American Statistical Association
Data normalization is an important step in the analysis of microarray data, as systematic but non-biological variation often arise from the complicated process of a microarray experiment. Existing methods for data normalization often assume that there are few and/or symmetric differential expressions, but this assumption does not always hold. In this talk, I will give a brief review of current methods for data normalization and present a new method for normalizing heterogeneous samples.
|Date:||Wednesday, February 14, 2007|
|Time:||4:00 P.M. - 5:00 P.M.|
Memorial Sloan-Kettering Cancer Center
Department of Epidemiology and Biostatistics
307 East 63rd Street
(between First and Second Avenues)
3rd Floor Conference Room
New York, New York
Note: To gain access to the building, please follow the directions by the telephone in the foyer.