A Comprehensive Evaluation of Consensus Spectrum Generation Methods in Proteomics.

ABSTRACT: Spectrum clustering is a powerful strategy to minimize redundant mass spectra by grouping them based on similarity, with the aim of forming groups of mass spectra from the same repeatedly measured analytes. Each such group of near-identical spectra can be represented by its so-called consensus spectrum for downstream processing. Although several algorithms for spectrum clustering have been adequately benchmarked and tested, the influence of the consensus spectrum generation step is rarely evaluated. Here, we present an implementation and benchmark of common consensus spectrum algorithms, including spectrum averaging, spectrum binning, the most similar spectrum, and the best-identified spectrum. We have analyzed diverse public data sets using two different clustering algorithms (spectra-clu

SUBMITTER: Luo X 

PROVIDER: S-EPMC9171829 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature