Work

A suite of automated sequence analyses reduces the number of candidate deleterious variants and reveals a difference between probands and unaffected siblings

Year: 2019

Type: article

Source: Genetics in Medicine

DOI: 10.1038/s41436-019-0434-0

Authors: Fangning Gu, Anchi Wu, M. Grace Gordon, Lukas Vlahos, Shane Macnamara, Elizabeth Burke, May C. Malicdan, David R. Adams, Cynthia J. Tifft, Camilo Toro, William A. Gahl, Thomas C. Markello

Institutions: National Institutes of Health, National Human Genome Research Institute, Office of the Director

Language: English

Topic: Genomics and Rare Diseases

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: bronze

Funders: National Institutes of Health, National Human Genome Research Institute, Common Fund

Awards: EXPANDING AND ENHANCING THE GENE EXPRESSION DATABASE, G5294359063, NHGRI/DIR Clinical Support Services, Human Biochemical Genetics

OpenAlex ID: W2914405711

FWCI: 0.903

Cites: 36

Cited by: 6

Related to: 10