Personal genomes: The case of the missing heritability

Transposable elements: targets for early nutritional effects on epigenetic gene regulation

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Large recurrent microdeletions associated with schizophrenia.

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Rare chromosomal deletions and duplications increase risk of schizophrenia

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Genetic Dissection of Transcriptional Regulation in Budding Yeast

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Genome-wide association analysis identifies 20 loci that influence adult height

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Many sequence variants affecting diversity of adult human height

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The genetics of autistic disorders and its clinical relevance: a review of the literature

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Identification of ten loci associated with height highlights new biological pathways in human growth

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Population-based resequencing of ANGPTL4 uncovers variations that reduce triglycerides and increase HDL

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Sizing up human height variation

Visscher, P. M. (2008) · Nature Genetics · doi:10.1038/ng0508-489 · Cited by 474

Conference Scene: The Great Debate: Genome-Wide Association Studies in Pharmacogenetics Research, Good or Bad?

Bailey, K. R., & Cheng, C. (2010) · Pharmacogenomics · doi:10.2217/pgs.10.6 · Cited by 17

Correction: Heritability and Genetic Correlations Explained by Common SNPs for Metabolic Syndrome Traits

Vattikuti, S., Guo, J., & Chow, C. C. (2012) · PLoS Genetics · doi:10.1371/annotation/61bb5924-6688-4ee5-a37f-d48aa09ad66a · Cited by 17

Multiple Germline Events Contribute to Cancer Development in Patients with Li-Fraumeni Syndrome

Subasri, V., Light, N. D., Kanwar, N., Brzezinski, J. J., Luo, P., Hansford, J. R., Cairney, E., Portwine, C., Elser, C., Finlay, J. L., et al. (2023) · Cancer Research Communications · doi:10.1158/2767-9764.crc-22-0402 · Cited by 16

Insatiable insecurity: maternal obesity as a risk factor for mother–child attachment and child weight

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Pathway-Based Genome-Wide Association Studies for Plasma Triglycerides in Obese Females and Normal-Weight Controls

Jiao, H., Wang, K., Yang, F., Grant, S. F. A., Hakonarson, H. H., Price, R. A., & Li, W. (2015) · PLoS ONE · doi:10.1371/journal.pone.0134923 · Cited by 18

Serotonin transporter promoter region (5‐HTTLPR) polymorphism predicts resting respiratory sinus arrhythmia

Ellis, A. J., Beevers, C. G., Hixon, J. G., & McGeary, J. E. (2010) · Psychophysiology · doi:10.1111/j.1469-8986.2010.01154.x · Cited by 16

An Improved Version of Logistic Bayesian LASSO for Detecting Rare Haplotype-Environment Interactions with Application to Lung Cancer

Zhang, Y., & Biswas, S. (2015) · Cancer Informatics · doi:10.4137/cin.s17290 · Cited by 16

Human Complex Trait Genetics: Lifting the Lid of the Genomics Toolbox - from Pathways to Prediction

Rowe, S. J., & Tenesa, A. (2012) · Current Genomics · doi:10.2174/138920212800543101 · Cited by 19

How intelligence changes with age

Plomin, R. J. (2012) · Nature · doi:10.1038/482165a · Cited by 16

Utilizing Population Controls in Rare-Variant Case-Parent Association Tests

Jiang, Y., Satten, G. A., Han, Y., Epstein, M. P., Heinzen, E. L., Goldstein, D. B., & Allen, A. S. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.04.014 · Cited by 16

A Likelihood Ratio‐Based Mann‐Whitney Approach Finds Novel Replicable Joint Gene Action for Type 2 Diabetes

Lu, Q. L., Wei, C., Ye, C., Li, M., & Elston, R. C. (2012) · Genetic Epidemiology · doi:10.1002/gepi.21651 · Cited by 16

Local True Discovery Rate Weighted Polygenic Scores Using GWAS Summary Data

Mak, T. S. H., Kwan, J. S. H., Campbell, D., & Sham, P. C. (2016) · Behavior Genetics · doi:10.1007/s10519-015-9770-2 · Cited by 16

