Statistical power and significance testing in large-scale genetic studies

Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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

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A method and server for predicting damaging missense mutations.

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Statistical Methods for Research Workers

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Principal components analysis corrects for stratification in genome-wide association studies

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Bootstrap Methods and their Application

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A haplotype map of the human genome

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Bootstrap Methods and Their Application

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Genome-wide association studies for common diseases and complex traits

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Rectangular Confidence Regions for the Means of Multivariate Normal Distributions

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Machine learning reveals complex genetics of fungal resistance in sorghum grain mold

Ahn, E. J. S., Prom, L. K., Park, S., Lee, D., Bhatt, J., Ellur, V., Lim, S., Jang, J. H., Lakshman, D. K., & Magill, C. (2025) · Heredity · doi:10.1038/s41437-025-00783-9 · Cited by 3

Platform-dependent effects of genetic variants on plasma APOL1

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SPS: A Simulation Tool for Calculating Power of Set‐Based Genetic Association Tests

Li, J., Sham, P. C., Song, Y., & Li, M. (2015) · Genetic Epidemiology · doi:10.1002/gepi.21898 · Cited by 3

Pathway-Wide Genetic Risks in Chlamydial Infections Overlap between Tissue Tropisms: A Genome-Wide Association Scan

Roberts, C. H., Ouburg, S., Preston, M. D., de Vries, H. J. C., Holland, M. J., & Morré, S. A. (2018) · Mediators of Inflammation · doi:10.1155/2018/3434101 · Cited by 3

Association of UCP1, UCP2 and UCP3 gene polymorphisms with cardiovascular disease risk factors in European adolescents: the HELENA study

Pascual-Gamarra, J. M., Salazar‐Tortosa, D. F., Labayen, I., Rupérez, A. I., Leclercq, C., Marcos, A., Gómez‐Martínez, S., Moreno, L. A., Meirhaeghe, A., Castillo, M. J., et al. (2020) · Pediatric Research · doi:10.1038/s41390-019-0735-7 · Cited by 3

Separating Measurement Error and Signal in Environmental Data: Use of Replicates to Address Uncertainty

Furman, M., Thomas, K., & George, B. J. (2023) · Environmental Science & Technology · doi:10.1021/acs.est.3c02231 · Cited by 3

Genetic Factors and Long-term Treatment-Related Neurocognitive Deficits, Anxiety, and Depression in Childhood Leukemia Survivors: An Exome-Wide Association Study

Petrykey, K., Lippé, S., Sultan, S., Robaey, P., Drouin, S., Bertout, L., Beaulieu, P., St-Onge, P., Baedke, J. L., Yasui, Y., et al. (2023) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-23-0634 · Cited by 3

OncoMiner: A Pipeline for Bioinformatics Analysis of Exonic Sequence Variants in Cancer

Leung, M., Knapka, J. A., Wagler, A. E., Rodriguez, G., & Kirken, R. A. (2016) · Springer eBooks · doi:10.1007/978-3-319-41279-5_12 · Cited by 3

A Structural Equation Model of Leader–Member Exchange, Employee–Supervisor Relationship, Performance Appraisal, and Career Development

Henkel, W. J., & Endres, A. (2019) · International Journal of Applied Management and Technology · doi:10.5590/ijamt.2019.18.1.06 · Cited by 3

Classifying mild traumatic brain injuries with functional network analysis

Lucas, F. A. S., Redell, J. B., Dash, P. K., & Liu, Y. (2018) · BMC Systems Biology · doi:10.1186/s12918-018-0645-z · Cited by 3

ARHGAP18 is a novel gene under positive natural selection that influences HbF levels in β-thalassaemia

He, Y., Luo, J., Chen, Y., Zhou, X., Yu, S., Jin, L., Xiao, X., Jia, S., & Liu, Q. (2017) · Molecular Genetics and Genomics · doi:10.1007/s00438-017-1377-2 · Cited by 3

Genetic Risk Factors for Sporadic Frontotemporal Dementia

Ferrari, R., Manzoni, C., & Momeni, P. (2018) · Springer eBooks · doi:10.1007/978-3-319-72938-1_9 · Cited by 3

Organization of Genetic Variation

Hartl, D. L. (2020) · Oxford University Press eBooks · doi:10.1093/oso/9780198862291.003.0002 · Cited by 3

