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Article
Joint variable selection and classification with immunohistochemical data
Technical report, Department of Statistics, Penn State University (2008)
  • Debashis Ghosh, Penn State University
  • Ratna Chakrabarti, University of Central Florida
Abstract

To determine if candidate cancer biomarkers have utility in a clinical setting, validation using immunohistochemical methods is typically done. Most analyses of such data have not incorporated the multivariate nature of the staining profiles. In this article, we consider modelling such data using recently developed ideas from the machine learning community. In particular, we consider the joint goals of feature selection and classification. We develop esti- mation procedures for the analysis of immunohistochemical profiles using the least absolute selection and shrinkage operator. These lead to novel and flexible models and algorithms for the analysis of compositional data. The techniques are illustrated using data from a cancer biomarker study.

Publication Date
2008
Citation Information
Debashis Ghosh and Ratna Chakrabarti. "Joint variable selection and classification with immunohistochemical data" Technical report, Department of Statistics, Penn State University (2008)
Available at: http://works.bepress.com/debashis_ghosh/30/