Dimension Reduction for the Integrative Analysis of Multilevel Omics Data

Thallinger, G. (Speaker), Bettina Pucher (Contributor), Oana Alina Zeleznik (Contributor)

Activity: Talk or presentationTalk at conference or symposiumScience to science

Description

Biological systems are increasingly studied at multiple omics levels simultaneously. Sequential analysis of the individual omics levels does not take the interconnected nature of the data into account. Integrative analysis of the multilevel data using dimension reduction techniques facilitate the identification of a larger number and more relevant features than sequential methods. We apply principal component-,
correspondence- and multiple co-inertia analysis to transcriptome and proteome data from 57 cancer cell lines and show that MCIA allows identification of a more complete set of relevant features and more accurate classification of the cancer types.
Period5 May 2018
Held atSIAM Conference on Applied Linear Algebra
Event typeConference
LocationHong Kong, Hong Kong
Degree of RecognitionInternational

Keywords

  • Human- & Biotechnology
  • Information, Communication & Computing
  • Basic - Fundamental (Grundlagenforschung)