Defining an informativeness metric for clustering gene expression data

Mar, Jessica C., Wells, Christine A. and Quackenbush, John (2011) Defining an informativeness metric for clustering gene expression data. Bioinformatics, 27 8: 1094-1100. doi:10.1093/bioinformatics/btr074

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Author Mar, Jessica C.
Wells, Christine A.
Quackenbush, John
Title Defining an informativeness metric for clustering gene expression data
Journal name Bioinformatics   Check publisher's open access policy
ISSN 1367-4803
Publication date 2011-04
Sub-type Article (original research)
DOI 10.1093/bioinformatics/btr074
Volume 27
Issue 8
Start page 1094
End page 1100
Total pages 7
Place of publication Oxford, United Kingdom
Publisher Oxford University Press
Language eng
Formatted abstract
Motivation: Unsupervised ‘cluster’ analysis is an invaluable tool for exploratory microarray data analysis, as it organizes the data into groups of genes or samples in which the elements share common patterns. Once the data are clustered, finding the optimal number of informative subgroups within a dataset is a problem that, while important for understanding the underlying phenotypes, is one for which there is no robust, widely accepted solution.
Results: To address this problem we developed an ‘informativeness metric’ based on a simple analysis of variance statistic that identifies the number of clusters which best separate phenotypic groups. The performance of the informativeness metric has been tested on both experimental and simulated datasets, and we contrast these results with those obtained using alternative methods such as the gap statistic.
Keyword Data set
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Non HERDC
Australian Institute for Bioengineering and Nanotechnology Publications
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Citation counts: TR Web of Science Citation Count  Cited 26 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 28 times in Scopus Article | Citations
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Created: Sat, 10 Sep 2011, 01:49:08 EST by System User on behalf of Aust Institute for Bioengineering & Nanotechnology