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|Title: ||Multiple hypothesis testing and clustering with mixtures of non-central t-distributions applied in microarray data analysis|
|Author(s): ||Marín, J. Miguel|
Rodríguez Bernal, M. T.
|Publisher: ||Universidad Carlos III de Madrid. Departamento de Estadística|
|Issued date: ||Nov-2010|
|Abstract: ||Multiple testing analysis, based on clustering methodologies, is usually applied in Microarray Data Analysis for comparisons between pair of groups. In this paper, we generalize this methodology to deal with multiple comparisons among more than two groups obtained from microarray expressions of genes. Assuming normal data, we define a statistic which depends on sample means and sample variances, distributed as a non-central t-distribution. As we consider multiple comparisons among groups, a mixture of non-central t-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.|
|Serie / Nº.: ||UC3M Working papers. Statistics and Econometrics|
Multiple hypothesis testing
|Appears in Collections:||DES - Working Papers. Statistics and Econometrics. WS|
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