ENFORCING CO-EXPRESSION IN MULTIMODAL REGRESSION FRAMEWORK.

ABSTRACT: We consider the problem of multimodal data integration for the study of complex neurological diseases (e.g. schizophrenia). Among the challenges arising in such situation, estimating the link between genetic and neurological variability within a population sample has been a promising direction. A wide variety of statistical models arose from such applications. For example, Lasso regression and its multitask extension are often used to fit a multivariate linear relationship between given phenotype(s) and associated observations. Other approaches, such as canonical correlation analysis (CCA), are widely used to extract relationships between sets of variables from different modalities. In this paper, we propose an exploratory multivariate method combining these two methods. More Specifically,

SUBMITTER: Zille P 

PROVIDER: S-EPMC5415360 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature