Large-scale tandem mass spectrum clustering using fast nearest neighbor searching

Abstract

Rationale: Advanced algorithmic solutions are necessary to process the ever increasing amounts of mass spectrometry data that is being generated. Here we describe the falcon spectrum clustering tool for efficient clustering of millions of MS/MS spectra. Methods: falcon succeeds in efficiently clustering large amounts of mass spectral data using advanced techniques for fast spectrum similarity searching. First, high-resolution spectra are binned and converted to low-dimensional vectors using feature hashing. Next, the spectrum vectors are used to construct nearest neighbor indexes for fast similarity searching. The nearest neighbor indexes are used to efficiently compute a sparse pairwise distance matrix without having to exhaustively compare all spectra to each other. Finally, density-based clustering is performed to group similar spectra into clusters. Results: Using a large draft human proteome dataset consisting of 25 million spectra, falcon is able to generate clusters of a similar quality as MS-Cluster and spectra-cluster, two widely used clustering tools, while being considerably faster. Notably, at comparable cluster quality levels, falcon generates larger clusters than alternative tools, leading to a larger reduction in data volume without the loss of relevant information for more efficient downstream processing. Conclusions: falcon is a highly efficient spectrum clustering tool. It is publicly available as open source under the permissive BSD license at https://github.com/bittremieux/falcon.

SIMSI-Transfer: Software-Assisted Reduction of Missing Values in Phosphoproteomic and Proteomic Isobaric Labeling Data Using Tandem Mass Spectrum Clustering

“…Compared with IMBR, spectral clustering is less sensitive to the issue of overlapping MS1 isotope patterns as the transfers of identifications are based on MS2 spectrum similarity rather than similar retention times and mass-to-charge ratios only. MaRaCluster (© Matthew The) ( 11 ) is one such spectrum clustering tool that showed competitive performance over others ( 16 , 17 ) and can also be used for TMT data. However, MaRaCluster has not yet been able to combine data from several TMT batches for the purpose of reducing missing quantification values.…”