ReSpect: Software for Identification of High and Low Abundance Ion Species in Chimeric Tandem Mass Spectra Academic Article Article uri icon

Overview

MeSH Major

  • Cell Transformation, Viral
  • Oncogenes
  • Receptors, Cell Surface

abstract

  • © 2015 American Society for Mass Spectrometry. Most shotgun proteomics data analysis workflows are based on the assumption that each fragment ion spectrum is explained by a single species of peptide ion isolated by the mass spectrometer; however, in reality mass spectrometers often isolate more than one peptide ion within the window of isolation that contribute to additional peptide fragment peaks in many spectra. We present a new tool called reSpect, implemented in the Trans-Proteomic Pipeline (TPP), which enables an iterative workflow whereby fragment ion peaks explained by a peptide ion identified in one round of sequence searching or spectral library search are attenuated based on the confidence of the identification, and then the altered spectrum is subjected to further rounds of searching. The reSpect tool is not implemented as a search engine, but rather as a post-search engine processing step where only fragment ion intensities are altered. This enables the application of any search engine combination in the iterations that follow. Thus, reSpect is compatible with all other protein sequence database search engines as well as peptide spectral library search engines that are supported by the TPP. We show that while some datasets are highly amenable to chimeric spectrum identification and lead to additional peptide identification boosts of over 30% with as many as four different peptide ions identified per spectrum, datasets with narrow precursor ion selection only benefit from such processing at the level of a few percent. We demonstrate a technique that facilitates the determination of the degree to which a dataset would benefit from chimeric spectrum analysis. The reSpect tool is free and open source, provided within the TPP and available at the TPP website.

publication date

  • November 2015

Research

keywords

  • Academic Article

Identity

Digital Object Identifier (DOI)

  • 10.1007/s13361-015-1252-5

PubMed ID

  • 26419769

Additional Document Info

start page

  • 1837

end page

  • 1847

volume

  • 26

number

  • 11