Abstract #300355

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JSM 2002 Abstract #300355
Activity Number: 394
Type: Invited
Date/Time: Thursday, August 15, 2002 : 10:30 AM to 12:20 PM
Sponsor: Section on Quality & Productivity*
Abstract - #300355
Title: Model Based Clustering and Outlier Detection in Microarray Data
Author(s): Johanna Hardin*+ and David Rocke
Affiliation(s): Fred Hutchinson Cancer Research Center and University of California, Davis
Address: 1100 Fairview Ave N, PO Box 19024, Seattle, Washington, 98109-1024,
Keywords: robust ; model-based clustering ; outlier detection
Abstract:

With microarray technologies becoming increasingly accessible to researchers, more and more complex questions are being asked about the structure of the data. The tools which identify genes that distinguish predefined groups are being refined, but we are still in need of good tools that can identify groups of genes or samples without supervision (or with only moderate supervision.) Though hierarchical techniques are unsupervised, they impose a structure on the data that may not be valid. We present an algorithm for applying a model-based clustering mechanism to microarray data that encompasses an outlier detection method. We propose unsupervised gene clusters and only moderately supervised sample clusters.

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