Non-linear interactions between candidate genes of myocardial infarction revealed in mRNA expression profiles

Hartmann, K., Seweryn, M. T., Handleman, S., Rempała, G. A., & Sadée, W. (2016) · BMC Genomics · doi:10.1186/s12864-016-3075-6 · Cited by 16

Gene-gene Interaction Analyses for Atrial Fibrillation

Lin, H., Müller‐Nurasyid, M., Smith, A. V., Arking, D. E., Barnard, J., Bartz, T. M., Lunetta, K. L., Lohman, K., Kleber, M. E., Lubitz, S. A., et al. (2016) · Scientific Reports · doi:10.1038/srep35371 · Cited by 17

An accurate and powerful method for copy number variation detection

Xiao, F., Luo, X., Hao, N., Niu, Y., Xiao, X., Cai, G., Amos, C. I., & Heping Zhang, D. (2019) · Bioinformatics · doi:10.1093/bioinformatics/bty1041 · Cited by 16

‘There and Back Again’—Forward Genetics and Reverse Phenotyping in Pulmonary Arterial Hypertension

Swietlik, E. M., Prapa, M., Martin, J. M., Pandya, D., Auckland, K., Morrell, N. W., & Gräf, S. (2020) · Genes · doi:10.3390/genes11121408 · Cited by 15

The honey bee genome-- what has it been good for?

Toth, A. L., & Zayed, A. (2021) · Apidologie · doi:10.1007/s13592-020-00829-3 · Cited by 18

Half a century later and we're back where we started: How the problem of locality turned in to the problem of portability

Matthews, L. J. (2021) · Studies in History and Philosophy of Science Part A · doi:10.1016/j.shpsa.2021.10.021 · Cited by 16

Complex genetics of pulmonary diseases: lessons from genome-wide association studies and next-generation sequencing

Pouladi, N., Bime, C., Garcia, J. G. N., & Lussier, Y. A. (2015) · Translational research · doi:10.1016/j.trsl.2015.04.016 · Cited by 17

Effectiveness of Shrinkage and Variable Selection Methods for the Prediction of Complex Human Traits using Data from Distantly Related Individuals

Berger, S., Pérez‐Rodríguez, P., Veturi, Y., Simianer, H., & Campos, G. D. L. (2015) · Annals of Human Genetics · doi:10.1111/ahg.12099 · Cited by 16

Paramutation in evolution, population genetics and breeding

Springer, N. M., & McGinnis, K. M. (2015) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2015.08.010 · Cited by 16

From Markers to Molecular Mechanisms: Type 1 Diabetes in the Post-GWAS Era

Baxter, A. G., & Jordan, M. A. (2012) · The Review of Diabetic Studies · doi:10.1900/rds.2012.9.201 · Cited by 16

Genotype by Environment Interactions in Cognitive Ability: A Survey of 14 Studies from Four Countries Covering Four Age Groups

Molenaar, D., van der Sluis, S., Boomsma, D. I., Haworth, C. M. A., Hewitt, J. K., Martin, N. G., Plomin, R. J., Wright, M. J., & Dolan, C. V. (2013) · Behavior Genetics · doi:10.1007/s10519-012-9581-7 · Cited by 15

IndOR: a new statistical procedure to test for SNP–SNP epistasis in genome‐wide association studies

Emily, M. (2012) · Statistics in Medicine · doi:10.1002/sim.5364 · Cited by 19

Cognitive Profiling Useful for Unraveling Cross-Disorder Mechanisms

Rommelse, N. N. J., van der Meer, J. M. J., Hartman, C. A., & Buitelaar, J. K. (2016) · Clinical Psychological Science · doi:10.1177/2167702616638826 · Cited by 18

Detection of common single nucleotide polymorphisms synthesizing quantitative trait association of rarer causal variantsPreprint

Fumihiko, T., 小林, 祥., Toshio, O., Akihiro, F., & Norihiro, K. (2011) · Genome Research · doi:10.1101/gr.115832.110 · Cited by 15

