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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).
Battle, A., Brown, C. D., Engelhardt, B. E. & Montgomery, S. B. Genetic effects on gene expression across human tissues. Nature 550, 204-213 (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).
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).
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).
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).
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).
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).
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).
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).
Herrera-Luis, E. et al. Genome-wide association study reveals a novel locus for asthma with severe exacerbations in diverse populations. Pediatr Allergy Immunol 32, 106-115 (2021).
McInnes, G. et al. Global Biobank Engine: enabling genotype-phenotype browsing for biobank summary statistics. Bioinformatics 35, 2495-2497 (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).
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Dietlein, F. et al. Identification of cancer driver genes based on nucleotide context. Nat Genet 52, 208-218 (2020).
Dietlein, F. et al. Identification of cancer driver genes based on nucleotide context. Nat Genet 52, 208-218 (2020).
Bonder, M. Jan et al. Identification of rare and common regulatory variants in pluripotent cells using population-scale transcriptomics. Nat Genet 53, 313-321 (2021).
Frésard, L. et al. Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts. Nat Med 25, 911-919 (2019).
Frésard, L. et al. Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts. Nat Med 25, 911-919 (2019).
Frésard, L. et al. Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts. Nat Med 25, 911-919 (2019).
Liu, B. & Montgomery, S. B. Identifying causal variants and genes using functional genomics in specialized cell types and contexts. Hum Genet 139, 95-102 (2020).
Gay, N. R. et al. Impact of admixture and ancestry on eQTL analysis and GWAS colocalization in GTEx. Genome Biol 21, 233 (2020).
Li, X. et al. The impact of rare variation on gene expression across tissues. Nature 550, 239-243 (2017).
Li, X. et al. The impact of rare variation on gene expression across tissues. Nature 550, 239-243 (2017).
Li, X. et al. The impact of rare variation on gene expression across tissues. Nature 550, 239-243 (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).
Ji, Y. et al. Incorporating European GWAS findings improve polygenic risk prediction accuracy of breast cancer among East Asians. Genet Epidemiol (2021). doi:10.1002/gepi.22382
Ji, Y. et al. Incorporating European GWAS findings improve polygenic risk prediction accuracy of breast cancer among East Asians. Genet Epidemiol (2021). doi:10.1002/gepi.22382
Sun, R. et al. Integration of multiomic annotation data to prioritize and characterize inflammation and immune-related risk variants in squamous cell lung cancer. Genet Epidemiol 45, 99-114 (2021).
Sun, R. et al. Integration of multiomic annotation data to prioritize and characterize inflammation and immune-related risk variants in squamous cell lung cancer. Genet Epidemiol 45, 99-114 (2021).
Sun, R. et al. Integration of multiomic annotation data to prioritize and characterize inflammation and immune-related risk variants in squamous cell lung cancer. Genet Epidemiol 45, 99-114 (2021).
Sun, R. et al. Integration of multiomic annotation data to prioritize and characterize inflammation and immune-related risk variants in squamous cell lung cancer. Genet Epidemiol 45, 99-114 (2021).
Sun, R. et al. Integration of multiomic annotation data to prioritize and characterize inflammation and immune-related risk variants in squamous cell lung cancer. Genet Epidemiol 45, 99-114 (2021).
Sun, R. et al. Integration of multiomic annotation data to prioritize and characterize inflammation and immune-related risk variants in squamous cell lung cancer. Genet Epidemiol 45, 99-114 (2021).
Sun, R. et al. Integration of multiomic annotation data to prioritize and characterize inflammation and immune-related risk variants in squamous cell lung cancer. Genet Epidemiol 45, 99-114 (2021).
Sun, R. et al. Integration of multiomic annotation data to prioritize and characterize inflammation and immune-related risk variants in squamous cell lung cancer. Genet Epidemiol 45, 99-114 (2021).
Goddard, P. C. et al. Integrative genomic analysis in African American children with asthma finds three novel loci associated with lung function. Genet Epidemiol 45, 190-208 (2021).
Goddard, P. C. et al. Integrative genomic analysis in African American children with asthma finds three novel loci associated with lung function. Genet Epidemiol 45, 190-208 (2021).

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