Work

Logistic Bayesian LASSO for genetic association analysis of data from complex sampling designs

Year: 2017

Type: article

Source: Journal of Human Genetics

DOI: 10.1038/jhg.2017.43

Authors: Yuan Zhang, Jonathan N Hofmann, Mark P Purdue, Shili Lin, Swati Biswas

Institutions: The University of Texas at Dallas, National Cancer Institute, Division of Cancer Epidemiology and Genetics, The Ohio State University

Language: English

Topic: Genetic Associations and Epidemiology

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Institutes of Health, National Cancer Institute, National Institute of General Medical Sciences

Awards: Identifying rare haplotype-environment interactions using Logistic Bayesian Lasso, Omics analysis of three-dimensional transcriptional regulation

OpenAlex ID: W2605493927

FWCI: 0.905

Cites: 34

Cited by: 15

Related to: 10