Evolution and Functional Impact of Rare Coding Variation from Deep Sequencing of Human Exomes

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A method and server for predicting damaging missense mutations.

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Finding the missing heritability of complex diseases

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

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Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm

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A haplotype map of the human genome

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A second generation human haplotype map of over 3.1 million SNPs

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Evolutionary Rate at the Molecular Level

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Robust relationship inference in genome-wide association studies

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Unresolved questions regarding human hereditary deafness

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Racial Disparities in Necrotizing Enterocolitis

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Computational approaches to study the effects of small genomic variations

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Balancing Selection on a Regulatory Region Exhibiting Ancient Variation That Predates Human–Neandertal Divergence

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High burden of private mutations due to explosive human population growth and purifying selection

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Strong Positive Selection in Aedes aegypti and the Rapid Evolution of Insecticide Resistance

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Nijmegen Breakage Syndrome Detected by Newborn Screening for T Cell Receptor Excision Circles (TRECs)

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Role of Genetics in Pediatric Inflammatory Bowel Disease

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Rare Coding Variants and Breast Cancer Risk: Evaluation of Susceptibility Loci Identified in Genome-Wide Association Studies

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Integration of structural dynamics and molecular evolution via protein interaction networks: a new era in genomic medicine

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Common genetic variation near the connexin-43 gene is associated with resting heart rate in African Americans: A genome-wide association study of 13,372 participants

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Whole Exome Sequencing Implicates an INO80D Mutation in a Syndrome of Aortic Hypoplasia, Premature Atherosclerosis, and Arterial Stiffness

Shameer, K., Klee, E. W., Dalenberg, A. K., & Kullo, I. J. (2014) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.113.000233 · Cited by 28

Exome-chip association analysis reveals an Asian-specific missense variant in PAX4 associated with type 2 diabetes in Chinese individuals

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Novel ultra-rare exonic variants identified in a founder population implicate cadherins in schizophrenia

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ActiveDriverDB: Interpreting Genetic Variation in Human and Cancer Genomes Using Post-translational Modification Sites and Signaling Networks (2021 Update)

Krassowski, M., Pellegrina, D. V. D. S., Mee, M. W., Fradet‐Turcotte, A., Bhat, M., & Reimand, J. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.626821 · Cited by 29

Pathogenic missense protein variants affect different functional pathways and proteomic features than healthy population variants

Laddach, A., Ng, J. C.-F., & Fraternali, F. (2021) · PLoS Biology · doi:10.1371/journal.pbio.3001207 · Cited by 26

The Genetics of Dilated Cardiomyopathy: A Prioritized Candidate Gene Study of LMNA , TNNT2 , TCAP , and PLN

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VariantMetaCaller: automated fusion of variant calling pipelines for quantitative, precision-based filtering

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Population and genomic lessons from genetic analysis of two Indian populations

Juyal, G., Mondal, M., Luisi, P., Laayouni, H., Sood, A., Midha, V., Heutink, P., Bertranpetit, J., Thelma, B. K., & Casals, F. (2014) · Human Genetics · doi:10.1007/s00439-014-1462-0 · Cited by 30

Novel ABCA3 mutations as a cause of respiratory distress in a term newborn

Gonçalves, J., Pinheiro, L., Costa, M. A., Silva, A., Gonçalves, A., & Pereira, A. (2013) · Gene · doi:10.1016/j.gene.2013.11.015 · Cited by 28

A burden of rare variants in BMPR2 and KCNK3 contributes to a risk of familial pulmonary arterial hypertension

Higasa, K., Ogawa, A., Terao, C. C., Shimizu, M., Kosugi, S., Yamada, R., Date, H., Matsubara, H., & Matsuda, F. (2017) · BMC Pulmonary Medicine · doi:10.1186/s12890-017-0400-z · Cited by 28

An ABC Method for Whole-Genome Sequence Data: Inferring Paleolithic and Neolithic Human Expansions

Jay, F., Boitard, S., & Austerlitz, F. (2019) · Molecular Biology and Evolution · doi:10.1093/molbev/msz038 · Cited by 35

