Five Years of GWAS Discovery

PLINK: a tool set for whole-genome association and population-based linkage analyses.

Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089

Model-based Analysis of ChIP-Seq (MACS)

Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., et al. (2008) · Genome Biology · doi:10.1186/gb-2008-9-9-r137 · Cited by 18,386

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

The Wellcome Trust Case Control Consortium, Management Committee, Burton, P. R., Clayton, D. G., Cardon, L. R., Craddock, N., Deloukas, P., Duncanson, A., Kwiatkowski, D. P., McCarthy, M. I., et al. (2007) · Nature · doi:10.1038/nature05911 · Cited by 9,442

Finding the missing heritability of complex diseases

Manolio, T. A., Collins, F. S., Cox, N. J., Goldstein, D. B., Hindorff, L. A., Hunter, D. J., McCarthy, M. I., Ramos, E. M., Cardon, L. R., Chakravarti, A., et al. (2009) · Nature · doi:10.1038/nature08494 · Cited by 8,336

A map of human genome variation from population-scale sequencing.

The 1000 Genomes Project Consortium (2010) · Nature · doi:10.1038/nature09534 · Cited by 7,877

Effectiveness of Antipsychotic Drugs in Patients with Chronic Schizophrenia

Lieberman, J. A., Stroup, T. S., McEvoy, J. P., Swartz, M. S., Rosenheck, R. A., Perkins, D. O., Keefe, R. S. E., Davis, S. M., Davis, C. E., Lebowitz, B. D., et al. (2005) · New England Journal of Medicine · doi:10.1056/nejmoa051688 · Cited by 5,892

A haplotype map of the human genome

The International HapMap Consortium (2005) · Nature · doi:10.1038/nature04226 · Cited by 5,858

The Future of Genetic Studies of Complex Human Diseases

Risch, N., & Merikangas, K. (1996) · Science · doi:10.1126/science.273.5281.1516 · Cited by 5,355

Principles of Population Genetics.

Cormack, R. M., Hartl, D. L., & Clark, A. G. (1990) · Biometrics · doi:10.2307/2531471 · Cited by 5,283

Common polygenic variation contributes to risk of schizophrenia and bipolar disorder

The International Schizophrenia Consortium (2009) · Nature · doi:10.1038/nature08185 · Cited by 4,821

A Genome-Wide Screen for Large-Effect Alloimmunization Susceptibility Loci among Red Blood Cell Transfusion Recipients with Sickle Cell Disease

Hanchard, N. A., Moulds, J. M., Belmont, J. W., & Chen, A. P. (2014) · Transfusion Medicine and Hemotherapy · doi:10.1159/000369079 · Cited by 25

An epidemiological perspective of personalized medicine: the E stonian experience

Milani, L. A., Leitsalu, L., & Metspalu, A. (2014) · Journal of Internal Medicine · doi:10.1111/joim.12320 · Cited by 27

Molecularly and clinically related drugs and diseases are enriched in phenotypically similar drug-disease pairs

Vogt, I., Prinz, J., & Campillos, M. (2014) · Genome Medicine · doi:10.1186/s13073-014-0052-z · Cited by 26

Genomic Characteristics of Gender Dysphoria Patients and Identification of Rare Mutations in RYR3 Gene

Yang, F., Zhu, X.-H., Zhang, Q., Sun, N., Ji, Y., Ma, J., Xiao, B., Ding, H., Sun, S., & Li, W. (2017) · Scientific Reports · doi:10.1038/s41598-017-08655-x · Cited by 26

Impaired Reproductive Function in Equines: From Genetics to Genomics

Laseca, N., Anaya, G., Peña, Z., Pirosanto, Y., Molina, A., & Demyda-Peyrás, S. (2021) · Animals · doi:10.3390/ani11020393 · Cited by 25

Alcohol Use and the Alcohol Use Disorders Over the Life Course: A Cross‐Level Developmental Review

Zucker, R. A., Hicks, B. M., & Heitzeg, M. M. (2016) · Wiley eBooks · doi:10.1002/9781119125556.devpsy318 · Cited by 26

