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DeBoever, C. et al. Assessing Digital Phenotyping to Enhance Genetic Studies of Human Diseases. Am J Hum Genet 106, 611-622 (2020).
Claussnitzer, M. et al. A brief history of human disease genetics. Nature 577, 179-189 (2020).
Li, X. et al. Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale. Nat Genet 52, 969-983 (2020).
Zhong, X. et al. Electronic health record phenotypes associated with genetically regulated expression of CFTR and application to cystic fibrosis. Genet Med 22, 1191-1200 (2020).
Qian, J. et al. A fast and scalable framework for large-scale and ultrahigh-dimensional sparse regression with application to the UK Biobank. PLoS Genet 16, e1009141 (2020).
Rochtus, A. et al. Genetic diagnoses in epilepsy: The impact of dynamic exome analysis in a pediatric cohort. Epilepsia 61, 249-258 (2020).
Rau, C. D. et al. Modeling epistasis in mice and yeast using the proportion of two or more distinct genetic backgrounds: Evidence for "polygenic epistasis". PLoS Genet 16, e1009165 (2020).
Unlu, G. et al. Phenome-based approach identifies RIC1-linked Mendelian syndrome through zebrafish models, biobank associations and clinical studies. Nat Med 26, 98-109 (2020).
Tcheandjieu, C. et al. A phenome-wide association study of 26 mendelian genes reveals phenotypic expressivity of common and rare variants within the general population. PLoS Genet 16, e1008802 (2020).
Dahl, A. et al. A Robust Method Uncovers Significant Context-Specific Heritability in Diverse Complex Traits. Am J Hum Genet 106, 71-91 (2020).
Werling, D. M. et al. Whole-Genome and RNA Sequencing Reveal Variation and Transcriptomic Coordination in the Developing Human Prefrontal Cortex. Cell Rep 31, 107489 (2020).