Genome-wide haplotype-based association analysis of major depressive disorder in Generation Scotland and UK BiobankPreprint

Howard, D. M., Hall, L. S., Hafferty, J. D., Zeng, Y., Adams, M. J., Clarke, T., Porteous, D. J., Nagy, R., Hayward, C., Smith, B. H., et al. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/068643 · Cited by 3

Genome‐Wide Association Studies

McCauley, J. L., Veturi, Y., Verma, S. S., & Ritchie, M. D. (2021) · Wiley eBooks · doi:10.1002/9781119104100.ch9 · Cited by 3

Landscape biogeography and population structuring of a facultatively amphidromous galaxiid fish, Galaxias brevipinnisPreprint

Augspurger, J. M., Jarvis, M., Wallis, G. P., King, T. M., Ingram, T., Hicks, A. S., & Closs, G. P. (2021) · doi:10.22541/au.162283809.92616181/v1 · Cited by 3

Transcriptome profiles of blastocysts originating from oocytes matured in follicular fluid from preovulatory follicles of greater or lesser maturity

Stokes, A. E., Clark, H. M., Edwards, J. L., Payton, R. R., Beever, J. E., Freeman, T. F., Hessock, E. A., Schrick, F. N., & Moorey, S. E. (2025) · BMC Genomics · doi:10.1186/s12864-025-11521-0 · Cited by 2

Ten essential tips for robust statistics in cell biology

Ibrahimi, E., & Wolford, B. N. (2025) · Nature Cell Biology · doi:10.1038/s41556-025-01801-y · Cited by 2

Cost-effective non-additive GWAS across 2329 diseases in 500,349 individuals

Molotkov, I., Kurki, M., FinnGen, Palotie, A. V., Daly, M. J., & Artomov, M. (2025) · Nature Communications · doi:10.1038/s41467-025-67277-4 · Cited by 2

Systematic comparison of phenome-wide admixture mapping and genome-wide association at biobank-scale

Cullina, S., Shemirani, R., Shi, Z., Mandla, R., Paşaniuc, B., Asgari, S., & Kenny, E. E. (2026) · Nature Communications · doi:10.1038/s41467-026-76694-y · Cited by 2

Next-Generation Sequencing Data-Based Association Testing of a Group of Genetic Markers for Complex Responses Using a Generalized Linear Model Framework

Xu, Z. Q., Yan, S., Wu, C., Duan, Q., Chen, S., & Li, Y. (2023) · Mathematics · doi:10.3390/math11112560 · Cited by 2

Why and When Statistics is Required, and How to Simplify Choosing Appropriate Statistical Techniques During Ph.D. Program in India?

Ganesha, H. R., & Aithal, P. S. (2022) · International Journal of Management Technology and Social Sciences · doi:10.47992/ijmts.2581.6012.0236 · Cited by 2

Over-representation analysis of angiogenic factors in immunosuppressive mechanisms in neoplasms and neurological conditions during COVID-19

Chatterjee, S. S., & Sanjeev, B. S. (2023) · Microbial Pathogenesis · doi:10.1016/j.micpath.2023.106386 · Cited by 2

Genomic Markers Associated with Cytomegalovirus DNAemia in Kidney Transplant Recipients

Shapira, G., Volkov, H., Fabian, I., Mohr, D. W., Bettinotti, M. P., Shomron, N., Avery, R. K., & Arav‐Boger, R. (2023) · Viruses · doi:10.3390/v15112227 · Cited by 2

Genome-wide association analysis using multiple Atlantic salmon populations

Ajasa, A. A., Gjøen, H. M., Boison, S. A., & Lillehammer, M. (2025) · Genetics Selection Evolution · doi:10.1186/s12711-025-00959-1 · Cited by 2

The presence of a marker associated with Pacific oyster resistance to OsHV-1 does not affect susceptibility to Vibrio aestuarianus

Surry, L. B., Sutherland, B. J. G., Lunda, S. L., Loudon, A. H., Divilov, K., Langdon, C. J., & Green, T. J. (2026) · Aquaculture Science and Management. · doi:10.1186/s44365-026-00038-6 · Cited by 2

Statistical Strategies for Selection of Differentially Expressed Proteins Based on Mass Spectrometry Technology

