Adaptively Integrative Association between Multivariate Phenotypes and Transcriptomic Data for Complex Diseases.

ABSTRACT: Phenotype-gene association studies can uncover disease mechanisms for translational research. Association with multiple phenotypes or clinical variables in complex diseases has the advantage of increasing statistical power and offering a holistic view. Existing multi-variate association methods mostly focus on SNP-based genetic associations. In this paper, we extend and evaluate two adaptive Fisher's methods, namely AFp and AFz, from the p-value combination perspective for phenotype-mRNA association analysis. The proposed method effectively aggregates heterogeneous phenotype-gene effects, allows association with different data types of phenotypes, and performs the selection of the associated phenotypes. Variability indices of the phenotype-gene effect selection are calculated by boo

SUBMITTER: Li Y 

PROVIDER: S-EPMC10138055 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature