Self-calibrated warping for mass spectra alignment.

Academic Article

Abstract

  • With recent advances in mass spectrometry (MS) technologies, it is now possible to study protein profiles over a wide range of molecular weights in small biological specimens. However, MS spectra are usually not aligned or synchronized between samples. To ensure the consistency of the subsequent analysis, spectrum alignment is necessary to align the spectra such that the same biological entity would show up at the same m/z value for different samples. Although a variety of alignment algorithms have been proposed in the past, most of them are developed based on chromatographic data and do not address some of the unique characteristics of the serum or other body fluid MS data. In this work, we propose a self-calibrated warping (SCW) algorithm to address some of the challenges associated with serum MS data alignment. In addition, we compare the proposed algorithm with five existing representative alignment methods using a clinical surface enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) data set.
  • Published In

  • Cancer Informatics  Journal
  • Keywords

  • alignment, data preprocessing, feature extraction, mass spectrometry, peak detection, proteomics, warping
  • Digital Object Identifier (doi)

    Author List

  • He QP; Wang J; Mobley JA; Richman J; Grizzle WE
  • Start Page

  • 65
  • End Page

  • 82
  • Volume

  • 10