Random-Effects Model Aimed at Discovering Associations in Meta-Analysis of Genome-wide Association Studies

Meta-analysis in clinical trials

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Quantifying heterogeneity in a meta‐analysis

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Statistical Aspects of the Analysis of Data From Retrospective Studies of Disease

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Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls

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Finding the missing heritability of complex diseases

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A haplotype map of the human genome

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The combination of estimates from different experiments

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A second generation human haplotype map of over 3.1 million SNPs

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Genomic Control for Association Studies

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Genome-wide association studies for complex traits: consensus, uncertainty and challenges

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Epigenome-wide association study of lung function in Latino children and youth with asthma

Luis, E. H., Li, A., Mak, A. C. Y., Pérez-García, J., Elhawary, J. R., Oh, S. S., Hu, D., Eng, C. S., Keys, K. L., Huntsman, S., et al. (2022) · Clinical Epigenetics · doi:10.1186/s13148-022-01227-5 · Cited by 21

A landscape of gene expression regulation for synovium in arthritis

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Integrated analysis of human genetic association study and mouse transcriptome suggests LBH and SHF genes as novel susceptible genes for amyloid-β accumulation in Alzheimer’s disease

Yamaguchi‐Kabata, Y., Morihara, T., Ohara, T., Ninomiya, T., Takahashi, A., Akatsu, H., Hashizume, Y., Hayashi, N., Shigemizu, D., Boroevich, K. A., et al. (2018) · Human Genetics · doi:10.1007/s00439-018-1906-z · Cited by 20

Genome-Wide Association Analysis of the Sense of Smell in U.S. Older Adults: Identification of Novel Risk Loci in African-Americans and European-Americans

Dong, J., Wyss, A. B., Yang, J., Price, T. R., Nicolas, A., Nalls, M. A., Tranah, G. J., Franceschini, N., Xu, Z., Schulte, C., et al. (2016) · Molecular Neurobiology · doi:10.1007/s12035-016-0282-8 · Cited by 21

Largest genome-wide association study for PTSD identifies genetic risk loci in European and African ancestries and implicates novel biological pathwaysPreprint

Nievergelt, C. M., Maihofer, A. X., Klengel, T., Atkinson, E. G., Chen, C., Choi, K. W., Coleman, J. R. I., Dalvie, S., Duncan, L. E., Logue, M. W., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/458562 · Cited by 24

Assessment and ascertainment in psychiatric molecular genetics: challenges and opportunities for cross-disorder research

Cai, N., Verhulst, B., Andreassen, O. A., Buitelaar, J. K., Edenberg, H. J., Hettema, J. M., Gandal, M. J., Grotzinger, A. D., Jonas, K. G., Lee, P., et al. (2024) · Molecular Psychiatry · doi:10.1038/s41380-024-02878-x · Cited by 18

Sequence-based GWAS in 180,000 German Holstein cattle reveals new candidate variants for milk production traits

Križanac, A.-M., Reimer, C., Heise, J., Liu, Z., Pryce, J. E., Bennewitz, J., Thaller, G., Falker‐Gieske, C., & Tetens, J. (2025) · Genetics Selection Evolution · doi:10.1186/s12711-025-00951-9 · Cited by 31

Alzheimer’s disease transcriptional landscape in ex vivo human microglia

Kosoy, R., Fullard, J. F., Bendl, J. M., Kleopoulos, S. P., Shao, Z., Argyriou, S., Mathur, D. D., Psychogyiou, K., Malakates, P., Vicari, J. M., et al. (2025) · Nature Neuroscience · doi:10.1038/s41593-025-02020-2 · Cited by 22

Nucleosides Associated With Incident Ischemic Stroke in the REGARDS and JHS Cohorts

Ament, Z., Patki, A., Chaudhary, N. S., Bhave, V. M., Guarniz, A. G., Gao, Y., Gerszten, R. E., Correa, A., Judd, S. E., Cushman, M., et al. (2022) · Neurology · doi:10.1212/wnl.0000000000200262 · Cited by 20

metaGE: Investigating genotype x environment interactions through GWAS meta-analysis

