Expectile Neural Networks for Genetic Data Analysis of Complex Diseases.

ABSTRACT: The genetic etiologies of common diseases are highly complex and heterogeneous. Classic methods, such as linear regression, have successfully identified numerous variants associated with complex diseases. Nonetheless, for most diseases, the identified variants only account for a small proportion of heritability. Challenges remain to discover additional variants contributing to complex diseases. Expectile regression is a generalization of linear regression and provides complete information on the conditional distribution of a phenotype of interest. While expectile regression has many nice properties, it has rarely been used in genetic research. In this paper, we develop an expectile neural network (ENN) method for genetic data analyses of complex diseases. Similar to expectile regression, E

SUBMITTER: Lin J 

PROVIDER: S-EPMC10201460 | biostudies-literature | 2023 Jan-Feb

REPOSITORIES: biostudies-literature