Battle, Alexis

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

The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans

The GTEx Consortium, Ardlie, K. G., Deluca, D. S., Segrè, A. V., Sullivan, T. J., Young, T. R., Gelfand, E. T., Trowbridge, C. A., Maller, J. B., Tukiainen, T., et al. (2015) · Science

Genetic Associations and EpidemiologyGenomics and Chromatin Dynamics

Cited by 5,062

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

Characterizing the genetic basis of transcriptome diversity through RNA-sequencing of 922 individuals

Battle, A., Mostafavi, S., Zhu, X., Potash, J. B., Weissman, M. M., McCormick, C., Haudenschild, C. D., Beckman, K. B., Shi, J., Mei, R., et al. (2014) · Genome Research

Genetic Associations and EpidemiologyRNA Research and Splicing

Cited by 547

Determinants of telomere length across human tissues

Demanelis, K., Jasmine, F., Chen, L. S., Chernoff, M., Tong, L., Delgado, D., Zhang, C., Shinkle, J., Sabarinathan, M., Lin, H., et al. (2020) · Science

Telomeres, Telomerase, and SenescenceGenetics, Aging, and Longevity in Model Organisms

Cited by 515

The impact of structural variation on human gene expression

GTEx Consortium, Chiang, C., Scott, A. J., Davis, J. R., Tsang, E. K., Li, X., Kim, Y., Hadzic, T., Damani, F. N., Ganel, L., et al. (2017) · Nature Genetics

Genomic variations and chromosomal abnormalitiesGenetic Associations and Epidemiology

Cited by 495

Impact of regulatory variation from RNA to protein

Battle, A., Khan, Z., Wang, S. H., Mitrano, A., Ford, M. J., Pritchard, J. K., & Gilad, Y. (2015) · Science

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 471

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

Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts

Undiagnosed Diseases Network, Frésard, L., Care4Rare Canada Consortium, Smail, C., Ferraro, N. M., Teran, N. A., Li, X., Smith, K. S., Bonner, D., Kernohan, K. D., et al. (2019) · Nature Medicine

Genomics and Rare DiseasesGenomics and Phylogenetic Studies

Cited by 321

Effect of predicted protein-truncating genetic variants on the human transcriptome

Rivas, M. A., Pirinen, M., Conrad, D. F., Lek, M., Tsang, E. K., Karczewski, K. J., Maller, J. B., Kukurba, K. R., DeLuca, D. S., Fromer, M., et al. (2015) · Science

Genomics and Rare DiseasesRNA Research and Splicing

Cited by 313

Retinal transcriptome and eQTL analyses identify genes associated with age-related macular degeneration

Ratnapriya, R., Sosina, O. A., Starostik, M. R., Kwicklis, M., Kapphahn, R. J., Fritsche, L. G., Walton, A., Arvanitis, M., Gieser, L., Pietraszkiewicz, A., et al. (2019) · Nature Genetics

Retinal Diseases and TreatmentsGenetic Associations and Epidemiology

Cited by 312

Where Are the Disease-Associated eQTLs?

Umans, B. D., Battle, A., & Gilad, Y. (2021) · Trends in Genetics

Genetic Associations and EpidemiologyGenomics and Chromatin Dynamics

Cited by 296

The Genotype-Tissue Expression (GTEx) project

Lonsdale, J., Thomas, J., Salvatore, M., Phillips, R., Lo, E., Shad, S., Hasz, R., Walters, G., Garcia, F., Young, N., et al. (2013) · Nature Genetics

Genetic Associations and EpidemiologyGenomics and Chromatin Dynamics

Cited by 263

Dynamic genetic regulation of gene expression during cellular differentiation

Strober, B. J., Elorbany, R., Rhodes, K., Krishnan, N., Tayeb, K., Battle, A., & Gilad, Y. (2019) · Science

Genetic Associations and EpidemiologyGenomics and Chromatin Dynamics

Cited by 219

Type I interferon signaling genes in recurrent major depression: increased expression detected by whole-blood RNA sequencing

Mostafavi, S., Battle, A., Zhu, X., Potash, J. B., Weissman, M. M., Shi, J., Beckman, K., Haudenschild, C., McCormick, C., Mei, R., et al. (2014) · Molecular Psychiatry

Tryptophan and brain disordersTreatment of Major Depression

Cited by 187

Sharing and Specificity of Co-expression Networks across 35 Human Tissues

Pierson, E., the GTEx Consortium, Koller, D., Battle, A., & Mostafavi, S. (2015) · PLOS Computational Biology

Bioinformatics and Genomic NetworksGene Regulatory Network Analysis

Cited by 177

Molecular quantitative trait loci

Aguet, F., Alasoo, K., Li, Y. I., Battle, A., Im, H. K., Montgomery, S. B., & Lappalainen, T. (2023) · Nature Reviews Methods Primers

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 98

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

A systematic comparison of computational methods for expression forecasting

Kernfeld, E., Yang, Y., Weinstock, J. S., Battle, A., & Cahan, P. (2023) · bioRxiv (Cold Spring Harbor Laboratory)

Gene Regulatory Network AnalysisGene expression and cancer classification

Cited by 15