Comparison of False Discovery Rate Control Strategies for Variant Peptide Identifications in Shotgun Proteogenomics

Proteogenomic
studies aiming at identification of variant peptides
using customized database searches of mass spectrometry data are facing
a dilemma of selecting the most efficient database search strategy:
A choice has to be made between using combined or sequential searches
against reference (wild-type) and mutant protein databases or directly
against the mutant database without the wild-type one. Here we called
these approaches “all-together”, “one-by-one”,
and “direct”, respectively. We share the results of
the comparison of these search strategies obtained for large data
sets of publicly available proteogenomic data. On the basis of the
results of this evaluation, we found that the “all-together”
strategy provided, in general, more variant peptide identifications
compared with the “one-by-one” approach, while showing
similar performance for some specific cases. To validate further the
results of this study, we performed a control comparison of the strategies
in question using publicly available data for a mixture of the annotated
human protein standard UPS1 and E. coli. For these
data, both “all-together” and “one-by-one”
approaches showed similar sensitivity and specificity of the searches,
while the “direct” approach resulted in an increased
number of false identifications.