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Article
Phenotyping Genetic Diseases Using an Extension of µ-Scores for Multivariate Data
Statistical Applications in Genetics and Molecular Biology (2010)
  • José F. Morales, The Rockefeller University
  • Tingting Song, The Rockefeller University
  • Arleen D. Auerbach, The Rockefeller University
  • Knut M. Wittkowski, The Rockefeller University
Abstract

As the field of genomics matures, more complex genotypes and phenotypes are being studied. Fanconi anemia (FA), for example, is an inherited chromosome instability syndrome with a complex array of variable disease phenotypes including congenital malformations, hematological manifestations, and cancer. To better understand specific aspects of the genetic etiology of FA and other rare diseases with complex phenotypes, it is often necessary to reduce the dimensions of the disease phenotype information. Towards this end, we extend a novel non-parametric approach to include information about a hierarchical structure among disease phenotypes. The proposed extension increases information content of the phenotype scores obtained and, thereby, the power of genotype-phenotype relationships studies.

Keywords
  • multidimensional,
  • ranking,
  • Fanconi anemia,
  • censoring,
  • genotype,
  • phenotype,
  • non-parametric
Publication Date
March 5, 2010
Citation Information
José F. Morales, Tingting Song, Arleen D. Auerbach and Knut M. Wittkowski. "Phenotyping Genetic Diseases Using an Extension of µ-Scores for Multivariate Data" Statistical Applications in Genetics and Molecular Biology Vol. 7 Iss. 1 (2010)
Available at: http://works.bepress.com/knut_wittkowski/3/