Publications

Export 57 results:
Author Title [ Year(Asc)]
2019
Liu, Y. et al. ACAT: A Fast and Powerful p Value Combination Method for Rare-Variant Analysis in Sequencing Studies. Am J Hum Genet 104, 410-421 (2019).
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).
Wang, Q. et al. A Bayesian framework that integrates multi-omics data and gene networks predicts risk genes from schizophrenia GWAS data. Nat Neurosci 22, 691-699 (2019).
Yang, H. et al. De novo pattern discovery enables robust assessment of functional consequences of non-coding variants. Bioinformatics 35, 1453-1460 (2019).
Dennis, J. et al. Diagnostic Algorithms to Study Post-Concussion Syndrome Using Electronic Health Records: Validating a Method to Capture an Important Patient Population. J Neurotrauma 36, 2167-2177 (2019).
Saito, Y. et al. Differential NOVA2-Mediated Splicing in Excitatory and Inhibitory Neurons Regulates Cortical Development and Cerebellar Function. Neuron 101, 707-720.e5 (2019).
Chen, H. et al. Efficient Variant Set Mixed Model Association Tests for Continuous and Binary Traits in Large-Scale Whole-Genome Sequencing Studies. Am J Hum Genet 104, 260-274 (2019).
Seplyarskiy, V. B. et al. Error-prone bypass of DNA lesions during lagging-strand replication is a common source of germline and cancer mutations. Nat Genet 51, 36-41 (2019).
Uricchio, L. H., Kitano, H. C., Gusev, A. & Zaitlen, N. A. An evolutionary compass for detecting signals of polygenic selection and mutational bias. Evol Lett 3, 69-79 (2019).
Xu, M. et al. Genome sequencing analysis identifies Epstein-Barr virus subtypes associated with high risk of nasopharyngeal carcinoma. Nat Genet 51, 1131-1136 (2019).
Unlu, G. et al. GRIK5 Genetically Regulated Expression Associated with Eye and Vascular Phenomes: Discovery through Iteration among Biobanks, Electronic Health Records, and Zebrafish. Am J Hum Genet 104, 503-519 (2019).
Frésard, L. et al. Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts. Nat Med 25, 911-919 (2019).
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).
Luo, R., Sedlazeck, F. J., Lam, T. - W. & Schatz, M. C. A multi-task convolutional deep neural network for variant calling in single molecule sequencing. Nat Commun 10, 998 (2019).
Wainberg, M. et al. Opportunities and challenges for transcriptome-wide association studies. Nat Genet 51, 592-599 (2019).
Abul-Husn, N. S. & Kenny, E. E. Personalized Medicine and the Power of Electronic Health Records. Cell 177, 58-69 (2019).
Sohail, M. et al. Polygenic adaptation on height is overestimated due to uncorrected stratification in genome-wide association studies. Elife 8, (2019).
Schoech, A. P. et al. Quantification of frequency-dependent genetic architectures in 25 UK Biobank traits reveals action of negative selection. Nat Commun 10, 790 (2019).
2018
Park, D. S. et al. An ancestry-based approach for detecting interactions. Genet Epidemiol 42, 49-63 (2018).
Hu, Y. et al. A common loss-of-function variant is associated with lower vitamin B concentration in African Americans. Blood 131, 2859-2863 (2018).
Verbanck, M., Chen, C. - Y., Neale, B. & Do, R. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat Genet 50, 693-698 (2018).
Westra, H. - J. et al. Fine-mapping and functional studies highlight potential causal variants for rheumatoid arthritis and type 1 diabetes. Nat Genet 50, 1366-1374 (2018).
Gazal, S. et al. Functional architecture of low-frequency variants highlights strength of negative selection across coding and non-coding annotations. Nat Genet 50, 1600-1607 (2018).
Regier, A. A. et al. Functional equivalence of genome sequencing analysis pipelines enables harmonized variant calling across human genetics projects. Nat Commun 9, 4038 (2018).
Slowikowski, K., Wei, K., Brenner, M. B. & Raychaudhuri, S. Functional genomics of stromal cells in chronic inflammatory diseases. Curr Opin Rheumatol 30, 65-71 (2018).
Belbin, G. M., Nieves-Colón, M. A., Kenny, E. E., Moreno-Estrada, A. & Gignoux, C. R. Genetic diversity in populations across Latin America: implications for population and medical genetic studies. Curr Opin Genet Dev 53, 98-104 (2018).