Walsche, A. D., Vergne, A., Rincent, R., Roux, F., Nicolas, S., Welcker, C., Mezmouk, S., Charcosset, A., & Mary‐Huard, T. (2025) · PLoS Genetics · doi:10.1371/journal.pgen.1011553 · Cited by 27

Shared genetics and causal relationships between migraine and thyroid function traits

Tasnim, S., Wilson, S. G., Walsh, J. P., & Nyholt, D. R. (2023) · Cephalalgia · doi:10.1177/03331024221139253 · Cited by 19

Identification of new risk loci shared across systemic vasculitides points towards potential target genes for drug repurposing

Ortiz‐Fernández, L., Carmona, E. G., Kerick, M., Lyons, P., Carmona, F. D., Mejías, R. L., Khor, C. C., Grayson, P. C., Tombetti, E., Jiang, L., et al. (2023) · Annals of the Rheumatic Diseases · doi:10.1136/ard-2022-223697 · Cited by 19

Multi-trait discovery and fine-mapping of lipid loci in 125,000 individuals of African ancestry

Kamiza, A. B., Touré, S. M., Zhou, F., Soremekun, O. S., Cissé, C., Wélé, M., Touré, A. M., Nashiru, O., Corpas, M., Nyirenda, M., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-41271-0 · Cited by 19

Integrated multiomics approach identifies calcium and integrin-binding protein-2 as a novel gene for pulse wave velocity

Mangino, M., Cecelja, M., Menni, C., Tsai, P.-C., Yuan, W., Small, K. S., Bell, J. T., Mitchell, G. F., Chowienczyk, P., & Spector, T. D. (2015) · Journal of Hypertension · doi:10.1097/hjh.0000000000000732 · Cited by 19

Rigorous tests of gene–environment interactions in a lab study of the oxytocin receptor gene (OXTR), alcohol exposure, and aggression

LoParo, D., Johansson, A., Walum, H., Westberg, L., Santtila, P. O., & Waldman, I. D. (2015) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32359 · Cited by 21

A Novel Random Effect Model for GWAS Meta-Analysis and Its Application to Trans-Ethnic Meta-Analysis

Shi, J., & Lee, S. (2016) · Biometrics · doi:10.1111/biom.12481 · Cited by 17

Association of IL18 genetic polymorphisms with Chagas disease in Latin American populations

Strauss, M., Acosta‐Herrera, M., Alcaraz, A., Casares‐Marfil, D., Bosch‐Nicolau, P., Presti, M. S. L., Molina, I., González, C. I., Chagas Genetics CYTED Network, & Martín, J. (2019) · PLoS neglected tropical diseases · doi:10.1371/journal.pntd.0007859 · Cited by 19

Single Nucleotide Polymorphism rs6942067 Is a Risk Factor in Young and in Non-Smoking Patients with HPV Negative Head and Neck Squamous Cell Carcinoma

Cardin, G. B., Bernard, M., Bahig, H., Nguyen‐Tan, P. F., Ballivy, O., Filion, É., Soulières, D., Philouze, P., Ayad, T., Guertin, L., et al. (2019) · Cancers · doi:10.3390/cancers12010055 · Cited by 19

Modelling Clustered Heterogeneity: Fixed Effects, Random Effects and Mixtures

Tutz, G., & Oelker, M. (2016) · International Statistical Review · doi:10.1111/insr.12161 · Cited by 19

GenomeMUSter mouse genetic variation service enables multitrait, multipopulation data integration and analysisPreprint

Ball, R. L., Bogue, M. A., Liang, H., Srivastava, A., Ashbrook, D. G., Lamoureux, A., Gerring, M. W., Hatoum, A. S., Kim, M. J., He, H., et al. (2024) · Genome Research · doi:10.1101/gr.278157.123 · Cited by 18

Fine-mapping across diverse ancestries drives the discovery of putative causal variants underlying human complex traits and diseases

Yuan, K., Longchamps, R. J., Pardiñas, A. F., Yu, M., Chen, T.-T., Lin, S.-C., Chen, Y., Lam, M., Liu, R., Xia, Y., et al. (2023) · doi:10.1101/2023.01.07.23284293 · Cited by 94

Complement component C4 structural variation and quantitative traits contribute to sex-biased vulnerability in systemic sclerosis

Kerick, M., Acosta‐Herrera, M., Simeón‐Aznar, C. P., Callejas-Rubio, J. L., Assassi, S., International SSc Group, Carreira, P. E., Castellvi, I., Ríos, R., García-Portales, R., et al. (2022) · npj Genomic Medicine · doi:10.1038/s41525-022-00327-8 · Cited by 18

From SNP to pathway-based GWAS meta-analysis: do current meta-analysis approaches resolve power and replication in genetic association studies?

Defo, J., Awany, D., & Ramesar, R. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbac600 · Cited by 20

Oral targeted therapies in the treatment of pulmonary arterial hypertension: A meta-analysis of clinical trials

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Japanese GWAS identifies variants for bust-size, dysmenorrhea, and menstrual fever that are eQTLs for relevant protein-coding or long non-coding RNAs

Hirata, T., Koga, K., Johnson, T. A., Morino, R., Nakazono, K., Kamitsuji, S., Akita, M., Kawajiri, M., Kami, A., Hoshi, Y., et al. (2018) · Scientific Reports · doi:10.1038/s41598-018-25065-9 · Cited by 18

Genome-Wide Association Study Identifies Genetic Risk Factors for Spastic Cerebral Palsy

Hale, A. T., Akinnusotu, O., He, J., Wang, J., Hibshman, N., Shannon, C. N., & Naftel, R. P. (2021) · Neurosurgery · doi:10.1093/neuros/nyab184 · Cited by 16

Reviewing and assessing existing meta-analysis models and tools

Makinde, F., Tchamga, M. S. S., Jafali, J., Fatumo, S., Chimusa, E. R., Mulder, N., & Mazandu, G. K. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab324 · Cited by 19

Assessment of genetic susceptibility to multiple primary cancers through whole-exome sequencing in two large multi-ancestry studies

Cavazos, T. B., Kachuri, L., Graff, R. E., Nierenberg, J. L., Thai, K. K., Alexeeff, S., Eeden, S. K. V. D., Corley, D. A., Kushi, L. H., Abecasis, G. R., et al. (2022) · BMC Medicine · doi:10.1186/s12916-022-02535-6 · Cited by 18

A large genome-wide association study of QT interval length utilizing electronic health records

Hoffmann, T. J., Lü, M., Oni‐Orisan, A., Lee, C., RISCH, N. J., & Iribarren, C. (2022) · Genetics · doi:10.1093/genetics/iyac157 · Cited by 17

H3AGWAS: a portable workflow for genome wide association studies

Brandenburg, J., Clark, L. V., Botha, G., Panji, S., Baichoo, S., Fields, C. J., & Hazelhurst, S. (2022) · BMC Bioinformatics · doi:10.1186/s12859-022-05034-w · Cited by 17

Cross-trait analyses identify shared genetics between migraine, headache, and glycemic traits, and a causal relationship with fasting proinsulin

Islam, M. R., & Nyholt, D. R. (2023) · Human Genetics · doi:10.1007/s00439-023-02532-6 · Cited by 17

Mouse phenome database: curated data repository with interactive multi-population and multi-trait analyses

Bogue, M. A., Ball, R. L., Walton, D. O., Dunn, M. H., Kolishovski, G., Berger, A., Lamoureux, A., Grubb, S. C., Gerring, M. W., Kim, M. J., et al. (2023) · Mammalian Genome · doi:10.1007/s00335-023-10014-3 · Cited by 16

Trans‐Ethnic Meta‐Analysis Identifies Common and Rare Variants Associated with Hepatocyte Growth Factor Levels in the Multi‐Ethnic Study of Atherosclerosis (MESA)

Larson, N. B., Berardi, C., Decker, P. A., Wassel, C. L., Kirsch, P. S., Pankow, J. S., Sale, M. M., de Andrade, M., Sicotte, H., Tang, W., et al. (2015) · Annals of Human Genetics · doi:10.1111/ahg.12119 · Cited by 17

Fine-mapping analysis revealed complex pleiotropic effect and tissue-specific regulatory mechanism of TNFSF15 in primary biliary cholangitis, Crohn’s disease and leprosy

Sun, Y., Irwanto, A. K., Toyo-oka, L., Hong, M., Liu, H., Andiappan, A. K., Choi, H., Hitomi, Y., Yu, G., Yu, Y., et al. (2016) · Scientific Reports · doi:10.1038/srep31429 · Cited by 16

A Novel Locus Predicts Spermatogenic Recovery among Childhood Cancer Survivors Exposed to Alkylating Agents

Sapkota, Y., Wilson, C. L., Zaidi, A. K., Moon, W., Tacer, K. F., Lu, L., Liu, Q., Baedke, J. L., Dhaduk, R., Wang, Z., et al. (2020) · Cancer Research · doi:10.1158/0008-5472.can-20-0093 · Cited by 17

Childhood Neighborhood Disadvantage, Parenting, and Adult Health

Mrug, S., Barker-Kamps, M., Orihuela, C. A., Patki, A., & Tiwari, H. K. (2022) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2022.01.028 · Cited by 19

An evaluation of different meta-analysis approaches in the presence of allelic heterogeneity

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Genome-Wide Association Analyses of Equine Metabolic Syndrome Phenotypes in Welsh Ponies and Morgan Horses

Norton, E. M., Schultz, N. E., Geor, R. J., McFarlane, D., Mickelson, J. R., & McCue, M. E. (2019) · Genes · doi:10.3390/genes10110893 · Cited by 16

Leveraging the local genetic structure for trans-ancestry association mapping

Xiao, J., Cai, M., Yu, X., Hu, X., Chen, G., Wan, X., & Yang, C. (2022) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2022.05.013 · Cited by 15

Whole‐exome rare‐variant analysis of Alzheimer's disease and related biomarker traits

Küçükali, F., Neumann, A., Dongen, J. V., Pooter, T. D., Joris, G., Rijk, P. D., Ohlei, O., Dobričić, V., Bos, I., Vos, S. J. B., et al. (2022) · Alzheimer s & Dementia · doi:10.1002/alz.12842 · Cited by 16

Meta-analysis of genetic association studies under heterogeneity

Neupane, B., Loeb, M. B., Anand, S. S., & Beyene, J. (2012) · European Journal of Human Genetics · doi:10.1038/ejhg.2012.75 · Cited by 16

Celebrity Suicides and Their Differential Influence on Suicides in the General Population: A National Population-Based Study in Korea

Myung, W., Won, H., D, M. F. M., Mischoulon, D., Yeung, A., Lee, D., Kim, D. K., & Jeon, H. J. (2015) · Psychiatry Investigation · doi:10.4306/pi.2015.12.2.204 · Cited by 16

Myasthenia gravis genome-wide association study implicates AGRN as a risk locus

Topaloudi, A., Zagoriti, Z., Flint, A. C., Martinez, M. B., Yang, Z., Tsetsos, F., Christou, Y.-P., Lagoumintzis, G., Yannaki, E., Zamba‐Papanicolaou, E., et al. (2021) · Journal of Medical Genetics · doi:10.1136/jmedgenet-2021-107953 · Cited by 15

Structural variants are a major source of gene expression differences in humans and often affect multiple nearby genesPreprint

Scott, A. J., Chiang, C., & Hall, I. M. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.03.06.434233 · Cited by 16

Structural variants linked to Alzheimer’s disease and other common age-related clinical and neuropathologic traits

Vialle, R. A., Lopes, K. D. P., Li, Y., Ng, B., Schneider, J. A., Buchman, A. S., Wang, Y., Farfel, J. M., Barnes, L. L., Wingo, A. P., et al. (2025) · Genome Medicine · doi:10.1186/s13073-025-01444-6 · Cited by 19

Genetic polymorphisms of IL17A associated with Chagas disease: results from a meta-analysis in Latin American populations

Strauss, M., Palma-Vega, M., Casares‐Marfil, D., Bosch‐Nicolau, P., Presti, M. S. L., Molina, I., González, C. I., Chagas Genetics CYTED Network, Paglini, P. A., Schijman, A. G., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-61965-5 · Cited by 15

Investigating the genetic architecture of eye colour in a Canadian cohort

Lona‐Durazo, F., Thakur, R., Pairo‐Castineira, E., Funderburk, K. M., Zhang, T., Kovacs, M. A., Choi, J., Jackson, I. J., Brown, K. M., & Parra, E. J. (2022) · iScience · doi:10.1016/j.isci.2022.104485 · Cited by 16

Admixture mapping identifies novel Alzheimer's disease risk regions in African Americans

Rajabli, F., Tosto, G., Hamilton‐Nelson, K. L., Kunkle, B. W., Vardarajan, B. N., Naj, A. C., Whitehead, P. G., Gardner, O. K., Bush, W. S., Sariya, S., et al. (2022) · Alzheimer s & Dementia · doi:10.1002/alz.12865 · Cited by 15

FarmGTEx TWAS-server: An Interactive Web Server for Customized TWAS Analysis

Zhang, Z., Chen, Z., Teng, J., Lin, Q., Lin, Q., Wu, J., Gao, Y., Bai, Z., Fang, L., Bai, Z., et al. (2025) · Genomics Proteomics & Bioinformatics · doi:10.1093/gpbjnl/qzaf006 · Cited by 15

A vascular endothelial growth factor receptor gene variant is associated with susceptibility to acute respiratory distress syndrome

the GEN-SEP Network, Hernandez‐Pacheco, N., Guillén‐Guío, B., Acosta‐Herrera, M., Pino-Yanes, M. D. M., Corrales, A., Ambrós, A., Nogales, L., Muriel, A., González-Higueras, E., et al. (2018) · Intensive Care Medicine Experimental · doi:10.1186/s40635-018-0181-6 · Cited by 15

A Novel Method for Mendelian Randomization Analyses With Pleiotropy and Linkage Disequilibrium in Genetic Variants From Individual Data

Wang, Y., Li, T., Fu, L., Yang, S., & Hu, Y. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.634394 · Cited by 15

Genetic Overlap Analysis Identifies a Shared Etiology between Migraine and Headache with Type 2 Diabetes

Islam, M. R., & Nyholt, D. R. (2022) · Genes · doi:10.3390/genes13101845 · Cited by 17

Analysis of Mining-Related Injuries in Chinese Coal Mines and Related Risk Factors: A Statistical Research Study Based on a Meta-Analysis

Tian, J. H., Wang, Y., & Gao, S. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph192316249 · Cited by 17

A pharmacogenetic investigation of intravenous furosemide in decompensated heart failure: a meta-analysis of three clinical trials

de Denus, S., Rouleau, J. L., Mann, D. L., Huggins, G. S., Cappola, T. P., Shah, S. H., Keleti, J., Zada, Y. F., Provost, S., Bardhadi, A., et al. (2016) · The Pharmacogenomics Journal · doi:10.1038/tpj.2016.4 · Cited by 15

Increasing Association Mapping Power and Resolution in Mouse Genetic Studies Through the Use of Meta-Analysis for Structured Populations

Furlotte, N. A., Kang, E. Y., van Nas, A., Farber, C. R., Lusis, A. J., & Eskin, E. (2012) · Genetics · doi:10.1534/genetics.112.140277 · Cited by 15

Serum adiponectin levels are inversely correlated with leukemia: A meta-analysis

Ma, J., Shang, J., Wang, H., Sui, J., Liu, K., & Du, J. (2016) · Journal of Cancer Research and Therapeutics · doi:10.4103/0973-1482.186695 · Cited by 15

MetaPhat: Detecting and Decomposing Multivariate Associations From Univariate Genome-Wide Association Statistics

Lin, J., Tabassum, R., Ripatti, S., & Pirinen, M. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2020.00431 · Cited by 12

Genome-wide association study and Mendelian randomization analysis provide insights for improving rice yield potential

Su, J., Xu, K., Wu, C., 李姿蓉, Hu, Z., Zheng, X., Song, S., Tang, Z., Tang, Z., & Li, L. (2021) · Scientific Reports · doi:10.1038/s41598-021-86389-7 · Cited by 18

Impact of disease-associated chromatin accessibility QTLs across immune cell types and contexts

Mu, Z., Randolph, H. E., Aguirre‐Gamboa, R., Ketter, E., Dumaine, A., Locher, V., Brandolino, C., Liu, X., Kaufmann, D., Barreiro, L. B., et al. (2025) · Cell Genomics · doi:10.1016/j.xgen.2025.101061 · Cited by 22

Biological insights into schizophrenia from ancestrally diverse populations

Bigdeli, T. B., Chatzinakos, C., Bendl, J. M., Barr, P. B., Venkatesh, S., Gorman, B. R., Clarence, T., Genovese, G., Iyegbe, C. O., Peterson, R. E., et al. (2026) · Nature · doi:10.1038/s41586-025-10000-6 · Cited by 21

UACA locus is associated with breast cancer chemoresistance and survival

Zhu, Q., Schultz, E., Long, J., Roh, J. M., Valice, E., Laurent, C. A., Radimer, K. H., Yan, L., Ergas, I. J., Davis, W., et al. (2022) · npj Breast Cancer · doi:10.1038/s41523-022-00401-5 · Cited by 14

Genetic insights into the age-specific biological mechanisms governing human ovarian aging

Ojavee, S. E., Darrous, L., Patxot, M., Läll, K., Fischer, K., Mägi, R., Kutalik, Z., & Robinson, M. R. (2023) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2023.07.006 · Cited by 14

Atlas of genetic effects in human microglia transcriptome across brain regions, aging and disease pathologies

Lopes, K. P., Snijders, G. J. L., Humphrey, J., de Witte, L. D., & Raj, T. (2021) · Alzheimer s & Dementia · doi:10.1002/alz.050942 · Cited by 18

Myocardial Fibrosis and Cardiomyopathy Risk: A Genetic Link in the MESA

Shabani, M., Wang, M., Jenkins, G. D., Rotter, J. I., Rich, S. S., Batzler, A. J., Taylor, K. D., Mychaleckyj, J. C., Liu, D., Lima, J. A. C., et al. (2023) · Circulation Heart Failure · doi:10.1161/circheartfailure.122.010262 · Cited by 13

Reproducible microbiome composition signatures of anxiety and depressive symptoms

Kouraki, A., Kelly, A., Vijay, A., Gohir, S. A., Astbury, S., Georgopoulos, V., Millar, B., Walsh, D. A., Ferguson, E., Menni, C., et al. (2023) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2023.10.035 · Cited by 14

Analysis of gut microbiome, host genetics, and plasma metabolites reveals gut microbiome-host interactions in the Japanese population

Tomofuji, Y., Kishikawa, T., Sonehara, K., Maeda, Y., Ogawa, K., Kawabata, S., Oguro-Igashira, E., Okuno, T., Nii, T., Kinoshita, M., et al. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.113324 · Cited by 13

Shared molecular mechanisms and transdiagnostic potential of neurodevelopmental disorders and immune disorders

Xiu, Z., Sun, L., Liu, K., Cao, H., Qu, H., Glessner, J., Ding, Z., Zheng, G., Wang, N., Xia, Q., et al. (2024) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2024.04.026 · Cited by 13

Role of Sex on the Genetic Susceptibility to Childhood Asthma in Latinos and African Americans

Espuela‐Ortiz, A., Luis, E. H., Lorenzo-Díaz, F., Hu, D., Eng, C. S., Villar, J., Rodríguez‐Santana, J., Burchard, E. G., & Pino-Yanes, M. D. M. (2021) · Journal of Personalized Medicine · doi:10.3390/jpm11111140 · Cited by 13

A Genetic Map of the Modern Urban Society of Amsterdam

Ferwerda, B., Abdellaoui, A., Nieuwdorp, M., & Zwinderman, A. H. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.727269 · Cited by 13

A flexible summary statistics-based colocalization method with application to the mucin cystic fibrosis lung disease modifier locus

Wang, F., Panjwani, N., Wang, C., Sun, L., & Strug, L. J. (2022) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2021.12.012 · Cited by 11

