Publications

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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).
Frésard, L. et al. Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts. Nat Med 25, 911-919 (2019).
Gay, N. R. et al. Impact of admixture and ancestry on eQTL analysis and GWAS colocalization in GTEx. Genome Biol 21, 233 (2020).
Kichaev, G. et al. Improved methods for multi-trait fine mapping of pleiotropic risk loci. Bioinformatics 33, 248-255 (2017).
Amariuta, T. et al. Improving the trans-ancestry portability of polygenic risk scores by prioritizing variants in predicted cell-type-specific regulatory elements. Nat Genet 52, 1346-1354 (2020).
Ritchie, M. D. et al. Incorporation of Biological Knowledge Into the Study of Gene-Environment Interactions. Am J Epidemiol 186, 771-777 (2017).
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).
P
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).
Aguirre, M., Rivas, M. A. & Priest, J. Phenome-wide Burden of Copy-Number Variation in the UK Biobank. Am J Hum Genet 105, 373-383 (2019).
Bastarache, L. et al. Phenotype risk scores identify patients with unrecognized Mendelian disease patterns. Science 359, 1233-1239 (2018).
Bastarache, L. et al. Phenotype risk scores identify patients with unrecognized Mendelian disease patterns. Science 359, 1233-1239 (2018).
Bastarache, L. et al. Phenotype risk scores identify patients with unrecognized Mendelian disease patterns. Science 359, 1233-1239 (2018).
Sohail, M. et al. Polygenic adaptation on height is overestimated due to uncorrected stratification in genome-wide association studies. Elife 8, (2019).
Aguirre, M. et al. Polygenic risk modeling with latent trait-related genetic components. Eur J Hum Genet (2021). doi:10.1038/s41431-021-00813-0
Pala, M. et al. Population- and individual-specific regulatory variation in Sardinia. Nat Genet 49, 700-707 (2017).
Seplyarskiy, V. B. et al. Population sequencing data reveal a compendium of mutational processes in the human germ line. Science 373, 1030-1035 (2021).
Seplyarskiy, V. B. et al. Population sequencing data reveal a compendium of mutational processes in the human germ line. Science 373, 1030-1035 (2021).
Seplyarskiy, V. B. et al. Population sequencing data reveal a compendium of mutational processes in the human germ line. Science 373, 1030-1035 (2021).
Seplyarskiy, V. B. et al. Population sequencing data reveal a compendium of mutational processes in the human germ line. Science 373, 1030-1035 (2021).
de Goede, O. M. et al. Population-scale tissue transcriptomics maps long non-coding RNAs to complex disease. Cell 184, 2633-2648.e19 (2021).
Asgari, S. et al. A positively selected FBN1 missense variant reduces height in Peruvian individuals. Nature 582, 234-239 (2020).

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