Applying High-Dimensional Approaches to Microarray Research David Allison, Statistical Genetics, University of Alabama-Birmingham Although termed the post-genomic era, our age may be more accurately labeled the genomic era. Draft sequences of several genomes coupled with new technologies allow study of the influences and responses of entire genomes rather than isolated single genes. This opens a new realm of highly dimensional biology (HDB) where questions involve multiplicity at unprecedented scales. HDB can involve thousands of genetic polymorphisms, gene expression levels, protein measurements, genetic sequences, or any combination of these and their interactions. Such situations demand creative approaches to the processes of inference, estimation, prediction, classification, and study design. Although bench scientists intuitively grasp the need for flexibility in the inferential process, elaboration of formal statistical frameworks supporting this are just beginning. I will discuss some of the unique statistical challenges facing investigators studying high-dimensional biology, describe some approaches being developed by scientists at UAB and elsewhere and offer an epistemological framework for the validation of proffered statistical procedures. |
Graybill Conference |