POE: Statistical Methods for Qualitative Analysis of Gene Expression View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2003

AUTHORS

Elizabeth S. Garrett , Giovanni Parmigiani

ABSTRACT

In many gene expression studies, the goals include discovery of novel biological classes and identification of genes whose expression can reliably be associated with these classes. Here we present a statistical analysis approach to facilitate both of these goals. The key idea is to model gene expression using latent categories that can be interpreted as a gene being turned “on“ or “off“ compared to a baseline level of expression. This three-way categorization is used for defining a reference in the unsupervised setting, for removing noise prior to clustering, for defining molecular subclasses in a way that is portable across platforms, and for defining easily interpretable probability-based distance measures for visualization, mining, and clustering. More... »

PAGES

362-387

Book

TITLE

The Analysis of Gene Expression Data

ISBN

978-0-387-95577-3
978-0-387-21679-9

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/0-387-21679-0_16

DOI

http://dx.doi.org/10.1007/0-387-21679-0_16

DIMENSIONS

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