American Statistical Association
The integrity and stability of chromosomes enable the cell to transmit accurately its genetic information and function properly physiologically. When aberrations such as rearrangements, deletions and amplifications occur in chromosomes (genomic instability), diseases may arise. In this talk, I will focus on copy number data and the detection of the break points where the changes of copy number occur. To detect the break points, we propose a wavelet-based test statistic taking the maximum of two-scale wavelet coefficient products across scales. I will discuss the statistical inference of this test statistic and show some simulation and real data analysis results.
After breakpoints are identified, the data can be segmented into different states, for example, normal versus aberration state. For simplicity, we represent the segmented data by a series of binary variables. There is ample evidence to show that some of the aberrations co-occur in diseases. Thus, it seems important to find these co-occurrences, as it may help us understand the network in the disease process. If time permits, I will also present a recent work on the sparse regression-based approach for identifying the network using high dimensional binary data.
|Date:||Wednesday, April 28, 2010|
|Time:||4:00 - 5:00 P.M.|
Memorial Sloan-Kettering Cancer Center
Department of Epidemiology and Biostatistics
307 East 63rd Street
(between First and Second Avenues)
New York, New York
Note: To gain access to the building, please follow the directions by the telephone in the foyer.