Work

High-throughput inference of pairwise coalescence times identifies signals of selection and enriched disease heritability

Year: 2018

Type: article

Source: Nature Genetics

DOI: 10.1038/s41588-018-0177-x

Authors: Pier Francesco Palamara, Jonathan Terhorst, Yun S. Song, Alkes L. Price

Institutions: Broad Institute, Harvard University, University of Oxford, University of Michigan, Chan Zuckerberg Biohub San Francisco, University of California, Berkeley

Language: English

Topic: Genetic Associations and Epidemiology

Subfield: Genetics

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

Funders: National Institutes of Health, Medical Research Council, National Institute of Mental Health, National Human Genome Research Institute, National Institute of General Medical Sciences, National Institute of Environmental Health Sciences

Awards: Improving Polygenic Prediction using Next-Generation Data Sets, G1554504499, PCA-based selection scans in very large samples, Leveraging functional data to predict disease risk in multi-ethnic populations, G5850737185, Functionally specialized components of disease heritability in ENCODE data, Mathematical Models and Statistical Methods for Large-Scale Population Genomics, Functional and population genetic architectures of complex disease

OpenAlex ID: W2789622920

FWCI: 4.447

Cites: 115

Cited by: 76

Related to: 10