Spherical Topic Models for Imaging Phenotype Discovery in Genetic Studies.
Ontology highlight
ABSTRACT: In this paper, we use Spherical Topic Models to discover the latent structure of lung disease. This method can be widely employed when a measurement for each subject is provided as a normalized histogram of relevant features. In this paper, the resulting descriptors are used as phenotypes to identify genetic markers associated with the Chronic Obstructive Pulmonary Disease (COPD). Features extracted from images capture the heterogeneity of the disease and therefore promise to improve detection of relevant genetic variants in Genome Wide Association Studies (GWAS). Our generative model is based on normalized histograms of image intensity of each subject and it can be readily extended to other forms of features as long as they are provided as normalized histograms. The resulting algorithm re
SUBMITTER: Batmanghelich KN
PROVIDER: S-EPMC4337963 | biostudies-literature | 2014
REPOSITORIES: biostudies-literature
ACCESS DATA