Omic-Sig

Omic-Sig analyzes kinase-substrate interactions and stratifies phospho-substrates and associated kinases by computing and ranking differential abundances between paired samples to profile protein phosphorylation using mass spectrometry-based phosphoproteomics and by integrating global proteomics and RNA-Seq transcriptome data.

Key Features:

• Kinase-substrate analysis: Detects and characterizes kinase-substrate interactions focused on protein phosphorylation.
• Paired-sample differential ranking: Computes and ranks differential abundances of phospho-sites and kinases between paired samples, such as tumor tissues and adjacent normal tissues.
• Phosphoproteomics support: Leverages mass spectrometry-based phosphoproteomics data to detect alterations in phosphorylation and kinase activity.
• Multi-omics integration: Integrates global proteomics and RNA-Seq transcriptome data for combined analysis with phosphoproteomics.
• Case–control differential analysis: Calculates differential abundances between case and control samples to identify significant changes in phosphorylation patterns.
• Data visualization: Produces visual representations to aid interpretation of complex multi-omics kinase-substrate relationships.

Scientific Applications:

• Cancer signaling analysis: Characterizes altered phosphorylation-driven signaling pathways in cancer cohorts.
• Disease mechanism investigation: Identifies dysregulated kinase-substrate relationships underlying disease processes.
• Biomarker and target discovery: Prioritizes phospho-sites and kinases as candidate biomarkers or therapeutic targets.
• Clinical cohort profiling: Applies paired-sample differential analyses to clinical research cohorts to reveal aberrant signaling events.

Methodology:

Computes and ranks differential abundances of phospho-sites and kinases between paired or case–control samples using mass spectrometry-based phosphoproteomics and integrates results with global proteomics and RNA-Seq transcriptome data.