A Normalized Tree Index for identification of correlated clinical parameters in microarray data

Martin C, Tauchen A, Becker A, Nattkemper TW (2011)
BioData Mining 4(1): 2.

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Abstract / Bemerkung
BACKGROUND: Measurements on gene level are widely used to gain new insights in complex diseases e.g. cancer. A promising approach to understand basic biological mechanisms is to combine gene expression profiles and classical clinical parameters. However, the computation of a correlation coefficient between high-dimensional data and such parameters is not covered by traditional statistical methods. METHODS: We propose a novel index, the Normalized Tree Index (NTI), to compute a correlation coefficient between the clustering result of high-dimensional microarray data and nominal clinical parameters. The NTI detects correlations between hierarchically clustered microarray data and nominal clinical parameters (labels) and gives a measurement of significance in terms of an empiric p-value of the identified correlations. Therefore, the microarray data is clustered by hierarchical agglomerative clustering using standard settings. In a second step, the computed cluster tree is evaluated. For each label, a NTI is computed measuring the correlation between that label and the clustered microarray data. RESULTS: The NTI successfully identifies correlated clinical parameters at different levels of significance when applied on two real-world microarray breast cancer data sets. Some of the identified highly correlated labels confirm the actual state of knowledge whereas others help to identify new risk factors and provide a good basis to formulate new hypothesis. CONCLUSIONS: The NTI is a valuable tool in the domain of biomedical data analysis. It allows the identification of correlations between high-dimensional data and nominal labels, while at the same time a p-value measures the level of significance of the detected correlations.
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BioData Mining
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4
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1
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2
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Article Processing Charge funded by the Deutsche Forschungsgemeinschaft and the Open Access Publication Fund of Bielefeld University.
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Martin C, Tauchen A, Becker A, Nattkemper TW. A Normalized Tree Index for identification of correlated clinical parameters in microarray data. BioData Mining. 2011;4(1):2.
Martin, C., Tauchen, A., Becker, A., & Nattkemper, T. W. (2011). A Normalized Tree Index for identification of correlated clinical parameters in microarray data. BioData Mining, 4(1), 2. doi:10.1186/1756-0381-4-2
Martin, C., Tauchen, A., Becker, A., and Nattkemper, T. W. (2011). A Normalized Tree Index for identification of correlated clinical parameters in microarray data. BioData Mining 4, 2.
Martin, C., et al., 2011. A Normalized Tree Index for identification of correlated clinical parameters in microarray data. BioData Mining, 4(1), p 2.
C. Martin, et al., “A Normalized Tree Index for identification of correlated clinical parameters in microarray data”, BioData Mining, vol. 4, 2011, pp. 2.
Martin, C., Tauchen, A., Becker, A., Nattkemper, T.W.: A Normalized Tree Index for identification of correlated clinical parameters in microarray data. BioData Mining. 4, 2 (2011).
Martin, Christian, Tauchen, Annika, Becker, Anke, and Nattkemper, Tim Wilhelm. “A Normalized Tree Index for identification of correlated clinical parameters in microarray data”. BioData Mining 4.1 (2011): 2.
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2012-02-06T14:25:32Z

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