Improved Performance Evaluation of DNA Copy Number Analysis Methods in Cancer Studies

• Activity Number: 574
• Type: Invited
• Date/Time: Wednesday, August 7, 2013 : 2:00 PM to 3:50 PM
• Sponsor: WNAR
• Author(s): Pierre Neuvial*+
• Companies: CNRS
• Keywords: copy number ; SNP microarrays ; cancer studies ; evaluation ; segmentation ; breakpoints

Abstract

Changes in DNA copy numbers are a hallmark of cancer cells. Therefore, the accurate detection and interpretation of such changes are two important steps toward improved diagnosis and treatment. The analysis of copy number profiles measured from high-throughput technologies such as SNP microarray and DNAseq data raises a number of statistical and bioinformatic challenges. Evaluating existing analysis methods is particularly challenging in the absence of gold standard data sets.

We have designed and implemented a framework to generate realistic DNA copy number profiles of cancer samples with known parent-specific copy-number state. This talk illustrates some of the benefits of this approach in a practical use case: a comparison study between methods for identifying parent-specific copy number states using SNP microarrays. This study helps identifying the pros and cons of the compared methods in terms of biologically informative parameters, such as the signal length, the number of breakpoints, the fraction of tumor cells in the sample, or the chip type.

The methods discussed are implemented in the open-source R packages aroma.cn, aroma.cn.eval and jointSeg.