Wang, J., YunPing, Z. H. U., Wu, S., Ma, J., Zhuang, J., & Chang, C. (2015) · Scientia Sinica Vitae · doi:10.1360/n052014-00197 · Cited by 2

G‐STRATEGY: Optimal Selection of Individuals for Sequencing in Genetic Association Studies

Wang, M., Jakobsdóttir, J., Smith, A. V., & McPeek, M. S. (2016) · Genetic Epidemiology · doi:10.1002/gepi.21982 · Cited by 2

Genomic treatment response prediction in schizophrenia

Legge, S. E., Pardiñas, A. F., & Walters, J. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-813176-3.00034-1 · Cited by 2

Design and implementation of a custom next generation sequencing panel for selected vitamin D associated genes

Benson, K. A., Chand, S., Maxwell, A. P., Smyth, L. J., Kilner, J., Borrows, R., & McKnight, A. J. (2017) · BMC Research Notes · doi:10.1186/s13104-017-2664-z · Cited by 2

Quick approximation of threshold values for genome-wide association studies

Hao, Z., Jiang, L., Gao, J., Ye, J., Zhao, J., Li, S., & Yang, R. (2018) · Briefings in Bioinformatics · doi:10.1093/bib/bby082 · Cited by 2

U-PASS: unified power analysis and forensics for qualitative traits in genetic association studies

Gao, Z., Terhorst, J., Hout, C. V. V., & Stoev, S. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz637 · Cited by 2

Association between CNTF Polymorphisms and Adiposity Markers in European Adolescents

Pascual-Gamarra, J. M., Salazar‐Tortosa, D. F., Labayen, I., Rupérez, A. I., Censi, L., Béghin, L., Michels, N., González‐Gross, M., Μanios, Y., Lambrinou, C., et al. (2020) · The Journal of Pediatrics · doi:10.1016/j.jpeds.2019.12.036 · Cited by 2

Interplay of physical activity and genetic variants of the endothelial lipase on cardiovascular disease risk factors

Salazar‐Tortosa, D. F., Pascual-Gamarra, J. M., Labayen, I., Rupérez, A. I., Censi, L., Béghin, L., Michels, N., González‐Gross, M., Μanios, Y., Lambrinou, C., et al. (2021) · Pediatric Research · doi:10.1038/s41390-021-01519-1 · Cited by 2

Biomedical research at the crossroads and ways through

Pons, J. M. V., & Adam, P. (2018) · Medicina Clínica (English Edition) · doi:10.1016/j.medcle.2018.05.036 · Cited by 2

Playing Musical Chairs in Big Data to Reveal Variables’ AssociationsPreprint

Aschard, H., Vilhjálmsson, B. J., Patel, C. J., Skurnik, D., Yu, J., Wolpin, B. M., Kraft, P. L., & Zaitlen, N. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/057190 · Cited by 2

The role of adaptive evolution in the success of an agricultural weed, Helianthus annuus

Drummond, E. B. M. (2019) · cIRcle (University of British Columbia) · doi:10.14288/1.0365262 · Cited by 2

Rewiring of gene expression in circulating white blood cells is associated with pregnancy outcome in heifers (Bos taurus)Preprint

Moorey, S. E., Walker, B. N., Elmore, M. F., Elmore, J. B., Rodning, S. P. P., & Biase, F. H. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.03.18.997379 · Cited by 2

Genetic parameter estimation and molecular foundation of Double-yolk eggs trait in white leghorn

Chen, A., Zhao, X., Wang, H., Zhao, X., Wang, G., Zhang, X., Ren, X., Zhang, Y., Xue, C., Yu, X., et al. (2025) · Poultry Science · doi:10.1016/j.psj.2025.105069 · Cited by 1

Discovering Genetic Variants in Hypertrophic Cardiomyopathy With Multiple Machine Learning Techniques

Lozano-Paredes, D., Bote-Curiel, L., Molina, M. S., Bielza, C., Gimeno, J. R., Muñoz-Romero, S., Gimeno-Blanes, F.-J., Larrañaga, P., & Rojo‐Álvarez, J. L. (2025) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbbio.2025.3572833 · Cited by 1

Genomic Insights into Genetic Diversity and Adaptation of Nanyang Cattle: Implications for Conservation and Breeding

Zhang, Y., Liu, X., Liu, J., Fu, T., Huang, H., Han, M., Liang, D., & Gao, T. (2025) · Animals · doi:10.3390/ani15203033 · Cited by 1

