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Comprehensive Workflow of Mass Spectrometry-based Shotgun Proteomics of Tissue Samples
Published on: November 13, 2021
Label-free quantitative shotgun proteomics using normalized spectral abundance factors.
Karlie A Neilson1, Tim Keighley, Dana Pascovici
1Macquarie University, North Ryde, NSW, Australia.
Methods in Molecular Biology (Clifton, N.J.)
|April 30, 2013
Summary
This chapter details a label-free quantitative shotgun proteomics workflow using the Scrappy program and spectral counting. It enables simultaneous protein quantification from complex samples, aiding biological data interpretation.
Area of Science:
- Proteomics
- Bioinformatics
- Computational Biology
Background:
- Quantitative proteomics is crucial for understanding biological systems.
- Label-free methods offer cost-effective protein quantification.
- Spectral counting is a common label-free quantification technique.
Purpose of the Study:
- To describe a laboratory workflow for label-free quantitative shotgun proteomics.
- To introduce the Scrappy program (R modules) for data analysis.
- To detail the process from peptide identification to protein quantification.
Main Methods:
- Utilizing the XTandem algorithm for peptide-to-spectrum matching.
- Employing spectral counting for protein quantification.
- Using normalized spectral abundance factors for relative protein abundance.
Main Results:
- A comprehensive workflow for quantitative shotgun proteomics is presented.
- The Scrappy program facilitates simultaneous quantification of thousands of proteins.
- Detailed output descriptions and graphical examples are provided.
Conclusions:
- The described workflow provides a robust method for label-free quantitative proteomics.
- The Scrappy program simplifies complex data analysis, enabling large-scale protein quantification.
- The chapter facilitates the extraction of meaningful biological insights from proteomics data.