A multi-enhancer RET regulatory code is disrupted in Hirschsprung diseasePreprint

Chatterjee, S., Karasaki, K. M., Fries, L. E., Kapoor, A., & Chakravarti, A. (2021) · Genome Research · doi:10.1101/gr.275667.121 · Cited by 25

Genome‐wide scans of genetic variants for psychophysiological endophenotypes: A methodological overview

Iacono, W. G., Malone, S. M., Vaidyanathan, U., & Vrieze, S. I. (2014) · Psychophysiology · doi:10.1111/psyp.12343 · Cited by 25

Heritability, parental transmission and environment correlation of pediatric-onset type 2 diabetes mellitus and metabolic syndrome-related traits

Miranda‐Lora, A. L., Vilchis‐Gil, J., Molina‐Díaz, M., Flores‐Huerta, S., & Klünder‐Klünder, M. (2017) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2017.02.005 · Cited by 25

Two approaches reveal a new paradigm of ‘switchable or genetics-influenced allele-specific DNA methylation’ with potential in human disease

Martos, S. N., Teng, L., Ramos, R. B., Lou, D. W., Dai, H., Xu, J.-C., Gao, G., Gao, Y., Wang, Q., An, C., et al. (2017) · Cell Discovery · doi:10.1038/celldisc.2017.38 · Cited by 24

FORGE: A tool to discover cell specific enrichments of GWAS associated SNPs in regulatory regions

Dunham, I., Kulesha, E., Iotchkova, V., Morganella, S., & Birney, E. (2015) · F1000Research · doi:10.12688/f1000research.6032.1 · Cited by 24

The Evolving Field of Genetic Epidemiology: From Familial Aggregation to Genomic Sequencing

Duggal, P., Ladd‐Acosta, C., Ray, D., & Beaty, T. H. (2019) · American Journal of Epidemiology · doi:10.1093/aje/kwz193 · Cited by 26

Mendelian randomization analysis revealed potential causal factors for systemic lupus erythematosus

Mo, X., Guo, Y., Qian, Q., Fu, M., Lei, S., Zhang, Y., & Zhang, H. (2019) · Immunology · doi:10.1111/imm.13144 · Cited by 24

Genome-Wide Association Studies

Guo, X., & Rotter, J. I. (2019) · JAMA · doi:10.1001/jama.2019.16479 · Cited by 24

Labor Rights as Human Rights

Saner, R., & Yiu, L. S. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108348607.008 · Cited by 24

Predicting Physical Appearance from DNA Data—Towards Genomic Solutions

Pośpiech, E., Teisseyre, P., Mielniczuk, J., & Branicki, W. (2022) · Genes · doi:10.3390/genes13010121 · Cited by 25

Case-only exome sequencing and complex disease susceptibility gene discovery: study design considerations

Wu, L., Schaid, D. J., Sicotte, H., Wieben, E. D., Li, H., & Petersen, G. M. (2014) · Journal of Medical Genetics · doi:10.1136/jmedgenet-2014-102697 · Cited by 25

Biological pathways and networks implicated in psychiatric disorders

Sullivan, P. F., & Posthuma, D. (2014) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2014.09.003 · Cited by 25

The “Missing Heritability” of Psychiatric Disorders: Elusive Genes or Non-Existent Genes?

Joseph, J. (2012) · Applied Developmental Science · doi:10.1080/10888691.2012.667343 · Cited by 26

Genome-Wide Association Study of Receptive Language Ability of 12-Year-Olds

Harlaar, N., Meaburn, E. L., Hayiou‐Thomas, M. E., Davis, O. S. P., Docherty, S. J., Hanscombe, K. B., Haworth, C. M. A., Price, T. S., Trzaskowski, M., Dale, P. S., et al. (2014) · Journal of Speech Language and Hearing Research · doi:10.1044/1092-4388(2013/12-0303 · Cited by 24

Genetic strategies for probing conscientiousness and its relationship to aging.

