Work

SEQSpark: A Complete Analysis Tool for Large-Scale Rare Variant Association Studies Using Whole-Genome and Exome Sequence Data

Year: 2017

Type: article

Source: The American Journal of Human Genetics

DOI: 10.1016/j.ajhg.2017.05.017

Authors: Di Zhang, Linhai Zhao, Biao Li, Zongxiao He, Gao T. Wang, Dajiang J. Liu, Suzanne M. Leal

Institutions: Baylor College of Medicine, University of Chicago, Pennsylvania 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: bronze

Funders: Medical Research Council, National Institute on Aging, National Human Genome Research Institute, U.S. National Library of Medicine

Awards: G1452797817, Computational tools for sequence-based large-scale epidemiology studies, Family-based methods to analyze sequence data to elucidate AD etiology, G6689231961, NLM Research Training Program in Biomedical Informatics and Data Science for Predoctoral and Postdoctoral Fellows

OpenAlex ID: W2734317952

FWCI: 1.086

Cites: 24

Cited by: 12

Related to: 10