Processing of data generated by 2-dimensional gel electrophoresis for statistical analysis: Missing data, normalization, and statistics

Jinsook Chang, Holly Van Remmen, Walter F. Ward, Fred E. Regnier, Arlan Richardson, John Cornell

Research output: Contribution to journalArticlepeer-review

45 Scopus citations

Abstract

Several high-throughput statistical methods were evaluated for processing data generated by two-dimensional polyacrylamide gel electrophoresis, including how to handle missing data, normalization, and statistical analysis of data obtained from 2-D gels. Quantile normalization combined with a nonparametric permutation test based on minimizing false discover rates gave the highest yield of proteins that changed with genotype and detected the anticipated 50% decrease in Mn-superoxide dismutase (MnSOD) protein levels in mitochondrial extracts obtained from MnSOD-deficient mice.

Original languageEnglish (US)
Pages (from-to)1210-1218
Number of pages9
JournalJournal of Proteome Research
Volume3
Issue number6
DOIs
StatePublished - Nov 2004

Keywords

  • 2-D PAGE
  • False discovery rates
  • Missing data
  • Mitochondria
  • Normalization
  • Permutation test

ASJC Scopus subject areas

  • Biochemistry
  • Chemistry(all)

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