Visualizing and comparing results of different peptide identification methods. (5th December 2016)

• Record Type: Journal Article
• Authors: Mohammed, Yassene; Palmblad, Magnus
• Is Part Of: Briefings in bioinformatics. Volume 19:Number 2(2018:Mar.)
• Page Start: 210
• Page End: 218
• Publication Date: 2016-12-05
• Subjects: data processing workflow -- data integration -- peptide–spectrum matching -- visualization; Genetics -- Data processing -- Periodicals; Molecular biology -- Data processing -- Periodicals; Genomes -- Data processing -- Periodicals; 572.80285
• DOI: 10.1093/bib/bbw115
• Languages: English
• ISSNs: 1467-5463

Abstract

Abstract: In mass spectrometry-based proteomics, peptides are typically identified from tandem mass spectra using spectrum comparison. A sequence search engine compares experimentally obtained spectra with those predicted from protein sequences, applying enzyme cleavage and fragmentation rules. To this, there are two main alternatives: spectral libraries and de novo sequencing. The former compares measured spectra with a collection of previously acquired and identified spectra in a library. De novo attempts to sequence peptides from the tandem mass spectra alone. We here present a theoretical framework and a data processing workflow for visualizing and comparing the results of these different types of algorithms. The method considers the three search strategies as different dimensions, identifies distinct agreement classes and visualizes the complementarity of the search strategies. We have included X! Tandem, SpectraST and PepNovo, as they are in common use and representative for algorithms of each type. Our method allows advanced investigation of how the three search methods perform relatively to each other and shows the impact of the currently used decoy sequences for evaluating the false discovery rates.