Genetic polymorphisms of human hepatic OATPs: functional consequences and effect on drug pharmacokinetics

Nie, Y., Yang, J., Liu, S., Sun, R., Chen, H., Long, N., Jiang, R. S., & Gui, C. (2019) · Xenobiotica · doi:10.1080/00498254.2019.1629043 · Cited by 28

Computational and experimental methods for classifying variants of unknown clinical significance.Preprint

Spielmann, M., & Kircher, M. (2022) · PubMed · doi:10.1101/mcs.a006196 · Cited by 28

Tetralogy of Fallot and Hypoplastic Left Heart Syndrome – Complex Clinical Phenotypes Meet Complex Genetic Networks

Lahm, H., Schön, P., Doppler, S. A., Dreßen, M., Cleuziou, J., Deutsch, M.-A., Ewert, P., Lange, R., & Krane, M. (2015) · Current Genomics · doi:10.2174/1389202916666150303232520 · Cited by 28

Large numbers of individuals are required to classify and define risk for rare variants in known cancer risk genes

Shirts, B. H., Jacobson, A. L., Jarvik, G. P., & Browning, B. L. (2013) · Genetics in Medicine · doi:10.1038/gim.2013.187 · Cited by 27

Computational Approaches and Resources in Single Amino Acid Substitutions Analysis Toward Clinical Research

Doss, C. G. P., Chakraborty, C., Narayan, V., & Kumar, D. T. (2014) · Advances in protein chemistry and structural biology · doi:10.1016/b978-0-12-800168-4.00010-x · Cited by 27

High prevalence of cancer‐associated TP53 variants in the gnomAD database: A word of caution concerning the use of variant filtering

Soussi, T., Leroy, B., Devir, M., & Rosenberg, S. (2019) · Human Mutation · doi:10.1002/humu.23717 · Cited by 27

Can one hear the shape of a population history?

Kim, J., Mossel, E., Rácz, M. Z., & Ross, N. (2014) · Theoretical Population Biology · doi:10.1016/j.tpb.2014.12.002 · Cited by 26

Multidisciplinary approaches for elucidating genetics and molecular pathogenesis of urinary tract malformations

Khan, K., Ahram, D. F., Liu, Y. P., Westland, R., Sampogna, R. V., Katsanis, N., Davis, E. E., & Sanna‐Cherchi, S. (2021) · Kidney International · doi:10.1016/j.kint.2021.09.034 · Cited by 28

Transplantation Genetics: Current Status and Prospects

Almoguera, B., Shaked, A. A., & Keating, B. J. (2014) · American Journal of Transplantation · doi:10.1111/ajt.12653 · Cited by 27

Genetic Variation in Cardiomyopathy and Cardiovascular Disorders

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Ankyrin-B metabolic syndrome combines age-dependent adiposity with pancreatic β cell insufficiency

Lorenzo, D. N., Healy, J. A., Hostettler, J., Davis, J. Q., Yang, J., Wang, C., Hohmeier, H. E., Zhang, M., & Bennett, V. (2015) · Journal of Clinical Investigation · doi:10.1172/jci81317 · Cited by 27

Next Generation Sequencing in the Clinical Domain: Clinical Advantages, Practical, and Ethical Challenges

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A missense mutation in SLC26A3 is associated with human male subfertility and impaired activation of CFTR

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A large‐scale exome array analysis of venous thromboembolism

Lindström, S., Brody, J. A., Turman, C., Germain, M., Bartz, T. M., Smith, E. N., Chen, M., Puurunen, M. K., Chasman, D. I., Hassler, J., et al. (2019) · Genetic Epidemiology · doi:10.1002/gepi.22187 · Cited by 28

The contribution of rare genetic variants to the pathogenesis of polycystic ovary syndrome

Dapas, M., & Dunaif, A. E. (2020) · Current Opinion in Endocrine and Metabolic Research · doi:10.1016/j.coemr.2020.02.011 · Cited by 28

