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Multiple hypothesis testing and clustering with mixtures of non-central -distributions applied in microarray data analysis
- Source :
-
Computational Statistics & Data Analysis . Jun2012, Vol. 56 Issue 6, p1898-1907. 10p. - Publication Year :
- 2012
-
Abstract
- Abstract: Multiple testing analysis and clustering methodologies are usually applied in microarray data analysis. A combination of both methods to deal with multiple comparisons among groups obtained from microarray expressions of genes is proposed. Assuming normal data, a statistic which depends on sample means and sample variances, distributed as a non-central -distribution is defined. As multiple comparisons among groups are considered, a mixture of non-central -distributions is derived. The estimation of the components of mixtures is obtained via a Bayesian approach, and the model is applied in a multiple comparison problem from a microarray experiment obtained from gorilla, bonobo and human cultured fibroblasts. [Copyright &y& Elsevier]
Details
- Language :
- English
- ISSN :
- 01679473
- Volume :
- 56
- Issue :
- 6
- Database :
- Academic Search Index
- Journal :
- Computational Statistics & Data Analysis
- Publication Type :
- Periodical
- Accession number :
- 72687058
- Full Text :
- https://doi.org/10.1016/j.csda.2011.11.016