Rare copy number variation in extremely impulsively violent males

Vevera, J., Zarrei, M., Hartmannová, H., Jedličková, I., Mušálková, D., Přistoupilová, A., Oliveriusová, P., Trešlová, H., Nosková, L., Hodaňová, K., et al. (2019) · Genes, Brain and Behavior · doi:10.1111/gbb.12536 · Cited by 15

A new efficient method to detect genetic interactions for lung cancer GWAS

Luyapan, J., Ji, X., Li, S., Xiao, X., Zhu, D. K., Duell, E. J., Christiani, D. C., Schabath, M. B., Arnold, S. M., Zienolddiny, S., et al. (2020) · BMC Medical Genomics · doi:10.1186/s12920-020-00807-9 · Cited by 15

From Genotype to Phenotype: Polygenic Prediction of Complex Human Traits

Raben, T. G., Lello, L., Widén, E., & Hsu, S. (2022) · Methods in molecular biology · doi:10.1007/978-1-0716-2205-6_15 · Cited by 14

Personality, anxiety, and cognitive failures as predictors of flow proneness

Kranjčev, M., & Hlupić, T. V. (2021) · Personality and Individual Differences · doi:10.1016/j.paid.2021.110888 · Cited by 15

Maternal obesity increases hypothalamic miR-505-5p expression in mouse offspring leading to altered fatty acid sensing and increased intake of high-fat food

Dearden, L., Furigo, I. C., Pantaleão, L. C., Wong, L. W. P., Fernandez‐Twinn, D. S., de Almeida-Faria, J., Kentistou, K. A., Carreira, M. V., Bidault, G., Vidal‐Puig, A., et al. (2024) · PLoS Biology · doi:10.1371/journal.pbio.3002641 · Cited by 18

Hybrid CPU/GPU Acceleration of Detection of 2-SNP Epistatic Interactions in GWAS

González‐Domínguez, J., Schmidt, B., Kässens, J. C., & Wienbrandt, L. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-09873-9_57 · Cited by 15

The Missing Heritability Paradigm: A Dramatic Resurgence of the GIGO Syndrome in Genetics

Génin, E., & Clerget‐Darpoux, F. (2015) · Human Heredity · doi:10.1159/000370327 · Cited by 19

Genotype calling from next-generation sequencing data using haplotype information of reads

Zhi, D., Wu, J., Liu, N., & Zhang, K. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts047 · Cited by 15

EPIQ—efficient detection of SNP–SNP epistatic interactions for quantitative traits

Arkin, Y., Rahmani, E., Kleber, M. E., Laaksonen, R., März, W., & Halperin, E. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu261 · Cited by 15

Cognition in Middle Adulthood

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Finding the missing heritability of complex

Manolio, 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) · Cited by 15

A Comparative Study of Five Association Tests Based on CpG Set for Epigenome-Wide Association Studies

Zhang, Q., Zhao, Y., Zhang, R., Wei, Y., Yi, H., Shao, F., & Chen, F. (2016) · PLoS ONE · doi:10.1371/journal.pone.0156895 · Cited by 15

An Improved Ant Colony Optimization Algorithm for the Detection of SNP-SNP Interactions

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A genome wide association study identifies new genes potentially associated with eyelid sagging

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Eating behaviour in contrasting adiposity phenotypes: Monogenic obesity and congenital generalized lipodystrophy

Santos, J. L., & Cortés, V. (2020) · Obesity Reviews · doi:10.1111/obr.13114 · Cited by 19

Bayesian Variable Selection in Searching for Additive and Dominant Effects in Genome-Wide Data

Peltola, T., Marttinen, P., Jula, A. M., Salomaa, V. V., Perola, M., & Vehtari, A. (2012) · PLoS ONE · doi:10.1371/journal.pone.0029115 · Cited by 15

Novel genes for QTc interval. How much heritability is explained, and how much is left to find?