Testing Closeness With Unequal Sized SamplesPreprint

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Strong Constraint on Human Genes Escaping X-Inactivation Is Modulated by their Expression Level and Breadth in Both Sexes

Slavney, A., Arbiza, L., Clark, A. G., & Keinan, A. (2016) · Molecular Biology and Evolution · doi:10.1093/molbev/msv225 · Cited by 26

Accurately Predicting Mutation-Caused Stability Changes from Protein Sequences Using Extreme Gradient Boosting

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Quantifying the origins of population variability in cardiac electrical activity through sensitivity analysis of the electrocardiogram

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IL12B and IL23R gene SNPs in Japanese psoriasis

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Mutation detection in formalin-fixed prostate cancer biopsies taken at the time of diagnosis using next-generation DNA sequencing

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Rare coding variation in paraoxonase-1 is associated with ischemic stroke in the NHLBI Exome Sequencing Project

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Estimating exome genotyping accuracy by comparing to data from large scale sequencing projects

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Global genetic diversity of human apolipoproteins and effects on cardiovascular disease risk

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Clinical genetic testing in endocrinology: Current concepts and contemporary challenges

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Gene-Specific Function Prediction for Non-Synonymous Mutations in Monogenic Diabetes Genes

Li, Q., Liu, X., Gibbs, R. A., Boerwinkle, E., Polychronakos, C., & Qu, H. (2014) · PLoS ONE · doi:10.1371/journal.pone.0104452 · Cited by 25

Progress and Future Aspects in Genetics of Human Hypertension

Zhao, Q., Kelly, T. N., Li, C., & He, J. (2013) · Current Hypertension Reports · doi:10.1007/s11906-013-0388-6 · Cited by 28

Rare variants analysis of cutaneous malignant melanoma genes in Parkinson's disease

Lubbe, S. J., Escott‐Price, V., Brice, A., Gasser, T., Pittman, A. M., Brás, J., Hardy, J., Heutink, P., Wood, N. W., Singleton, A., et al. (2016) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2016.07.013 · Cited by 26

Genomic approaches to the assessment of human spina bifida risk

Ross, M. E., Mason, C. E., & Finnell, R. H. (2016) · Birth Defects Research · doi:10.1002/bdra.23592 · Cited by 26

Partial uniparental isodisomy of chromosome 16 unmasks a deleterious biallelic mutation in IFT140 that causes Mainzer-Saldino syndrome

Helm, B. M., Willer, J. R., Sadeghpour, A., Golzio, C., Crouch, E. R., Vergano, S. A. S., Katsanis, N., & Davis, E. E. (2017) · Human Genomics · doi:10.1186/s40246-017-0111-9 · Cited by 27

µ-Crystallin: A thyroid hormone binding protein

Kinney, C. J., & Bloch, R. J. (2021) · Endocrine Regulations · doi:10.2478/enr-2021-0011 · Cited by 27

Correction: The Role of Selection in Shaping Diversity of Natural M. tuberculosis Populations

Pepperell, C. S., Casto, A. M., Kitchen, A., Granka, J. M., Cornejo, O. E., Holmes, E. C., Birren, B. W., Galagan, J. E., & Feldman, M. W. (2013) · PLoS Pathogens · doi:10.1371/annotation/cff22061-44d5-4301-b853-41702d160203 · Cited by 25

Improving long-term kidney allograft survival by rethinking HLA compatibility: from molecular matching to non-HLA genes

Mattoo, A., Jaffe, I. S., Keating, B. J., Montgomery, R. A., & Mangiola, M. (2024) · Frontiers in Genetics · doi:10.3389/fgene.2024.1442018 · Cited by 28

Mitochondrial DNA Polymerase γ Mutations and Their Implications in mtDNA Alterations in Colorectal Cancer

Linkowska, K., Jawień, A., Marszałek, A., Malyarchuk, B. А., Tońska, K., Bartnik, E., Skonieczna, K., & Grzybowski, T. (2015) · Annals of Human Genetics · doi:10.1111/ahg.12111 · Cited by 25