South, S. C., & Krueger, R. F. (2012) · Developmental Psychology · doi:10.1037/a0030725 · Cited by 26

Genetics of Adverse Reactions to Haloperidol in a Mouse Diallel: A Drug–Placebo Experiment and Bayesian Causal Analysis

Crowley, J. J., Kim, Y., Lenarcic, A., Quackenbush, C. R., Barrick, C. J., Adkins, D. E., Shaw, G. S., Miller, D. R., de Villena, F. P., Sullivan, P. F., et al. (2013) · Genetics · doi:10.1534/genetics.113.156901 · Cited by 24

Transcriptomic Segregation of Human Autoantigens Useful for the Diagnosis of Autoimmune Diseases

Burbelo, P. D., Iadarola, M. J., Alevizos, I., & Sapio, M. R. (2016) · Molecular Diagnosis & Therapy · doi:10.1007/s40291-016-0211-6 · Cited by 24

Catfish genomic studies: progress and perspectives

Jin, Y., Liu, S., Yuan, Z., Yang, Y., Tan, S., & Liu, Z. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-801418-9.00004-4 · Cited by 24

A method to customize population-specific arrays for genome-wide association testing

Ehli, E. A., Abdellaoui, A., Fedko, I. O., Grieser, C., Nohzadeh‐Malakshah, S., Willemsen, G. A. H. M., de Geus, E. J. C., Boomsma, D. I., Davies, G. E., & Hottenga, J. (2016) · European Journal of Human Genetics · doi:10.1038/ejhg.2016.152 · Cited by 25

Genome-wide approaches to understanding and improving complex traits in aquaculture species.

Palaiokostas, C., & Houston, R. D. (2018) · CABI Reviews · doi:10.1079/pavsnnr201712055 · Cited by 24

Quantifying gene selection in cancer through protein functional alteration bias

Brandes, N., Linial, N., & Linial, M. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz546 · Cited by 26

The rs4759314 SNP within Hotair lncRNA is associated with risk of multiple sclerosis

Taheri, M. N., Noroozi, R., Sadeghpour, S., Omrani, M. D., & Ghafouri‐Fard, S. (2020) · Multiple Sclerosis and Related Disorders · doi:10.1016/j.msard.2020.101986 · Cited by 24

Transcriptome prediction performance across machine learning models and diverse ancestries

Okoro, P. C., Schubert, R., Guo, X., Johnson, W. C., Rotter, J. I., Hoeschele, I., Liu, Y., Im, H. K., Luke, A. H., Dugas, L. R., et al. (2021) · Human Genetics and Genomics Advances · doi:10.1016/j.xhgg.2020.100019 · Cited by 24

ATHENA: A TOOL FOR META-DIMENSIONAL ANALYSIS APPLIED TO GENOTYPES AND GENE EXPRESSION DATA TO PREDICT HDL CHOLESTEROL LEVELS

Holzinger, E. R., DUDEK, S. M., Frase, A., Krauss, R. M., Medina, M. W., & Ritchie, M. D. (2012) · Pacific Symposium on Biocomputing (PSB) · doi:10.1142/9789814447973_0038 · Cited by 24

Homogeneous case subgroups increase power in genetic association studies

Traylor, M., Markus, H. S., & Lewis, C. M. (2014) · European Journal of Human Genetics · doi:10.1038/ejhg.2014.194 · Cited by 24

Unraveling Genetic Origin of Aging-Related Traits: Evolving Concepts

Kulminski, A. M. (2013) · Rejuvenation Research · doi:10.1089/rej.2013.1441 · Cited by 23

Two-Variance-Component Model Improves Genetic Prediction in Family Datasets

Tucker, G., Loh, P., MacLeod, I. M., Hayes, B. J., Goddard, M. E., Berger, B., & Price, A. L. (2015) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.10.002 · Cited by 23

Exome Sequence Analysis of 14 Families With High Myopia

Kloss, B. A. V., Tompson, S. W. J., Whisenhunt, K. N., Quow, K., Huang, S. J., Pavelec, D. M., Rosenberg, T., & Young, T. L. (2017) · Investigative Ophthalmology & Visual Science · doi:10.1167/iovs.16-20883 · Cited by 23

