A method for analyzing censored survival phenotype with gene expression data

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. Method: We propose a method for an integrated study of survival time and gene expression. This method can be summarized as a two-step procedure: in the first step, a moderate number of genes are pre-selected using correlation or liquid association (LA). Imputation and transformation methods are employed for the correlation/LA calculation. In the second step, the dimension of the predictors is further reduced using the modified sliced inverse regression for censored data (censorSIR). Results: The new method is tested via both simulated and real data. For the real dat...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Tongtong Wu, Wei Sun, Shinsheng Yuan, Chun-Houh Chen, Ker-Chau Li
• Keywords: BMCBI 2008, Gene Expression, Gene Expression Profiles, Survival Times