Jamshidi, Y., Nolte, I. M., Spector, T. D., & Snieder, H. (2010) · Genome Medicine · doi:10.1186/gm156 · Cited by 15

Pathway-Wide Association Study Implicates Multiple Sterol Transport and Metabolism Genes in HDL Cholesterol Regulation

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Biological Knowledge-Driven Analysis of Epistasis in Human GWAS with Application to Lipid Traits

Ma, L., Keinan, A., & Clark, A. G. (2014) · Methods in molecular biology · doi:10.1007/978-1-4939-2155-3_3 · Cited by 15

SIPSO: Selectively Informed Particle Swarm Optimization Based on Mutual Information to Determine SNP-SNP Interactions

Zhang, W., Shang, J., Li, H., Sun, Y., & Liu, J. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-42291-6_11 · Cited by 15

Evaluating Rare Variants in Complex Disorders Using Next-Generation Sequencing

Ezewudo, M. N., & Zwick, M. E. (2013) · Current Psychiatry Reports · doi:10.1007/s11920-013-0349-4 · Cited by 16

Whole-Genome Sequencing in Pharmacogenetics

Urban, T. J. (2013) · Pharmacogenomics · doi:10.2217/pgs.12.211 · Cited by 15

Genome‐Wide Association Studies in Asthma

Portelli, M. A., & Sayers, I. (2016) · Encyclopedia of Life Sciences · doi:10.1002/9780470015902.a0024639 · Cited by 15

Network approaches to the genetic dissection of phenotypes in animals and humans

Lee, I. (2013) · Animal Cells and Systems · doi:10.1080/19768354.2013.789076 · Cited by 14

GWAS Characterization of the Genetic Regions Associated with Nine Important Agronomic Traits in Tomato (Solanum lycopersicum L.)

Liu, Z., Jiang, J., & Li, J. (2023) · Agronomy · doi:10.3390/agronomy13051191 · Cited by 14

Genome-Wide Interaction Study Identifies RCBTB1 as a Modifier for Smoking Effect on Carotid Intima-Media Thickness

Wang, L., Rundek, T., Beecham, A. H., Hudson, B. I., Blanton, S. H., Zhao, H., Sacco, R. L., & Dong, C. (2013) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.113.302706 · Cited by 14

The New Perspectives on Genetic Studies of Type 2 Diabetes and Thyroid Diseases

Xu, M., Bi, Y., Cui, B., Hong, J., Wang, W., & Ning, G. (2013) · Current Genomics · doi:10.2174/138920213804999138 · Cited by 14

Common Variants in SLC17A3 Gene Affect Intra-personal Variation in Serum Uric Acid Levels in Longitudinal Time Series

Polašek, O., Jerončić, I., Mulić, R., Klišmanić, Z., Pehlić, M., Zemunik, T., & Kolčić, I. (2010) · Croatian Medical Journal · doi:10.3325/cmj.2010.51.32 · Cited by 14

U-statistics in genetic association studies

Li, H. (2012) · Human Genetics · doi:10.1007/s00439-012-1178-y · Cited by 14

Utilising Family‐Based Designs for Detecting Rare Variant Disease Associations

Preston, M. D., & Dudbridge, F. (2014) · Annals of Human Genetics · doi:10.1111/ahg.12051 · Cited by 14

The hidden cost of moving up: Type 2 diabetes and the escape from persistent poverty in the American South

Steckel, R. H. (2013) · American Journal of Human Biology · doi:10.1002/ajhb.22399 · Cited by 14

Genetic origin of the relationship between parental negativity and behavior problems from early childhood to adolescence: A longitudinal genetically sensitive study

Alemany, S., Rijsdijk, F. V., Haworth, C. M. A., Fañanás, L., & Plomin, R. J. (2013) · Development and Psychopathology · doi:10.1017/s0954579412001198 · Cited by 14

Phenotypic Evolution With and Beyond Genome Evolution

Félix, M. (2016) · Current topics in developmental biology/Current Topics in Developmental Biology · doi:10.1016/bs.ctdb.2016.04.002 · Cited by 15

Viewing Education Policy through a Genetic Lens

Asbury, K., & Wai, J. (2019) · Journal of School Choice · doi:10.1080/15582159.2019.1705008 · Cited by 16

Translational relevance of forward genetic screens in animal models for the study of psychiatric disease

