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Collaborative Center for Statistics in Science
300 George Street
Suite 523
New Haven CT, 06511
Phone: (203) 785-5185
Fax: (203) 785-5145

Introduction to Tree - and Forest-based Genomic Analysis

Multiple genes, gene-by-gene interactions, and gene-by-environment interactions are believed to underlie most complex diseases. However, such interactions are difficult to identify. While there have been recent successes in identifying genetic variants for complex diseases, it still remains difficult to identify gene-gene and gene-environment interactions. To overcome this difficulty, we propose a forest-based approach and a concept of variable importance. The proposed approach is demonstrated by simulation study for its validity and illustrated by a real data analysis for its use. Analyses of both real data and simulated data based on published genetic models show the effectiveness of our approach.
In this brief presentation, I describe the recursive partitioning technique using a microarray data as an example. Forest constructions using bagging and a deterministic scheme are described.

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