An insight into high-resolution mass-spectrometry data

Research output: Contribution to journalArticle

24 Scopus citations

Abstract

Mass spectrometry is a powerful tool with much promise in global proteomic studies. The discipline of statistics offers robust methodologies to extract and interpret high-dimensional mass-spectrometry data and will be a valuable contributor to the field. Here, we describe the process by which data are produced, characteristics of the data, and the analytical preprocessing steps that are taken in order to interpret the data and use it in downstream statistical analyses. Because of the complexity of data acquisition, statistical methods developed for gene expression microarray data are not directly applicable to proteomic data. Areas in need of statistical research for proteomic data include alignment, experimental design, abundance normalization, and statistical analysis.

Original languageEnglish (US)
Pages (from-to)481-500
Number of pages20
JournalBiostatistics
Volume10
Issue number3
DOIs
StatePublished - Jul 2009

Keywords

  • Experimental design
  • Fourier transform
  • Mass calibration
  • Mass spectrometry
  • Normalization

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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