Table I

Tabulation of independent thresholds specific to each algorithm and associated number of correct and incorrect peptide identifications found for each calculated FPR

Results were calculated by first determining the expected number of incorrect peptide hits, i.e. those identified reverse sequences for each FPR. That is, at 0.1% FPR we calculated that there will be three reverse, i.e. incorrect, peptide identifications using the equation FPR = 2 × (FP/(TP + FP)) and solving for FP. The integer 2 is used to compensate for the doubling size of the database. All results were sorted by decreasing threshold, e.g. decreasing Xcorr values. The threshold value is then reported that correlates with the expected number of incorrect peptide identifications, e.g. Xcorr of 5.84 for the third false positive representing an FPR of 0.1%. Numbers of correct peptide identifications are those that are equal to or above the threshold cutoff for that FPR.

SEQUEST
Peptide FPRIncorrect (reverse) peptide sequencesΔCnCorrect (forward) peptide sequencesXcorrCorrect (forward) peptide sequences
%
0.1030.43665.84115
0.50170.26213715.13287
1330.22817094.75447
51670.14924833.941134
Mascot
Peptide FPRIncorrect (reverse) peptide sequencesIdentity scoreCorrect (forward) peptide sequencesIon scoreCorrect (forward) peptide sequences
%
0.10242.9109946.41324
0.50942199035.12360
11841.8223631.92761
59038.1354124.53541
X!Tandem
Peptide FPRIncorrect (reverse) peptide sequencesLog(e) scoreCorrect (forward) peptide sequences
%
0.1023.282167
0.50102.282919
1201.893285
5991.333901