Fast Open Modification Spectral Library Searching through Approximate Nearest Neighbor Indexing

Abstract

<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 library searching. 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 the Apache 2.0 license at <a data-untrusted="" href="https://github.com/bittremieux/ANN-SoLo" id="d531044e165" target="xrefwindow">https://github.com/bittremieux/ANN-SoLo</a>. </p>