Using a cross-model loadings plot to identify protein spots causing 2-DE gels to become outliers in PCA

Luise Cederkvist Kristiansen, Susanne Jacobsen, Flemming Jessen, Bo Jørgensen

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

The multivariate method PCA is an exploratory tool often used to get an overview of multivariate data, such as the quantified spot volumes of digitized 2-DE gels. PCA can reveal hidden structures present in the data, and thus enables identification of potential outliers and clustering. Based on PCA, we here present an approach for identification of protein spots causing 2-DE gels to become outliers. The approach can potentially obviate analytical exclusion of entire 2-DE gels.
Original languageEnglish
JournalProteomics
Volume10
Issue number8
Pages (from-to)1721-1723
ISSN1615-9853
DOIs
Publication statusPublished - 2010

Keywords

  • 2-DE
  • Gel quality
  • Gel defects
  • Technology
  • PCA

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