PMA

PMA processes and normalizes protein microarray data to correct systematic bias and noise for high-throughput protein interaction measurements.

Key Features:

• Neighbourhood background correction: Corrects local background noise surrounding array spots.
• Net intensity correction: Calculates signal intensity after background subtraction.
• User-defined noise threshold: Allows users to set custom thresholds for noise filtering.
• User-defined CV threshold amongst replicates: Enables coefficient of variation filtering across replicate spots.
• Assay controls: Incorporates control elements for quality assessment.
• Composite 'pin-to-pin' normalization amongst sub-arrays: Normalizes signal intensities across sub-arrays printed by different pins.
• 'Array-to-array' normalization amongst whole arrays: Normalizes signal intensities across entire arrays.

Scientific Applications:

• Cancer biomarker discovery: Supports high-throughput measurement of protein interactions and associated functions to identify potential cancer biomarkers.
• Protein interaction analysis: Enables robust data processing for protein microarray experiments measuring protein interactions.
• Cross-study data consolidation: Provides consistent analysis methods to facilitate collaborative data comparison across research groups.

Methodology:

The pipeline implements neighbourhood background correction, net intensity correction, user-defined noise and CV thresholds, assay controls, composite pin-to-pin normalization amongst sub-arrays, and array-to-array normalization amongst whole arrays.