My colleagues and I are developing methods for matching peptide mass spectra to entries in a protein sequence database. Our goals are to derive easily-interpreted tests of statistical significance, investigate the utility of restricting the search database by species of origin, and provide open source code that can be further tested and improved by other investigators. Work to date had focused on development of an objective measure of spectral noisiness and its relationship to success in protein identification using exisiting commercial matching algorithms. We have found, surprisingly, that spectral noise is a rather minor factor, with limitations in the matching algorithms being more often responsible for identification failure. We have also developed a preliminary version of OMSSA, an Open Mass Spectrometry Serch Algorithm. Tests have shown that the search hueristics used in OMSSA are as fast as those in commercial algorithms, and furthermore that OMSSA's significance test statistics offer somewhat improved signal-to-noise properties.
| Xu, Ming; Geer, Lewis Y; Bryant, Stephen H et al. (2005) Assessing data quality of peptide mass spectra obtained by quadrupole ion trap mass spectrometry. J Proteome Res 4:300-5 |
| Geer, Lewis Y; Markey, Sanford P; Kowalak, Jeffrey A et al. (2004) Open mass spectrometry search algorithm. J Proteome Res 3:958-64 |
