Publications

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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).
Sofer, T., Schifano, E. D., Christiani, D. C. & Lin, X. Weighted pseudolikelihood for SNP set analysis with multiple secondary outcomes in case-control genetic association studies. Biometrics 73, 1210-1220 (2017).
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Sub-genic intolerance, ClinVar, and the epilepsies: A whole-exome sequencing study of 29,165 individuals. Am J Hum Genet 108, 965-982 (2021).
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Dahl, A. et al. A Robust Method Uncovers Significant Context-Specific Heritability in Diverse Complex Traits. Am J Hum Genet 106, 71-91 (2020).
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Bastarache, L. et al. Phenotype risk scores identify patients with unrecognized Mendelian disease patterns. Science 359, 1233-1239 (2018).
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).
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).
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Liu, Z. & Lin, X. Multiple phenotype association tests using summary statistics in genome-wide association studies. Biometrics 74, 165-175 (2018).
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).
J Weissenkampen, D. et al. Methods for the Analysis and Interpretation for Rare Variants Associated with Complex Traits. Curr Protoc Hum Genet 101, e83 (2019).
DeBoever, C. et al. Medical relevance of protein-truncating variants across 337,205 individuals in the UK Biobank study. Nat Commun 9, 1612 (2018).
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Amar, D., Sinnott-Armstrong, N., Ashley, E. A. & Rivas, M. A. Graphical analysis for phenome-wide causal discovery in genotyped population-scale biobanks. Nat Commun 12, 350 (2021).
McInnes, G. et al. Global Biobank Engine: enabling genotype-phenotype browsing for biobank summary statistics. Bioinformatics 35, 2495-2497 (2019).
Rochtus, A. et al. Genetic diagnoses in epilepsy: The impact of dynamic exome analysis in a pediatric cohort. Epilepsia 61, 249-258 (2020).
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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).
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Nayar, K. et al. Elevated Polygenic Burden for Autism Spectrum Disorder Is Associated With the Broad Autism Phenotype in Mothers of Individuals With Autism Spectrum Disorder. Biol Psychiatry 89, 476-485 (2021).
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).
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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).
Stern, A. J., Speidel, L., Zaitlen, N. A. & Nielsen, R. Disentangling selection on genetically correlated polygenic traits via whole-genome genealogies. Am J Hum Genet 108, 219-239 (2021).
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Sakaue, S. et al. A cross-population atlas of genetic associations for 220 human phenotypes. Nat Genet 53, 1415-1424 (2021).
Aschard, H. et al. Covariate selection for association screening in multiphenotype genetic studies. Nat Genet 49, 1789-1795 (2017).
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Claussnitzer, M. et al. A brief history of human disease genetics. Nature 577, 179-189 (2020).
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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).
Park, D. S. et al. An ancestry-based approach for detecting interactions. Genet Epidemiol 42, 49-63 (2018).
Dahl, A., Guillemot, V., Mefford, J., Aschard, H. & Zaitlen, N. Adjusting for Principal Components of Molecular Phenotypes Induces Replicating False Positives. Genetics 211, 1179-1189 (2019).