The paper, entitled 'SQID: An intensity-incorporated protein identification algorithm for tandem mass spectrometry', can be read online in the Journal of Proteome Research by following this link: http://pubs.acs.org/doi/abs/10.1021/pr100959y
To interpret LC-MS/MS data in proteomics, most popular protein identification algorithms primarily use predicted fragment m/z values to assign peptide sequences to fragmentation spectra. The intensity information is often undervalued, since it is not as easy to predict and incorporate into algorithms. Nevertheless, the use of intensity to assist peptide identification is an attractive prospect and can potentially improve the confidence of matches and generate more identifications. Based on our previously reported study of fragmentation intensity patterns, we developed a protein identification algorithm, SeQuence IDentfication (SQID), which makes use of the coarse intensity from a statistical analysis. The scoring scheme was validated by comparing with Sequest and X!Tandem using three datasets, and the results indicate an improvement in the number of identified peptides, including unique peptides that are not identified by Sequest or X!Tandem. The software and source code are available under the GNU GPL license at: http://quiz2.chem.arizona.edu/wysocki/bioinformatics.htm.