McInnes, G. et al. Global Biobank Engine: enabling genotype-phenotype browsing for biobank summary statistics. Bioinformatics (2018). doi:10.1093/bioinformatics/bty999
Wojcik, G. L. et al. Imputation-Aware Tag SNP Selection To Improve Power for Large-Scale, Multi-ethnic Association Studies. G3 (Bethesda) 8, 3255-3267 (2018).
DeBoever, C. et al. Medical relevance of protein-truncating variants across 337,205 individuals in the UK Biobank study. Nat Commun 9, 1612 (2018).
Liu, Z. & Lin, X. Multiple phenotype association tests using summary statistics in genome-wide association studies. Biometrics 74, 165-175 (2018).
Bastarache, L. et al. Phenotype risk scores identify patients with unrecognized Mendelian disease patterns. Science 359, 1233-1239 (2018).
Sordillo, J. E., Kraft, P., Wu, A. Chen & Asgari, M. M. Quantifying the Polygenic Contribution to Cutaneous Squamous Cell Carcinoma Risk. J Invest Dermatol 138, 1507-1510 (2018).
Li, H. et al. A synthetic-diploid benchmark for accurate variant-calling evaluation. Nat Methods 15, 595-597 (2018).
Sun, R., Carroll, R. J., Christiani, D. C. & Lin, X. Testing for gene-environment interaction under exposure misspecification. Biometrics 74, 653-662 (2018).
2017
Gottlieb, A. et al. Cohort-specific imputation of gene expression improves prediction of warfarin dose for African Americans. Genome Med 9, 98 (2017).
Aschard, H. et al. Covariate selection for association screening in multiphenotype genetic studies. Nat Genet 49, 1789-1795 (2017).
McAllister, K. et al. Current Challenges and New Opportunities for Gene-Environment Interaction Studies of Complex Diseases. Am J Epidemiol 186, 753-761 (2017).
Zaitlen, N. et al. The Effects of Migration and Assortative Mating on Admixture Linkage Disequilibrium. Genetics 205, 375-383 (2017).
Cassa, C. A. et al. Estimating the selective effects of heterozygous protein-truncating variants from human exome data. Nat Genet 49, 806-810 (2017).
Barnett, I., Mukherjee, R. & Lin, X. The Generalized Higher Criticism for Testing SNP-Set Effects in Genetic Association Studies. J Am Stat Assoc 112, 64-76 (2017).
Battle, A., Brown, C. D., Engelhardt, B. E. & Montgomery, S. B. Genetic effects on gene expression across human tissues. Nature 550, 204-213 (2017).
Belbin, G. Morven et al. Genetic identification of a common collagen disease in puerto ricans via identity-by-descent mapping in a health system. Elife 6, (2017).
He, L., Zhbannikov, I., Arbeev, K. G., Yashin, A. I. & Kulminski, A. M. A genetic stochastic process model for genome-wide joint analysis of biomarker dynamics and disease susceptibility with longitudinal data. Genet Epidemiol 41, 620-635 (2017).
Martin, A. R. et al. Human Demographic History Impacts Genetic Risk Prediction across Diverse Populations. Am J Hum Genet 100, 635-649 (2017).
Li, X. et al. The impact of rare variation on gene expression across tissues. Nature 550, 239-243 (2017).
Kichaev, G. et al. Improved methods for multi-trait fine mapping of pleiotropic risk loci. Bioinformatics 33, 248-255 (2017).
Ritchie, M. D. et al. Incorporation of Biological Knowledge Into the Study of Gene-Environment Interactions. Am J Epidemiol 186, 771-777 (2017).
Ritz, B. R. et al. Lessons Learned From Past Gene-Environment Interaction Successes. Am J Epidemiol 186, 778-786 (2017).
Fonseka, C. Y., Rao, D. A. & Raychaudhuri, S. Leveraging blood and tissue CD4+ T cell heterogeneity at the single cell level to identify mechanisms of disease in rheumatoid arthritis. Curr Opin Immunol 49, 27-36 (2017).
Chun, S. et al. Limited statistical evidence for shared genetic effects of eQTLs and autoimmune-disease-associated loci in three major immune-cell types. Nat Genet 49, 600-605 (2017).

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