Genome-wide association studies reveals polygenic genetic architecture of litter traits in Duroc pigs

Ding, R., Qiu, Y., Zhuang, Z., Ruan, D., Wu, J., Zhou, S., Ye, J., Cao, L., Hong, L., Xu, Z. Q., et al. (2021) · Theriogenology · doi:10.1016/j.theriogenology.2021.08.012 · Cited by 25

Cold-Blooded and on Purpose: A Review of the Biology of Proactive Aggression

Belfry, K. D., & Kolla, N. J. (2021) · Brain Sciences · doi:10.3390/brainsci11111412 · Cited by 25

Making sense of OMICS data in population‐based environmental health studies

Kyrtopoulos, S. Α. (2013) · Environmental and Molecular Mutagenesis · doi:10.1002/em.21778 · Cited by 23

Immunogenetics of human echinococcosis

Yang, Y. R., Ellis, M. K., & McManus, D. P. (2012) · Trends in Parasitology · doi:10.1016/j.pt.2012.08.001 · Cited by 23

Mechanistic and topological explanations in medicine: the case of medical genetics and network medicine

Darrason, M. (2015) · Synthese · doi:10.1007/s11229-015-0983-y · Cited by 27

The FER rs4957796 TT genotype is associated with unfavorable 90-day survival in Caucasian patients with severe ARDS due to pneumonia

Hinz, J. M., Büttner, B., Kriesel, F., Steinau, M., Popov, A., Ghadimi, M. B., Beißbarth, T., Tzvetkov, M. V., Bergmann, I., & Mansur, A. (2017) · Scientific Reports · doi:10.1038/s41598-017-08540-7 · Cited by 23

Fusion pore in exocytosis: More than an exit gate? A β-cell perspective

Hastoy, B., Clark, A., Rorsman, P., & Lang, J. (2017) · Cell Calcium · doi:10.1016/j.ceca.2017.10.005 · Cited by 25

Functional Validation of Candidate Genes Detected by Genomic Feature Models

Rohde, P. D., Østergaard, S., Kristensen, T. N., Sørensen, P., Loeschcke, V., Mackay, T. F. C., & Sarup, P. M. (2018) · G3 Genes Genomes Genetics · doi:10.1534/g3.118.200082 · Cited by 24

Accounting for Population Structure and Phenotypes From Relatives in Association Mapping for Farm Animals: A Simulation Study

Mancin, E., Lourenco, D. A. L., Bermann, M., Mantovani, R., & Misztal, I. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.642065 · Cited by 23

Interpretable artificial neural networks incorporating Bayesian alphabet models for genome-wide prediction and association studies

Zhao, T., Fernando, R. L., & Cheng, H. (2021) · G3 Genes Genomes Genetics · doi:10.1093/g3journal/jkab228 · Cited by 24

The Impact of Improved Microarray Coverage and Larger Sample Sizes on Future Genome‐Wide Association Studies

Lindquist, K. J., Jorgenson, E., Hoffmann, T. J., & Witte, J. S. (2013) · Genetic Epidemiology · doi:10.1002/gepi.21724 · Cited by 23

Detection and interpretation of shared genetic influences on 40 human traitsPreprint

Pickrell, J. K., Berisa, T., Ségurel, L., Tung, J. Y., & Hinds, D. A. (2015) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/019885 · Cited by 24

Evolutionary Physiology and Genomics in the Highly Adaptable Killifish ( Fundulus heteroclitus )

Crawford, D. L., Schulte, P. M., Whitehead, A., & Oleksiak, M. F. (2020) · Comprehensive physiology · doi:10.1002/cphy.c190004 · Cited by 23

Genome-wide fine-mapping improves identification of causal variants

Wu, Y., Zheng, Z., Thibaut, L., Lin, T., Feng, Q., Cheng, H., Yengo, L., Goddard, M. E., Wray, N. R., Visscher, P. M., et al. (2026) · Nature Genetics · doi:10.1038/s41588-026-02549-3 · Cited by 23

