SecretSanta

SecretSanta predicts extracellular proteins secreted via classical pathways by identifying N-terminal signal peptides and integrating multiple prediction tools for secretome analysis.

Key Features:

• Integration of Established Tools: Wraps and parses command-line tools with wrapper and parser functions to produce integrative predictions of extracellular proteins secreted via classical pathways.
• Classical Secretory Pathway Prediction: Detects N-terminal signal peptides to identify proteins routed through the classical secretory pathway.
• Modularity and Flexibility: Modular design enables construction of customized pipelines and comparative analyses across species or experimental conditions.
• Scalability and Efficiency: Implemented in the R programming language with parallelized functions optimized for large-scale sequence processing.

Scientific Applications:

• Biomarker Discovery: Predicts extracellular proteins based on N-terminal signal peptides to identify candidate biomarkers for disease classification.
• Host-Pathogen Interaction Studies: Analyzes secretomes to support investigation of molecular interactions between hosts and pathogens and related immune responses.
• Comparative Secretome Analysis: Enables comparison of secretomes across species or environmental conditions to study evolutionary processes and functional adaptations.

Methodology:

Integrates command-line prediction tools via wrapper and parser functions; implemented in R with parallelized functions; predicts secreted proteins by detecting N-terminal signal peptides indicative of the classical secretory pathway.