RPPA SPACE

RPPA SPACE normalizes and quantifies Reverse-Phase Protein Array (RPPA) data in R to produce analysis-ready protein concentration estimates and slide-level quality-control metrics.

Key Features:

• Enhanced normalization and quantitation: Refines RPPA normalization to generate quantitative protein concentration estimates from raw array data.
• Slide-level 'noise' metric: Implements a novel 'noise' metric that estimates random error on each RPPA slide for quality assessment.
• Poor-quality sample exclusion: Supports identification and exclusion of poor-quality samples to improve dataset reliability.
• Parameter flexibility and performance: Reduces required input parameters, offers flexible parameterization, and provides faster processing with enhanced error reporting.

Scientific Applications:

• Proteomics quantitation: Produces normalized protein expression data suitable for downstream proteomic analyses.
• Cancer research: Enables comparative analysis of protein expression patterns across tumor and control samples.
• Drug development: Supports evaluation of protein-level responses to therapeutics across large sample cohorts.
• Molecular biology: Facilitates measurement of pathway- and protein-specific changes in experimental studies.

Methodology:

Builds upon the SuperCurve method, implements a slide-level 'noise' quality metric, enables exclusion of poor-quality samples, and streamlines normalization and quantitation of RPPA data.