Gene-set distance analysis (GSDA): a powerful tool for gene-set association analysis.

ABSTRACT:

Background

Identifying sets of related genes (gene sets) that are empirically associated with a treatment or phenotype often yields valuable biological insights. Several methods effectively identify gene sets in which individual genes have simple monotonic relationships with categorical, quantitative, or censored event-time variables. Some distance-based methods, such as distance correlations, may detect complex non-monotone associations of a gene-set with a quantitative variable that elude other methods. However, the distance correlations have yet to be generalized to associate gene-sets with categorical and censored event-time endpoints. Also, there is a need to determine which genes empirically drive the significance of an association of a gene set with an endpoint.

Results</

SUBMITTER: Cao X 

PROVIDER: S-EPMC8059024 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature