Fast Open Modification Spectral Library Searching through Approximate Nearest Neighbor Indexing

Abstract

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. 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 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 with SpectraST. 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 .

Extremely fast and accurate open modification spectral library searching of high-resolution mass spectra using feature hashing and graphics processing units

“…Second, because the sensitivity of multidimensional indexing techniques decreases as the dimensionality increases, due to the curse of dimensionality [18], shorter vectors are preferred. Previously, we empirically found that mass bins of 1 Da represented a good trade-off between fragment mass resolution and vector dimensionality [8].…”

“…To build an ANN index to efficiently select candidates from the spectral library, spectra are vec-torized to represent them as points in a multidimensional space. In previous work [8], we converted spectra to sparse vectors by dividing the mass range into equally spaced bins and assigning each peak's intensity to the corresponding bin. When choosing the mass bin width two conflicting factors must be considered.…”

“…As a result, historically OMS has only been used to a limited extent and with severely restricted protein databases. Based on computational and algorithmic advances, however, recently several modern open search engines have been developed that can efficiently handle this large search space [6][7][8][9][10][11]. These tools make it possible to perform OMS on a proteome-wide scale, allowing researchers to gain a deeper understanding of the protein modification landscape.…”

“…Here we present an update to our Approximate Nearest Neighbor Spectral Library (ANN-SoLo) tool for efficient open modification spectral library searching [8]. As described previously, ANN-SoLo uses approximate nearest neighbor (ANN) indexing to speed up OMS by selecting only a limited number of the most relevant library spectra to compare to an unknown query spectrum.…”

Proteomics Standards Initiative Extended FASTA Format (PEFF)

“…In both cases, if the exact combination of peptide sequence, amino acid modifications, and charge state is not present in the search space, then the spectrum cannot be correctly identified. Several groups have demonstrated the ability to open the search space to consider unpredicted modifications [5][6][7][8][9] , but these strategies generally lead to an overall decrease in identifications at a given FDR threshold, so are not widely adopted in bottom-up proteomics.…”