A Dynamic Noise Level Algorithm for Spectral Screening of Peptide MS/MS Spectra

Background: High-throughput shotgun proteomics data contain a significant number of spectra from non-peptide ions or spectra of too poor quality to obtain highly confident peptide identifications. These spectra cannot be identified with any positive peptide matches in some database search programs or are identified with false positives in others. Removing these spectra can improve the database search results and lower computational expense. Results: A new algorithm has been developed to filter tandem mass spectra of poor quality from shotgun proteomic experiments. The algorithm determines the noise level dynamically and independently for each spectrum in a tandem mass spectrometric data set. Spectra are filtered based on a minimum number of required signal peaks with a signal-to-noise ratio of 2. The algorithm was tested with 23 sample data sets containing 62,117 total spectra. Conclusions: The spectral screening removed 89.0% of the tandem mass spectra that did not yield a peptide ma...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Hua Xu, Michael A. Freitas
• Keywords: BMCBI 2010, Database Search, Tandem Mass, Tandem Mass Spectra