GWAS in Africans identifies novel lipids loci and demonstrates heterogenous association within Africa

Bentley, A. R., Chen, G., Doumatey, A. P., Shriner, D., Meeks, K. A. C., Gouveia, M. H., Ekoru, K., Zhou, J., the Africa America Diabetes Mellitus Investigators, Adeyemo, A., et al. (2021) · Human Molecular Genetics · doi:10.1093/hmg/ddab174 · Cited by 12

Novel insights into the whole-blood DNA methylome of asthma in ethnically diverse children and youth

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Exploring the cross‐cancer effect of smoking and its fingerprints in blood DNA methylation on multiple cancers: A Mendelian randomization study

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Trans-ancestry meta-analysis of genome wide association studies of inhibitory control

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Robust meta‐analysis of biobank‐based genome‐wide association studies with unbalanced binary phenotypes

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Iterative hard thresholding in genome-wide association studies: Generalized linear models, prior weights, and double sparsity

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SNPs associated with colorectal cancer at 15q13.3 affect risk enhancers that modulate GREM1 gene expression

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DNA methylation signatures as biomarkers of socioeconomic position

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Association between DNA methylation and ADHD symptoms from birth to school age: A prospective meta-analysisPreprint

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Powerful detection of polygenic selection and evidence of environmental adaptation in US beef cattlePreprint

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Rates of Depression in Children and Adolescents With ADHD: A Systematic Review and Meta-Analysis

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Genome-wide association study in minority children with asthma implicates DNAH5 in bronchodilator responsiveness

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Admixture mapping of asthma in southwestern Europeans with North African ancestry influences

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Meta-Analysis of Common and Rare Variants

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Meta-Analysis of SNP-Environment Interaction with Heterogeneity

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Multi-ancestry genome-wide meta-analysis of 56,241 individuals identifies LRRC4C, LHX5-AS1 and nominates ancestry-specific loci PTPRK , GRB14 , and KIAA0825 as novel risk loci for Alzheimer’s disease: the Alzheimer’s Disease Genetics ConsortiumPreprint

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A cross-ancestry genome-wide meta-analysis, fine-mapping, and gene prioritization approach to characterize the genetic architecture of adiponectin

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A genome-wide association study for rheumatoid arthritis replicates previous HLA and non-HLA associations in a cohort from South Africa

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Common Variants on FGD5 Increase Hazard of Mortality or Rehospitalization in Patients With Heart Failure From the ASCEND-HF Trial

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Epigenomic response to albuterol treatment in asthma-relevant airway epithelial cells

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Dissecting Meta-Analysis in GWAS Era: Bayesian Framework for Gene/Subnetwork-Specific Meta-Analysis

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Gene Sequencing Identifies Perturbation in Nitric Oxide Signaling as a Nonlipid Molecular Subtype of Coronary Artery Disease

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Evaluation of a Two‐Stage Approach in Trans‐Ethnic Meta‐Analysis in Genome‐Wide Association Studies

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Multivariate meta-analysis of the association of G-protein beta 3 gene (GNB3) haplotypes with cardiovascular phenotypes

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FastGxC: Fast and Powerful Context-Specific eQTL Mapping in Bulk and Single-Cell DataPreprint

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Leveraging drug perturbation to reveal genetic regulators of hepatic gene expression in African Americans

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The prevalence of comorbid mental health difficulties in young people with chronic skin conditions: A systematic review and meta-analysis

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Genetic Architecture of Idiopathic Inflammatory Myopathies From Meta‐Analyses

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Contribution of germline and somatic mutations to risk of neuromyelitis optica spectrum disorder

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Increasing the power of meta-analysis of genome-wide association studies to detect heterogeneous effects

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A Case Study of Fixed-Effects and Random-Effects Meta-Analysis Models for Genome-Wide Association Studies in Celiac Disease

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Beta-Meta: a meta-analysis application considering heterogeneity among genome-wide association studies

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Discovery Properties of Genome-wide Association Signals From Cumulatively Combined Data Sets

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Dissecting heterogeneity in GWAS meta-analysis

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