Sheardown, E., Mech, A. M., Petrazzini, M. E. M., Leggieri, A., Gidziela, A., Hosseinian, S., Sealy, I. M., Torres-Pérez, J. V., Busch‐Nentwich, E. M., Malanchini, M., et al. (2022) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2022.104559 · Cited by 13

Comparing BeadChip and WGS Genotyping: Non-Technical Failed Calling Is Attributable to Additional Variation within the Probe Target Sequence

Gershoni, M., Shirak, A., Raz, R., & Seroussi, E. (2022) · Genes · doi:10.3390/genes13030485 · Cited by 14

A statistical boosting framework for polygenic risk scores based on large-scale genotype data

Klinkhammer, H., Staerk, C., Maj, C., Krawitz, P. M., & Mayr, A. J. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2022.1076440 · Cited by 16

Candidate Gene and Genome-Wide Association Studies in Behavioral Medicine

Nolte, I. M., McCaffery, J. M., & Snieder, H. (2010) · Springer eBooks · doi:10.1007/978-0-387-09488-5_29 · Cited by 14

On the genetics of sleep disorders: genome-wide association studies and beyond

Parsons, M. (2015) · Advances in Genomics and Genetics · doi:10.2147/agg.s57139 · Cited by 14

Using GWAS Data to Identify Copy Number Variants Contributing to Common Complex Diseases

Zöllner, S., & Teslovich, T. M. (2009) · Statistical Science · doi:10.1214/09-sts304 · Cited by 14

Feature co-localization landscape of the human genome

Ng, S.-K., Hu, T., Long, X., Chan, C.-H., Tsang, S., & Xue, H. (2016) · Scientific Reports · doi:10.1038/srep20650 · Cited by 14

Rare Variants Association Analysis in Large-Scale Sequencing Studies at the Single Locus Level

Jeng, X. J., Daye, Z. J., Lu, W., & Tzeng, J. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004993 · Cited by 14

Genomic breeding value evaluation for economically important traits of Japanese Black cattle.

Watanabe, T. (2016) · The Journal of Animal Genetics · doi:10.5924/abgri.44.3 · Cited by 14

Best Prediction of the Additive Genomic Variance in Random-Effects Models

Schreck, N., Piepho, H., & Schlather, M. (2019) · Genetics · doi:10.1534/genetics.119.302324 · Cited by 13

Prioritization based on neutral genetic diversity may fail to conserve important characteristics in cattle breeds

Hall, S. J. G., Lenstra, J. A., & Deeming, D. C. (2011) · Journal of Animal Breeding and Genetics · doi:10.1111/j.1439-0388.2011.00949.x · Cited by 14

Genetics and education: Toward a genetically sensitive classroom.

Haworth, C. M. A., & Plomin, R. J. (2011) · American Psychological Association eBooks · doi:10.1037/13273-018 · Cited by 15

Kullback–Leibler Distance Methods for Detecting Disease Association with Rare Variants from Sequencing Data

Turkmen, A., Yan, Z., Hu, Y., & Lin, S. (2015) · Annals of Human Genetics · doi:10.1111/ahg.12103 · Cited by 13

An Assessment of the Individual and Collective Effects of Variants on Height Using Twins and a Developmentally Informative Study Design

Vrieze, S. I., McGue, M. K., Miller, M. B., Legrand, L. N., Schork, N. J., & Iacono, W. G. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002413 · Cited by 13

Assumptions and Properties of Limiting Pathway Models for Analysis of Epistasis in Complex Traits

Stringer, S., Derks, E. M., Kahn, R. S., Hill, W. G., & Wray, N. R. (2013) · PLoS ONE · doi:10.1371/journal.pone.0068913 · Cited by 12

Interaction between a diabetes-related methylation site (TXNIP cg19693031) and variant (GLUT1 rs841853) on fasting blood glucose levels among non-diabetics

Tsai, H., Shen, C., Ho, C., Hsu, S., Tantoh, D. M., Nfor, O. N., Chiu, S., Chou, Y., & Liaw, Y. (2022) · Journal of Translational Medicine · doi:10.1186/s12967-022-03269-y · Cited by 14