Genetic Approaches to the Study of Gene Variants and Their Impact on the Pathophysiology of Type 2 Diabetes

Szabó, M. I., Máté, B., Csép, K., & Benedek, T. (2017) · Biochemical Genetics · doi:10.1007/s10528-017-9827-4 · Cited by 23

Integration of Mendelian randomisation and systems biology models to identify novel blood-based biomarkers for stroke

Islam, T., Rahman, M. R., Khan, A., & Moni, M. A. (2023) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2023.104345 · Cited by 22

Transcriptomic and epigenomic landscapes of muscle growth during the postnatal period of broilers

Gu, S., Huang, Q., Jie, Y., Sun, C., Wen, C., & Yang, N. (2024) · Journal of Animal Science and Biotechnology/Journal of animal science and biotechnology · doi:10.1186/s40104-024-01049-w · Cited by 22

Impact of New Genomic Technologies on Understanding Adverse Drug Reactions

Maggo, S. D. S., Savage, R. L., & Kennedy, M. A. (2015) · Clinical Pharmacokinetics · doi:10.1007/s40262-015-0324-9 · Cited by 23

Characterization of Expression Quantitative Trait Loci in the Human Colon

Singh, T., Levine, A. P., Smith, P. J., Smith, A. M., Segal, A. W., & Barrett, J. C. (2015) · Inflammatory Bowel Diseases · doi:10.1097/mib.0000000000000265 · Cited by 23

Massively Parallel Genetics

Shendure, J., & Fields, S. (2016) · Genetics · doi:10.1534/genetics.115.180562 · Cited by 22

A Single Nucleotide Polymorphism in the Il17ra Promoter Is Associated with Functional Severity of Ankylosing Spondylitis

Vidal-Castiñeira, J. R., López‐Vázquez, A., Díaz‐Peña, R., Díaz-Bulnes, P., Martínez‐Camblor, P., Coto, E., Coto‐Segura, P., Bruges‐Armas, J., Pinto, J., Blanco, F. J., et al. (2016) · PLoS ONE · doi:10.1371/journal.pone.0158905 · Cited by 22

Trans-ancestry Fine Mapping and Molecular Assays Identify Regulatory Variants at the ANGPTL8 HDL-C GWAS Locus

Cannon, M. E., Duan, Q., Wu, Y., Zeynalzadeh, M., Xu, Z. Q., Kangas, A. J., Soininen, P., Ala‐Korpela, M., Civelek, M., Lusis, A. J., et al. (2017) · G3 Genes Genomes Genetics · doi:10.1534/g3.117.300088 · Cited by 22

Identification of potential gene‐associated major traits using GBS ‐ GWAS for Korean apple germplasm collections

Lee, S. J., Ban, S. H., Kim, G. H., Kwon, S. I., Kim, J. H., & Choi, C. W. (2017) · Plant Breeding · doi:10.1111/pbr.12544 · Cited by 22

Parenting Interacts with Oxytocin Polymorphisms to Predict Adolescent Social Anxiety Symptom Development: A Novel Polygenic Approach

Nelemans, S. A., Assche, E. V., Bijttebier, P., Colpin, H., Leeuwen, K. G. V., Verschueren, K., Claes, S. J., Noortgate, W. V. D., & Goossens, L. (2018) · Research on Child and Adolescent Psychopathology · doi:10.1007/s10802-018-0432-8 · Cited by 22

Nighttime snacking is associated with risk of obesity and hyperglycemia in adults: a cross-sectional survey from Chinese adult teachers

Xiaoyang, L., Zheng, C., Xu, C., Liu, Q., Wang, J., Hong, Y., & Zhao, P. (2017) · Journal of Biomedical Research · doi:10.7555/jbr.31.20160083 · Cited by 22

What Can the Study of Genetics Offer to Educators?

