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A method for analyzing censored survival phenotype with gene expression data
Authors:Tongtong Wu  Wei Sun  Shinsheng Yuan  Chun-Houh Chen  Ker-Chau Li
Institution:(1) Department of Epidemiology and Biostatistics, University of Maryland, College Park, MD 20742, USA;(2) Department of Biostatistics, Genetics, Carolina Center for Genome Science, University of North Carolina, Chapel Hill, NC 27599, USA;(3) Institute of Statistical Science,Academia Sinica, Taipei, 115, Taiwan;(4) Department of Statistics, University of California, Los Angeles, CA 90095-1554, USA
Abstract:

Background  

Survival time is an important clinical trait for many disease studies. Previous works have shown certain relationship between patients' gene expression profiles and survival time. However, due to the censoring effects of survival time and the high dimensionality of gene expression data, effective and unbiased selection of a gene expression signature to predict survival probabilities requires further study.
Keywords:
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