ComplexBrowser

ComplexBrowser performs supervised analysis of quantitative proteomics data to identify protein complex components and quantify coordinated changes in complex abundance using curated resources such as CORUM and the EBI Complex Portal.

Key Features:

• Supervised quantitative proteomics analysis: Identifies protein complex components and assesses subunit co-expression within large-scale proteomic datasets.
• Complex Fold Change (CFC) factor: Computes the CFC metric to summarize coordinated expression trends across complex subunits.
• Database integration: Matches proteomic entries to curated complex annotations from CORUM and the EBI Complex Portal.
• Normalization and quality control: Applies normalization procedures and quality-control measures to proteomic data prior to analysis.
• Statistical testing (Limma): Performs differential analysis using the Limma test to evaluate significance of changes at the complex level.

Scientific Applications:

• Human adenocarcinoma tissue analysis: Identification of significantly regulated protein complexes in human adenocarcinoma samples.
• Mouse T-cell activation studies: Detection of coordinated complex regulation during mouse T-cell activation.
• Inference of biological processes: Elucidation of metabolic shifts and chromatin remodeling through coordinated complex-level changes.

Methodology:

Integrates quantitative proteomics data with CORUM and Complex Portal annotations, calculates the Complex Fold Change (CFC) factor to quantify coordinated subunit expression changes, applies normalization and quality-control procedures, and uses the Limma test for statistical evaluation within an R-based implementation.