Direct Measurements of Human Colon Crypt Stem Cell Niche Genetic Fidelity: The Role of Chance in Non-Darwinian Mutation Selection

Kang, H., & Shibata, D. K. (2013) · Frontiers in Oncology · doi:10.3389/fonc.2013.00264 · Cited by 25

Identification of the Photoreceptor Transcriptional Co-Repressor SAMD11 as Novel Cause of Autosomal Recessive Retinitis Pigmentosa

Cortón, M., Avila-Fernández, A., Campello, L., Sánchez, M., Benavides, B., López-Molina, M.-I., Fernández‐Sánchez, L., Sánchez-Alcudia, R., da Silva, L. R. J., Reyes, N. S., et al. (2016) · Scientific Reports · doi:10.1038/srep35370 · Cited by 26

Identification of a novel RPGRIP 1 mutation in an Iranian family with leber congenital amaurosis by exome sequencing

İmani, S., Cheng, J., Mobasher‐Jannat, A., Wei, C., Fu, S., Yang, L., Jadidi, K., Khosravi, M. H., Mohazzab‐Torabi, S., Shasaltaneh, M. D., et al. (2017) · Journal of Cellular and Molecular Medicine · doi:10.1111/jcmm.13454 · Cited by 25

Analyses of the genetic diversity and protein expression variation of the acyl: CoA medium-chain ligases, ACSM2A and ACSM2B

van der Sluis, R. (2018) · Molecular Genetics and Genomics · doi:10.1007/s00438-018-1460-3 · Cited by 25

Pharmacogenomics of statins: lipid response and other outcomes in Brazilian cohorts

Dagli-Hernandez, C., Zhou, Y., Lauschke, V. M., Genvigir, F. D. V., Hirata, T. D. C., Hirata, M. H., & Hirata, R. D. C. (2021) · Pharmacological Reports · doi:10.1007/s43440-021-00319-y · Cited by 25

Steroid-sensitive nephrotic syndrome candidate gene CLVS1 regulates podocyte oxidative stress and endocytosis

Lane, B. M., Chryst-Stangl, M., Wu, G., Shalaby, M. A., Desoky, S. M. E., Middleton, C. C., Huggins, K., Sood, A., Ochoa, A., Malone, A. F., et al. (2021) · JCI Insight · doi:10.1172/jci.insight.152102 · Cited by 24

Analysis of coding variants identified from exome sequencing resources for association with diabetic and non-diabetic nephropathy in African Americans

Bailey, J. N. C., Palmer, N. D., Ng, M. C. Y., Bonomo, J. A., Hicks, P. J., Hester, J. M., Langefeld, C. D., Freedman, B. I., & Bowden, D. W. (2014) · Human Genetics · doi:10.1007/s00439-013-1415-z · Cited by 24

Episodic Neurologic Disorders: Syndromes, Genes, and Mechanisms

Russell, J. F., Fu, Y., & Ptáček, L. J. (2013) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-062012-170300 · Cited by 24

Evaluating information content of SNPs for sample-tagging in re-sequencing projects

Hu, H., Liu, X., Jin, W., Ropers, H., & Wienker, T. F. (2015) · Scientific Reports · doi:10.1038/srep10247 · Cited by 24

Non-Coding Loss-of-Function Variation in Human Genomes

Zappala, Z., & Montgomery, S. B. (2016) · Human Heredity · doi:10.1159/000447453 · Cited by 28

No significant enrichment of rare functionally defective CPA1 variants in a large Chinese idiopathic chronic pancreatitis cohort

Wu, H., Zhou, D., Berki, D. M., Geisz, A., Zou, W., Sun, X., Hu, L., Zhao, Z., Zhao, A., He, L., et al. (2017) · Human Mutation · doi:10.1002/humu.23254 · Cited by 25

Personalised analytics for rare disease diagnostics

Anderson, D., Baynam, G., Blackwell, J. M., & Lassmann, T. (2019) · Nature Communications · doi:10.1038/s41467-019-13345-5 · Cited by 24

