Building consensus spectral libraries for peptide identification in proteomics

Abstract
Spectral searching, based on matching experimental peptide spectra to reference spectral libraries, is gaining interest as an alternative to traditional sequence-database searching in mass spectrometry–based proteomics. A software tool, SpectraST, now allows users to build their own high-quality spectral libraries from raw data. Spectral searching has drawn increasing interest as an alternative to sequence-database searching in proteomics. We developed and validated an open-source software toolkit, SpectraST, to enable proteomics researchers to build spectral libraries and to integrate this promising approach in their data-analysis pipeline. It allows individual researchers to condense raw data into spectral libraries, summarizing information about observed proteomes into a concise and retrievable format for future data analyses.