Lung Cancer Genomic Data and Statistical Analysis

• Activity Number: 4
• Type: Invited
• Date/Time: Sunday, July 31, 2011 : 2:00 PM to 3:50 PM
• Sponsor: ENAR
• Author(s): Ker-Chau Li*+
• Companies: Academia Sinica
• Keywords: lung cancer ; gene expression ; bioinformatics ; next generation sequencing ; high dimension data analysis

Abstract

Lung cancer is the most common cause of cancer deaths worldwide. Lung cancer also shows the tendency of inheritance within the risk families. In lung adenocarcinoma, treatment of the EGFR tyrosine kinase inhibitors has been shown to be more effective for patients with EGFR activating mutations in their tumor cells. During the last few years, high throughput genomic data from many labs worldwide have accumulated rapidly, opening the great potential of discovering novel disease driving factors. However, the statistical analysis of various modes of molecular data including gene expression, DNA copy numbers, SNP, miroRNA expression, and the next generation sequencing data also poses many challenges. This talk will present some of our ongoing works, using both the public domain data and the data generated in collaboration with lung cancer biologists in Taiwan.