Symbolic discriminant analysis of microarray data in autoimmune disease

Jason H. Moore, Joel S. Parker, Nancy Olsen, Thomas M. Aune

Research output: Contribution to journalArticle

56 Citations (Scopus)

Abstract

New laboratory technologies such as DNA microarrays have made it possible to measure the expression levels of thousands of genes simultaneously in a particular cell or tissue. The challenge for genetic epidemiologists will be to develop statistical and computational methods that are able to identify subsets of gene expression variables that classify and predict clinical endpoints. Linear discriminant analysis is a popular multivariate statistical approach for classification of observations into groups. This is because the theory is well described and the method is easy to implement and interpret. However, an important limitation is that linear discriminant functions need to be prespecified. To address this limitation and the limitation of linearity, we have developed symbolic discriminant analysis (SDA) for the automatic selection of gene expression variables and discriminant functions that can take any form. In the present study, we demonstrate that SDA is capable of identifying combinations of gene expression variables that are able to classify and predict autoimmune diseases.

Original languageEnglish (US)
Pages (from-to)57-69
Number of pages13
JournalGenetic Epidemiology
Volume23
Issue number1
DOIs
StatePublished - Jul 18 2002

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Discriminant Analysis
Autoimmune Diseases
Gene Expression
Oligonucleotide Array Sequence Analysis
Technology
Genes

All Science Journal Classification (ASJC) codes

  • Epidemiology
  • Genetics(clinical)

Cite this

Moore, Jason H. ; Parker, Joel S. ; Olsen, Nancy ; Aune, Thomas M. / Symbolic discriminant analysis of microarray data in autoimmune disease. In: Genetic Epidemiology. 2002 ; Vol. 23, No. 1. pp. 57-69.
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Symbolic discriminant analysis of microarray data in autoimmune disease. / Moore, Jason H.; Parker, Joel S.; Olsen, Nancy; Aune, Thomas M.

In: Genetic Epidemiology, Vol. 23, No. 1, 18.07.2002, p. 57-69.

Research output: Contribution to journalArticle

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