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Conference papers
Multiblock analysis of omics and imaging data with variable selection
Abstract : Sparse 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.
Cited literature [5 references]
https://www.hal.inserm.fr/inserm-01145569
Contributor : Nathalie Duchange <>
Submitted on : Friday, April 24, 2015 - 4:01:44 PM
Last modification on : Wednesday, September 16, 2020 - 5:48:51 PM
Long-term archiving on: : Wednesday, April 19, 2017 - 5:57:10 AM
Contributor : Nathalie Duchange <>
Submitted on : Friday, April 24, 2015 - 4:01:44 PM
Last modification on : Wednesday, September 16, 2020 - 5:48:51 PM
Long-term archiving on: : Wednesday, April 19, 2017 - 5:57:10 AM
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ACTES-RITS2015-HAL-p28-29.pdf
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