Title

Joint Variable Selection And Classification With Immunohistochemical Data

Keywords

Antibody; L penalty 1; LASSO algorithm; Protein; Tissue microarray

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 estimation 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. © the authors, licensee Libertas Academica Ltd.

Publication Date

1-1-2009

Publication Title

Biomarker Insights

Volume

2009

Issue

4

Number of Pages

103-110

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.4137/bmi.s2465

Socpus ID

67651202721 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/67651202721

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