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Tandem mass spectrometry has become a remarkably powerful technology to identify proteins in proteomics. Bioinformatics tools, especially database searching tools, are essential for the interpretation of large quantities of proteomics data. Despite recent improvements in database searching algorithms, only a relatively small fraction of spectra can be confidently assigned to peptide sequences in a typical proteomics analysis. The remaining unassigned spectra often consist of low quality spectra that cause a significant amount of computational overhead but that contribute little to protein identification. On the other hand, many high quality spectra remain unassigned due to modifications, mutations, and the deficiencies of the scoring methods implemented in database searching tools. Here we present ScanRanker, an open-source algorithm that offers a robust method for spectral quality assessment. Unlike existing tools that require training software for each type of instrument to be employed, ScanRanker evaluates quality of tandem mass spectra via sequence tagging, providing reliable performance in data sets from different instruments. The superior performance of ScanRanker enables it not only to filter low quality spectra prior to database searching, but also to find unassigned high quality spectra that evade identification through database search.