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<p class="first" id="P1">Open modification searching (OMS) is a powerful search strategy
that identifies peptides
carrying any type of modification by allowing a modified spectrum to match against
its unmodified variant by using a very wide precursor mass window. A drawback of this
strategy, however, is that it leads to a large increase in search time. Although performing
an open search can be done using existing spectral library search engines by simply
setting a wide precursor mass window, none of these tools have been optimized for
OMS, leading to excessive runtimes and suboptimal identification results.
</p><p id="P2">Here we present the ANN-SoLo tool for fast and accurate open spectral
ANN-SoLo uses approximate nearest neighbor indexing to speed up OMS by selecting only
a limited number of the most relevant library spectra to compare to an unknown query
spectrum. This approach is combined with a cascade search strategy to maximize the
number of identified unmodified and modified spectra while strictly controlling the
false discovery rate, as well as a shifted dot product score to sensitively match
modified spectra to their unmodified counterparts.
</p><p id="P3">ANN-SoLo achieves state-of-the-art performance in terms of speed and
the number of
identifications. On a previously published human cell line data set, ANN-SoLo confidently
identifies more spectra than SpectraST or MSFragger and achieves a speedup of an order
of magnitude compared to SpectraST.
</p><p id="P4">ANN-SoLo is implemented in Python and C++. It is freely available under
2.0 license at
<a data-untrusted="" href="https://github.com/bittremieux/ANN-SoLo" id="d531044e165"