Pierce, Brandon L.

The GTEx Consortium atlas of genetic regulatory effects across human tissues

The GTEx Consortium, Aguet, F., Anand, S., Ardlie, K. G., Gabriel, S., Getz, G. A., Graubert, A., Hadley, K., Handsaker, R. E., Huang, K. H., et al. (2020) · Science

Genetic Associations and EpidemiologyRNA Research and Splicing

Cited by 5,547

Unraveling the polygenic architecture of complex traits using blood eQTL metaanalysis

Võsa, U., Claringbould, A., Westra, H.-J., Bonder, M. J., Deelen, P., Zeng, B., Kirsten, H., Saha, A., Kreuzhuber, R., Kasela, S., et al. (2018) · Nature Genetics

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 2,607

Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression

Võsa, U., Claringbould, A., Westra, H.-J., Bonder, M. J., Deelen, P., Zeng, B., Kirsten, H., Saha, A., Kreuzhuber, R., Yazar, S., et al. (2021) · Nature Genetics

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 2,607

Efficient design for Mendelian randomization studies: subsample and 2-sample instrumental variable estimators.

Pierce, B. L., & Burgess, S. (2013) · American Journal of Epidemiology

Genetic Associations and EpidemiologyAdvanced Causal Inference Techniques

Cited by 1,389

A Quantitative Proteome Map of the Human Body

Jiang, L., Wang, M., Lin, S., Jian, R., Li, X., Chan, J., Dong, G., Fang, H., Robinson, A. E., Aguet, F., et al. (2020) · Cell

Advanced Proteomics Techniques and ApplicationsBioinformatics and Genomic Networks

Cited by 458

Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood

Qi, T., Wu, Y., Zeng, J., Zhang, F., Xue, A., Jiang, L., Zhu, Z., Kemper, K., Yengo, L., Zheng, Z., et al. (2018) · Nature Communications

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 427

Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits.

Porcu, E., Rüeger, S., Lepik, K., eQTLGen Consortium, Agbessi, M., Ahsan, H., Alves, I., Andiappan, A., Arindrarto, W., Awadalla, P., et al. (2019) · Nature Communications

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 322

Mendelian randomization study of adiposity-related traits and risk of breast, ovarian, prostate, lung and colorectal cancer

Gao, C., Patel, C. J., Michailidou, K., Peters, U., Gong, J., Schildkraut, J., Schumacher, F. R., Zheng, W., Boffetta, P., Stucker, I., et al. (2016) · International Journal of Epidemiology

Genetic Associations and EpidemiologyCancer Risks and Factors

Cited by 163

Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics

Barbeira, A. N., Dickinson, S. P., Bonazzola, R., Zheng, J., Wheeler, H. E., Torres, J. M., Torstenson, E. S., Shah, K. P., Garcia, T., Edwards, T. L., et al. (2018) · Nature Communications

Genetic Associations and EpidemiologyBioinformatics and Genomic Networks

Cited by 69