The Percolator Analysis Engine for Tandem Mass Spectrometry Data
William Noble (University of Washington)
To improve Percolator, the dominant software for analyzing spectrum identifications produced by protein tandem mass spectrometry, by making the software faster, more robust, and applicable to more types of mass spectrometry data.
Tandem mass spectrometry is the only technology currently capable of identifying and quantifying proteins in a complex biological sample in a high-throughput fashion. As such, this technology is a key driver behind the rapid growth of the field of proteomics. The Percolator algorithm, first described in 2007, has become one of the most widely used software tools in this field. The Percolator software takes as input database search results produced by any one of a variety of search tools and then applies a semi-supervised machine learning approach to rank the identified spectra based on the quality of the peptide-spectrum matches.