Work

Linking regulatory variants to target genes by integrating single-cell multiome methods and genomic distance

Year: 2025

Type: article

Source: Nature Genetics

DOI: 10.1038/s41588-025-02220-3

Authors: Elizabeth Dorans, Karthik Jagadeesh, Kushal Dey, Alkes L. Price

Institutions: Broad Institute, Harvard University, Memorial Sloan Kettering Cancer Center, Weill Cornell Medicine, Louis V. Gerstner, Jr. Graduate School of Biomedical Sciences

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: U.S. Department of Health and Human Services, National Institutes of Health, National Institute of Mental Health, National Human Genome Research Institute, National Cancer Institute

Awards: G1007166040, G1403589279, G1700559947, Leveraging functional data to predict disease risk in multi-ethnic populations, G6568865999, G7165297371, G7496421227, G835666399, G8787444564, G9000131021, G9000286330, Cancer Center Support Grant, Statistical methods to localize disease heritability and identify biological mechanisms, Decoding disease-critical genomic architecture using multimodal single-cell omics data, New approaches for leveraging single-cell data to identify disease-critical genes and gene sets, Functional and population genetic architectures of complex disease, Integrating case-control transcriptomic and genetic data in admixed individuals to identify disease genes for schizophrenia and bipolar disorder, Integrative modelling of single-cell data to elucidate the genetic architecture of complex disease, Predicting the impact of genetic variants, genes and pathways on human Disease, Integrative modelling of single-cell data to elucidate the genetic architecture of complex disease

OpenAlex ID: W4411246217

FWCI: 5.263

Cites: 123

Cited by: 9

Related to: 10