Cancer Informatics

Array-based comparative genomic hybridization (aCGH) allows measuring DNA copy number at the whole genome scale. In cancer studies, one may be interested in identifying DNA copy number aberrations (CNAs) associated with certain clinicopathological characteristics such as cancer metastasis. We proposed to define test regions based on copy number pattern profiles across multiple samples, using either smoothed log2-ratio or discrete data of copy number gain/loss calls. Association test performed on the refined test regions instead of the probes has improved power due to reduced number of tests. We also compared three types of measurement of copy number levels, normalized log2-ratio, smoothed log2-ratio, and copy number gain or loss calls in statistical hypothesis testing. The relative strengths and weaknesses of the proposed method were demonstrated using both simulation studies and real data analysis of a liver cancer study.