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Increasing confidence in proteomic spectral deconvolution through mass defect

Milan Avila Clasen, Louise Ulrich Kurt, Marlon Dias Mariano Santos, Diogo Borges Lima, Fan Liu, Fábio C. Gozzo, Valmir C. Barbosa, Paulo C. Carvalho

2022Bioinformatics17 citationsDOIOpen Access PDF

Abstract

MOTIVATION: Confident deconvolution of proteomic spectra is critical for several applications such as de novo sequencing, cross-linking mass spectrometry and handling chimeric mass spectra. RESULTS: In general, all deconvolution algorithms may eventually report mass peaks that are not compatible with the chemical formula of any peptide. We show how to remove these artifacts by considering their mass defects. We introduce Y.A.D.A. 3.0, a fast deconvolution algorithm that can remove peaks with unacceptable mass defects. Our approach is effective for polypeptides with less than 10 kDa, and its essence can be easily incorporated into any deconvolution algorithm. AVAILABILITY AND IMPLEMENTATION: Y.A.D.A. 3.0 is freely available for academic use at http://patternlabforproteomics.org/yada3. SUPPLEMENTARY INFORMATION: Supplementary information is available at Bioinformatics online.

Topics & Concepts

DeconvolutionComputer scienceConfidence intervalComputational biologyArtificial intelligenceStatisticsAlgorithmMathematicsBiologyAdvanced Proteomics Techniques and ApplicationsMass Spectrometry Techniques and ApplicationsGenomics and Phylogenetic Studies
Increasing confidence in proteomic spectral deconvolution through mass defect | Litcius