Multiblock analysis of omics and imaging data with variable selection

Congrès sous l’égide de la Société Française de Génie Biologique et Médical (SFGBM)National audienceSparse generalized canonical correlation analysis (SGCCA) has been proposed to combine RGCCA with an ℓ 1-penalty in a unified framework. Within this framework, blocks are not necessarily fully connected, which provides flexibility. The versatility and usefulness of SGCCA are illustrated on a 3-block dataset which combine Gene Expression, Comparative Genomic Hybridiza-tion and tumor location, determined on RMI at diagnosis. All data were measured on a cohort of 53 children with High Grade Glioma. SGCCA is available on CRAN as part of the RGCCA package