title: PeakLink: a new peptide peak linking method in LC-MS/MS using wavelet and SVM.
abstract: BACKGROUND
  In liquid chromatography-mass spectrometry/tandem mass spectrometry (LC-MS/MS), it is necessary to link tandem MS-identified peptide peaks so that protein expression changes between the two runs can be tracked. However, only a small number of peptides can be identified and linked by tandem MS in two runs, and it becomes necessary to link peptide peaks with tandem identification in one run to their corresponding ones in another run without identification. In the past, peptide peaks are linked based on similarities in retention time (rt), mass or peak shape after rt alignment, which corrects mean rt shifts between runs. However, the accuracy in linking is still limited especially for complex samples collected from different conditions. Consequently, large-scale proteomics studies that require comparison of protein expression profiles of hundreds of patients can not be carried out effectively.
  
  
  METHODS
  In this article, we consider the problem of linking peptides from a pair of LC-MS/MS runs and propose a new method, PeakLink (PL), which uses information in both the time and frequency domain as inputs to a non-linear support vector machine (SVM) classifier. The PL algorithm first uses a threshold on an rt likelihood ratio score to remove candidate corresponding peaks with excessively large elution time shifts, then PL calculates the correlation between a pair of candidate peaks after reducing noise through wavelet transformation. After converting rt and peak shape correlation to statistical scores, an SVM classifier is trained and applied for differentiating corresponding and non-corresponding peptide peaks.
  
  
  RESULTS
  PL is tested in multiple challenging cases, in which LC-MS/MS samples are collected from different disease states, different instruments and different laboratories. Testing results show significant improvement in linking accuracy compared with other algorithms.
  
  
  METHODS
  M files for the PL alignment method are available at http://compgenomics.utsa.edu/zgroup/PeakLink.
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Department of Electrical and Computer Engineering, The University of Texas at San Antonio, San Antonio, TX 78246, USA.
authors.forename: Mehrab
authors.initials: M
authors.lastname: Ghanat Bari
authors.affiliation: Department of Electrical and Computer Engineering, The University of Texas at San Antonio, San Antonio, TX 78246, USA.
authors.forename: Xuepo
authors.initials: X
authors.lastname: Ma
authors.affiliation: Department of Electrical and Computer Engineering, The University of Texas at San Antonio, San Antonio, TX 78246, USA.
authors.forename: Jianqiu
authors.initials: J
authors.lastname: Zhang
mesh_terms: D000465:Algorithms; D002853:Chromatography, Liquid / Q000379:methods*; D006801:Humans; D010455:Peptides / Q000737:chemistry*; D040901:Proteomics / Q000379:methods; D060388:Support Vector Machine; D053719:Tandem Mass Spectrometry / Q000379:methods*; D058067:Wavelet Analysis
chemical_list: D010455:Peptides