Prof. Hongmei Jiang : Statistical issues in cancer-related copy number profiling

Posted by , part of the Statistics and Data Science Seminar.

At

April 21, 2010, 3 p.m.

In

SEO 636

Abstract

Copy number changes, either amplification or deletion of DNA materials, have been linked with cancer and other diseases. High-throughput DNA arrays enable simultaneous measurements of copy number on the genome-wide level. Given the intensity measurements from a single sample, methodologies and algorithms based on diverse techniques such as Hidden Markov Models, binary segmentation, and mixture models, have been developed to divide the genome into segments or regions of equal copy number. In this talk we will discuss how to find regions of recurrent gains or losses of DNA fragments across multiple cancer samples; how to identify chromosome regions which are associated with clinical variables such as relapse and survival outcome. The methods will be demonstrated on a liver cancer data set.