Body Mass Index Modulates Blood Pressure Heritability: The Family Blood Pressure Program

Simino, J. M., Shi, G., Weder, A. B., Boerwinkle, E., Hunt, S. C., & Rao, D. C. (2013) · American Journal of Hypertension · doi:10.1093/ajh/hpt144 · Cited by 24

Inferring Selective Constraint from Population Genomic Data Suggests Recent Regulatory Turnover in the Human Brain

Schrider, D. R., & Kern, A. D. (2015) · Genome Biology and Evolution · doi:10.1093/gbe/evv228 · Cited by 26

Testing for Rare Variant Associations in the Presence of Missing Data

Auer, P. L., Wang, G. T., & Leal, S. M. (2013) · Genetic Epidemiology · doi:10.1002/gepi.21736 · Cited by 22

The ICR1000 UK exome series: a resource of gene variation in an outbred population

Ruark, E., Münz, M., Renwick, A., Clarke, M., Ramsay, E., Hanks, S., Mahamdallie, S., Elliott, A., Seal, S., Strydom, A., et al. (2015) · F1000Research · doi:10.12688/f1000research.7049.1 · Cited by 24

Large differences in proportions of harmful and benign amino acid substitutions between proteins and diseases

Schaafsma, G. C. P., & Vihinen, M. (2017) · Human Mutation · doi:10.1002/humu.23236 · Cited by 24

Population-specific genetic variation in large sequencing data sets: why more data is still better

van Rooij, J., Jhamai, M. M., Arp, P., Nouwens, S., Verkerk, M., Albert Hofman, D., Ikram, M. A., Verkerk, A. J. M. H., van Meurs, J. B. J., Rivadeneira, F., et al. (2017) · European Journal of Human Genetics · doi:10.1038/ejhg.2017.110 · Cited by 24

Strategies for identification of somatic variants using the Ion Torrent deep targeted sequencing platform

Deshpande, A. S., Lang, W., McDowell, T. L., Sivakumar, S., Zhang, J., Wang, J., Lucas, F. A. S., Fowler, J., Kadara, H. N., & Scheet, P. A. (2018) · BMC Bioinformatics · doi:10.1186/s12859-017-1991-3 · Cited by 23

Considerations for rare variants in drug metabolism genes and the clinical implications

Drögemöller, B. I., Wright, G. E. B., & Warnich, L. (2014) · Expert Opinion on Drug Metabolism & Toxicology · doi:10.1517/17425255.2014.903239 · Cited by 24

Polar Bodies in Assisted Reproductive Technology: Current Progress and Future Perspectives1

Wei, Y., Zhang, T., Wang, Y., Schatten, H., & Sun, Q. (2014) · Biology of Reproduction · doi:10.1095/biolreprod.114.125575 · Cited by 24

Pathway Databases: Making Chemical and Biological Sense of the Genomic Data Flood

D’Eustachio, P. (2013) · Chemistry & Biology · doi:10.1016/j.chembiol.2013.03.018 · Cited by 25

Application of high-throughput sequencing for studying genomic variations in congenital heart disease

Dorn, C., Grunert, M., & Sperling, S. (2013) · Briefings in Functional Genomics · doi:10.1093/bfgp/elt040 · Cited by 23

A future of the model organism model

Rine, J. (2014) · Molecular Biology of the Cell · doi:10.1091/mbc.e12-10-0768 · Cited by 26

Common and Rare Genetic Variation in CCR2 , CCR5 , or CX3CR1 and Risk of Atherosclerotic Coronary Heart Disease and Glucometabolic Traits

Golbus, J. R., Stitziel, N. O., Zhao, W., Xue, C., Farrall, M., McPherson, R., Erdmann, J., Deloukas, P., Watkins, H. C., Schunkert, H., et al. (2016) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.115.001374 · Cited by 25

Improving Patient behavioral Consent through Different Service Quality Dimensions: Assessing the Mediating Role of Patient Satisfaction

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Predicting Genetic Variation Severity Using Machine Learning to Interpret Molecular Simulations

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