhances sensitivity and specificity for detecting differential expression between experimental conditions using probe-level data.
• Splicing Event Identification: Supports detection of alternative splicing events using probe-level measurements.

Scientific Applications:

• Gene Expression Studies: Analyze large-scale Affymetrix microarray datasets to identify genes with significant expression changes, aiding biomarker or therapeutic target discovery.
• Splicing Analysis: Investigate alternative splicing events that may contribute to disease progression or response to treatment.

Methodology:

Averages probe-level expression changes to derive robust gene-level estimates and reduce noise and variability inherent in Affymetrix microarray data.