Sage: An Open-Source Tool for Fast Proteomics Searching and Quantification at Scale.

Area of Science:

• Proteomics
• Bioinformatics
• Computational Biology

Background:

• Increasing complexity and volume of proteomics data require advanced software tools.
• Auditable and extensible software is crucial for reliable proteomics research.
• Open-source and permissively licensed tools best meet these requirements.

Purpose of the Study:

• To introduce Sage, a novel, high-performance proteomics pipeline.
• To provide an efficient, scalable, and cloud-ready solution for peptide identification and quantification.
• To offer an open-source and freely available alternative to existing proteomics software.

Main Methods:

• Development of a high-performance proteomics pipeline named Sage.
• Implementation of scalable and cloud-ready architecture.
• Focus on open-source and permissive licensing for auditability and extensibility.

Main Results:

• Sage demonstrates performance comparable to state-of-the-art proteomics tools.
• Sage operates an order of magnitude faster than existing software.
• The pipeline is designed for efficient peptide identification and quantification from mass spectra.

Conclusions:

• Sage offers a significant advancement in proteomics data analysis software.
• The open-source nature of Sage promotes auditability and extensibility.
• Sage provides a faster and scalable solution for handling complex proteomics datasets.