Inferring the Location and Effect of Tumor Suppressor Genes by Instability‐Selection Modeling of Allelic‐Loss Data

Summary. Cancerous tumor growth creates cells with abnormal DNA. Allelic‐loss experiments identify genomic deletions in cancer cells, but sources of variation and intrinsic dependencies complicate inference about the location and effect of suppressor genes; such genes are the target of these experiments and are thought to be involved in tumor development. We investigate properties of an instability‐selection model of allelic‐loss data, including likelihood‐based parameter estimation and hypothesis testing. By considering a special complete‐data case, we derive an approximate calibration method for hypothesis tests of sporadic deletion. Parametric bootstrap and Bayesian computations are also developed. Data from three allelic‐loss studies are reanalyzed to illustrate the methods.