A comparative analysis of methods for predicting clinical outcomes using high-dimensional genomic datasets

Jiang, X., Cai, B., Xue, D., Lu, X., Cooper, G. F., & Neapolitan, R. E. (2014) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2013-002358 · Cited by 13

Estimates of missing heritability for complex traits in Brown Swiss cattle

Román-Ponce, S. I., Samorè, A. B., Dolezal, M., Bagnato, A., & Meuwissen, T. H. E. (2014) · Genetics Selection Evolution · doi:10.1186/1297-9686-46-36 · Cited by 13

Differential Susceptibility to Context: A Promising Model of the Interplay of Genes and the Social Environment

Simons, R. L., Beach, S. R. H., & Barr, A. B. (2012) · Advances in group processes · doi:10.1108/s0882-6145(2012)0000029008 · Cited by 14

Epigenetic Programming of Adipose Tissue in the Progeny of Obese Dams

Lecoutre, S., Kwok, K. H. M., Petrus, P., Lambert, M., & Breton, C. (2019) · Current Genomics · doi:10.2174/1389202920666191118092852 · Cited by 14

A novel statistical method for modeling covariate effects in bisulfite sequencing derived measures of DNA methylation

Zhao, K., Oualkacha, K., Lakhal‐Chaieb, L., Labbe, A., Klein, K., Ciampi, A., Hudson, M., Colmegna, I., Pastinen, T., Zhang, T., et al. (2020) · Biometrics · doi:10.1111/biom.13307 · Cited by 14

Rare variants regulate expression of nearby individual genes in multiple tissues

Li, J., Kong, N., Han, B., & Sul, J. H. (2021) · PLoS Genetics · doi:10.1371/journal.pgen.1009596 · Cited by 12

Unifying heritability in evolutionary theory

Bourrat, P. (2021) · Studies in History and Philosophy of Science Part A · doi:10.1016/j.shpsa.2021.10.019 · Cited by 15

Evaluating the detection ability of a range of epistasis detection methods on simulated data for pure and impure epistatic models

Russ, D., Williams, J. A., Cardoso, V. R., Bravo-Merodio, L., Pendleton, S. C., Aziz, F., Acharjee, A., & Gkoutos, G. V. (2022) · PLoS ONE · doi:10.1371/journal.pone.0263390 · Cited by 13

The Human Genome, Microbiomes, and Disease

Badger, J. H., Ng, P. C., & Venter, J. C. (2010) · Springer eBooks · doi:10.1007/978-1-4419-7089-3_1 · Cited by 13

Genetics of autoimmunity: An update

Sorrentino, R. (2013) · Immunology Letters · doi:10.1016/j.imlet.2013.12.005 · Cited by 14

Family-based association analysis: a fast and efficient method of multivariate association analysis with multiple variants

Won, S., Kim, W., Lee, S., Lee, Y., Sung, J., & Park, T. (2015) · BMC Bioinformatics · doi:10.1186/s12859-015-0484-5 · Cited by 13

Pathway genetic load allows simultaneous evaluation of multiple genetic associations

Huebinger, R., Garner, H. R., & Barber, R. C. (2010) · Burns · doi:10.1016/j.burns.2010.02.001 · Cited by 13

ATG18 and FAB1 Are Involved in Dehydration Stress Tolerance in Saccharomyces cerevisiae

López‐Martínez, G., Margalef-Català, M., Salinas, F., Liti, G., & Otero, R. R. C. (2015) · PLoS ONE · doi:10.1371/journal.pone.0119606 · Cited by 13

Adaptive Tests for Detecting Gene-Gene and Gene-Environment Interactions

Pan, W., Basu, S., & Shen, X. (2011) · Human Heredity · doi:10.1159/000330632 · Cited by 13

Predicting Sensation Seeking From Dopamine Genes

Powell, J. E., & Zietsch, B. P. (2011) · Psychological Science · doi:10.1177/0956797610397669 · Cited by 13

Meta-dimensional data integration identifies critical pathways for susceptibility, tumorigenesis and progression of endometrial cancer

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Female Genomics: Infertility and Overall Health

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