Canonical Correlation Analysis to relate a Genomic Dataset with a Neuroimage Dataset.

Abstract

This thesis investigates the relationship between copy number variations and neuro-image features of Glioblastoma patients. Canonical correlation analysis was employed to elicit these relationships. This thesis highlights some of the concepts of the technique which enabled us to obtain our main results. We found three pairs of significant canonical variates with correlations of 0:6704;0:6347 and 0:5552 respectively, which was used to identify genes and neuro-image features related to Glioblastoma.