Thomas, M. S. C., Kovas, Y. V., Meaburn, E. L., & Tolmie, A. K. (2015) · Mind Brain and Education · doi:10.1111/mbe.12077 · Cited by 23

Expression quantitative trait analyses to identify causal genetic variants for type 2 diabetes susceptibility

Das, S. K., & Sharma, N. (2014) · World Journal of Diabetes · doi:10.4239/wjd.v5.i2.97 · Cited by 22

Deep Learning Framework for Complex Disease Risk Prediction Using Genomic Variations

Alzoubi, H., Alzubi, R., & Ramzan, N. (2023) · Sensors · doi:10.3390/s23094439 · Cited by 21

A genome-wide association study and genomic prediction for Phakopsora pachyrhizi resistance in soybean

Xiong, H., Chen, Y., Pan, Y., Wang, J., Lu, W., & Shi, A. (2023) · Frontiers in Plant Science · doi:10.3389/fpls.2023.1179357 · Cited by 21

Causal effects of specific gut microbiota on musculoskeletal diseases: a bidirectional two-sample Mendelian randomization study

Chen, D., Han, H., Sun, X., Zhou, G., Zhou, Q., & Li, Z. (2023) · Frontiers in Microbiology · doi:10.3389/fmicb.2023.1238800 · Cited by 21

Structural variants and short tandem repeats impact gene expression and splicing in bovine testis tissue

Bhati, M., Mapel, X. M., Lloret‐Villas, A., & Pausch, H. (2023) · Genetics · doi:10.1093/genetics/iyad161 · Cited by 21

mtPGS: Leverage multiple correlated traits for accurate polygenic score construction

Xu, C., Ganesh, S. K., & Zhou, X. (2023) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2023.08.016 · Cited by 21

Population Genetics Identifies Challenges in Analyzing Rare Variants

Johnston, H. R., Hu, Y., & Cutler, D. J. (2015) · Genetic Epidemiology · doi:10.1002/gepi.21881 · Cited by 22

Functional Logistic Regression Approach to Detecting Gene by Longitudinal Environmental Exposure Interaction in a Case‐Control Study

Wei, P., Tang, H., & Li, D. (2014) · Genetic Epidemiology · doi:10.1002/gepi.21852 · Cited by 21

Transmission of Metabolic Dysfunction Across Generations

Jaeger, K., Saben, J. L., & Moley, K. H. (2016) · Physiology · doi:10.1152/physiol.00017.2016 · Cited by 21

Multivariate analysis of genome-wide data to identify potential pleiotropic genes for type 2 diabetes, obesity and coronary artery disease using MetaCCA

Jia, X., Yang, Y., Chen, Y., Xia, Z., Zhang, W., Feng, Y. Y., Li, Y., Tan, J., Xu, C., Zhang, Q., et al. (2018) · International Journal of Cardiology · doi:10.1016/j.ijcard.2018.10.102 · Cited by 21

EnDisease: a manually curated database for enhancer-disease associations

Zeng, W., Xu, M., & Jiang, R. (2019) · Database · doi:10.1093/database/baz020 · Cited by 21

Signals Among Signals: Prioritizing Nongenetic Associations in Massive Data Sets

Manrai, A. K., Ioannidis, J. P. A., & Patel, C. J. (2019) · American Journal of Epidemiology · doi:10.1093/aje/kwz031 · Cited by 21

Genetic Susceptibility, Dietary Protein Intake, and Changes of Blood Pressure

Sun, D., Zhou, T., Li, X., Heianza, Y., Liang, Z., Bray, G. A., Sacks, F. M., & Qi, L. (2019) · Hypertension · doi:10.1161/hypertensionaha.119.13510 · Cited by 21

Applying computation biology and “big data” to develop multiplex diagnostics for complex chronic diseases such as osteoarthritis

Ren, G., & Krawetz, R. J. (2015) · Biomarkers · doi:10.3109/1354750x.2015.1105499 · Cited by 22

