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The effect of peptide identification search algorithms on MS2-based label-free protein quantification
Sven Degroeve1, An Staes, Pieter-Jan De Bock
1Department of Medical Protein Research, VIB, and Ghent University, Faculty of Medicine and Health Sciences, Ghent, Belgium.
Omics : a Journal of Integrative Biology
|July 19, 2012
Summary
Different search algorithms impact protein quantification in label-free mass spectrometry (MS2). Using multiple search engines is recommended to mitigate search engine bias in protein abundance results.
Area of Science:
- Proteomics
- Analytical Chemistry
- Biochemistry
Background:
- Label-free MS2-based quantification estimates protein abundance using fragmentation spectra.
- Peptide identification by search algorithms is a critical first step in this quantification process.
Purpose of the Study:
- To investigate the impact of different search algorithms on protein quantification reproducibility.
- To determine if variations in peptide identification affect label-free MS2-based protein quantification.
Main Methods:
- Evaluated the effect of using distinct search algorithms on protein quantification.
- Examined the reproducibility of protein quantification in technical repeat measurements of the same sample.
Main Results:
- A significant search engine effect was observed in MS2-based label-free protein quantification.
- Differences in peptide identification by various search algorithms influence protein abundance estimations.
Conclusions:
- Search engine choice can introduce bias into label-free MS2-based protein quantification.
- Performing analysis with multiple distinct search engines is recommended to address potential bias.
