Reverse and Random Decoy Methods for False Discovery Rate Estimation in High Mass Accuracy Peptide Spectral Library Searches

Spectral library searching (SLS)
is an attractive alternative to
sequence database searching (SDS) for peptide identification due to
its speed, sensitivity, and ability to include any selected mass spectra.
While decoy methods for SLS have been developed for low mass accuracy
peptide spectral libraries, it is not clear that they are optimal
or directly applicable to high mass accuracy spectra. Therefore, we
report the development and validation of methods for high mass accuracy
decoy libraries. Two types of decoy libraries were found to be suitable
for this purpose. The first, referred to as Reverse, constructs spectra
by reversing a library’s peptide sequences except for the C-terminal
residue. The second, termed Random, randomly replaces all non-C-terminal
residues and either retains the original C-terminal residue or replaces
it based on the amino-acid frequency of the library’s C-terminus.
In both cases the m/z values of
fragment ions are shifted accordingly. Determination of FDR is performed
in a manner equivalent to SDS, concatenating a library with its decoy
prior to a search. The utility of Reverse and Random libraries for
target-decoy SLS in estimating false-positives and FDRs was demonstrated
using spectra derived from a recently published synthetic human proteome
project (Zolg, D. P.; et al. Nat. Methods 2017, 14, 259–262). For data sets from two large-scale
label-free and iTRAQ experiments, these decoy building methods yielded
highly similar score thresholds and spectral identifications at 1%
FDR. The results were also found to be equivalent to those of using
the decoy-free PeptideProphet algorithm. Using these new methods for
FDR estimation, MSPepSearch, which is freely available search software,
led to 18% more identifications at 1% FDR and 23% more at 0.1% FDR
when compared with other widely used SDS engines coupled to postprocessing
approaches such as Percolator. An application of these methods for
FDR estimation for the recently reported “hybrid” library
search (Burke, M. C.; et al. J. Proteome Res. 2017, 16, 1924–1935) method is also
made. The application of decoy methods for high mass accuracy SLS
permits the merging of these results with those of SDS, thereby increasing
the assignment of more peptides, leading to deeper proteome coverage.