Genetic and Environmental Stability of Intelligence in Childhood and Adolescence

Franić, S., Dolan, C. V., van Beijsterveldt, C. E. M., Pol, H. E. H., Bartels, M., & Boomsma, D. I. (2014) · Twin Research and Human Genetics · doi:10.1017/thg.2014.26 · Cited by 22

‘Omics’ biomarkers associated with chronic low back pain: protocol of a retrospective longitudinal study

Allegri, M., Gregori, M. D., Minella, C. E., Klersy, C., Wang, W., Sim, M., Gieger, C., Manz, J., Pemberton, I. K., MacDougall, J., et al. (2016) · BMJ Open · doi:10.1136/bmjopen-2016-012070 · Cited by 21

The Adolescent Origins of Substance Use Disorders: A Behavioral Genetic Perspective

McGue, M. K., Irons, D. E., & Iacono, W. G. (2014) · Nebraska Symposium on Motivation/The Nebraska symposium on motivation · doi:10.1007/978-1-4939-0653-6_3 · Cited by 22

GWAS implicates a role for quantitative immune traits and threshold effects in risk for human autoimmune disorders

Gregersen, P. K., Diamond, B., & Plenge, R. M. (2012) · Current Opinion in Immunology · doi:10.1016/j.coi.2012.09.003 · Cited by 20

Obesity-associated family with sequence similarity 13, member A (FAM13A) is dispensable for adipose development and insulin sensitivity

Tang, J., Zhou, H., Sahay, K., Xu, W., Yang, J., Zhang, W., & Chen, W. (2018) · International Journal of Obesity · doi:10.1038/s41366-018-0222-y · Cited by 20

Maternal Metabolic Health, Lifestyle, and Environment—Understanding How Epigenetics Drives Future Offspring Health

Schwartz, S. S., & Amrom, D. (2023) · Current Diabetes Reviews · doi:10.2174/1573399818666220422085016 · Cited by 20

Genome-Wide Association Study and Genomic Prediction for Bacterial Wilt Resistance in Common Bean (Phaseolus vulgaris) Core Collection

Zia, B., Shi, A., Olaoye, D., Xiong, H., Ravelombola, W., Gepts, P., Schwartz, H. F., Brick, M. A., Otto, K., Ogg, B., et al. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.853114 · Cited by 20

Gene-environment interaction explains a part of missing heritability in human body mass index

Jung, H., Kim, D. J., Baek, E. J., Chung, J. Y., Ha, T. W., Kim, H.-K., Kang, J., Lim, J. E., & Oh, B. (2023) · Communications Biology · doi:10.1038/s42003-023-04679-4 · Cited by 20

Benchmarking of local genetic correlation estimation methods using summary statistics from genome-wide association studies

Zhang, C., Zhang, Y., Zhang, Y., & Zhao, H. (2023) · Briefings in Bioinformatics · doi:10.1093/bib/bbad407 · Cited by 22

Group-based variant calling leveraging next-generation supercomputing for large-scale whole-genome sequencing studies

Standish, K. A., Carland, T. M., Lockwood, G. K., Pfeiffer, W., Tatineni, M., Huang, C. C., Lamberth, S. L., Cherkas, Y., Brodmerkel, C. M., Jaeger, E., et al. (2015) · BMC Bioinformatics · doi:10.1186/s12859-015-0736-4 · Cited by 20

Genome wide association studies (GWAS) and common forms of human epilepsy

Buono, R. J. (2013) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2012.07.006 · Cited by 20

Imaging genetics — towards discovery neuroscience

Ge, T., Schumann, G., & Feng, J. (2013) · Quantitative Biology · doi:10.1007/s40484-013-0023-1 · Cited by 21

Genomics and personalised whole-of-life healthcare

Bauer, D. C., Gaff, C., Dinger, M. E., Caramins, M. C., Buske, F. A., Fenech, M. F., Hansen, D. T., & Cobiac, L. (2014) · Trends in Molecular Medicine · doi:10.1016/j.molmed.2014.04.001 · Cited by 20

Translating Genomic Advances to Physical Therapist Practice: A Closer Look at the Nature and Nurture of Common Diseases

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