Fast open modification spectral library searching through approximate nearest neighbor indexing
| Main Authors: | Bittremieux, Wout, Meysman, Pieter, Noble, William Stafford, Laukens, Kris |
|---|---|
| Format: | info Proceeding Journal |
| Terbitan: |
, 2018
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| Online Access: |
https://zenodo.org/record/1319036 |
Daftar Isi:
- Open modification search (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. 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. ANN-SoLo outperforms the state-of-the-art SpectraST spectral library search engine both in terms of speed and the number of identifications. On a previously published human cell line data set, ANN-SoLo confidently identifies 40% more spectra than SpectraST while achieving a speedup of an order of magnitude. ANN-SoLo is implemented in Python and C++. It is freely available under the Apache 2.0 license at https://github.com/bittremieux/ANN-SoLo.