The TUB variant impairs leptin sensitivity and AgRP neuronal response, leading to obesity

Tong, M., Chen, Y., Song, B., Hong, J., Gu, W., Shen, J., Yang, H., Xia, H., Li, Q., Chen, Y., et al. (2026) · Science Translational Medicine · doi:10.1126/scitranslmed.adw0458 · Cited by 1

A Beginner's How‐To Guide to Urban Population Genetics and Genomics

Carlen, E. J., Miles, L. S., Avilés‐Rodríguez, K. J., & Booth, W. (2026) · Ecology and Evolution · doi:10.1002/ece3.73372 · Cited by 1

mPower: a real data-based power analysis tool for microbiome study design

Yang, L., & Chen, J. (2026) · Microbiome · doi:10.1186/s40168-026-02427-4 · Cited by 1

Strategies to improve the performance of rare variant association studies by optimizing the selection of controls

Zhu, N., Heinrich, V., Dickhaus, T., Hecht, J., Robinson, P. N., Mundlos, S., Kamphans, T., & Krawitz, P. M. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv457 · Cited by 2

Univariate and multivariate statistical tests in genetic association studies

Ruotsalainen, S. (2017) · Työväentutkimus Vuosikirja · Cited by 1

Association between PTCH1 and RAD54B Single-Nucleotide Polymorphisms and Non-syndromic Orofacial Clefts in the Northeast Population of Iran

Farimani, R. M., Azimi–Nezhad, M., KhorramKhorshid, H. R., Ebadifar, A., Tohidkhah, S., Jafarian, Z., Kamali, K., Nazari, Z., & Ebrahimzadeh‐Vesal, R. (2022) · Avicenna Journal of Medical Biotechnology · doi:10.18502/ajmb.v14i4.10486 · Cited by 1

Recent Advances in Genetic Epidemiology of Colorectal Cancer in Chinese Population

Tian, J., Miao, X., & Lin, D. (2022) · Springer eBooks · doi:10.1007/978-981-19-2199-5_9 · Cited by 1

Effects of gene-lifestyle environment interactions on type 2 diabetes mellitus development: an analysis using the Korean Genome and Epidemiology Study data

Hyun, S., & Jun, S. (2023) · Journal of Korean Biological Nursing Science · doi:10.7586/jkbns.23.353 · Cited by 1

Rigor and reproducibility in genetic research and the effects on scientific reporting and public discourse

Schmidt, M. H. M., & Dluzen, D. F. (2024) · Elsevier eBooks · doi:10.1016/b978-0-12-817218-6.00012-7 · Cited by 1

Multiomics Approach to Asthma: Navigating the Network

McDonald, M. (2017) · American Journal of Respiratory Cell and Molecular Biology · doi:10.1165/rcmb.2017-0220ed · Cited by 1

Application of DNA Microarrays in Cytogenetics

Aziz, M. A. (2017) · International Journal of Cell Science & Molecular Biology · doi:10.19080/ijcsmb.2017.02.555578 · Cited by 1

Adrenal insufficiency and ICS: genetics takes a breath

Cho, M. H., & Tantisira, K. G. (2018) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(18)30101-2 · Cited by 1

Marginal Screening of 2 × 2 Tables in Large-Scale Case-Control Studies

McKeague, I. W., & Qian, M. (2018) · Biometrics · doi:10.1111/biom.12957 · Cited by 1

The Clinical Application of RNA Sequencing in Genetic Diagnosis of Mendelian Disorders

Stenton, S. L., & Prokisch, H. (2018) · Advances in Molecular Pathology · doi:10.1016/j.yamp.2018.06.004 · Cited by 1

Case Management for Southwestern Hospice Organization

Rumsey, C. M., & Hopkins, E. (2019) · Journal of Hospice and Palliative Nursing · doi:10.1097/njh.0000000000000603 · Cited by 1

Across-breed genomic prediction for body weight in Siberian cattle populations

Karacaören, B. (2020) · TURKISH JOURNAL OF VETERINARY AND ANIMAL SCIENCES · doi:10.3906/vet-1911-98 · Cited by 1

Designing Genetic Linkage and Association Studies that Maintain Desired Statistical Power in the Presence of Mixtures

Gordon, D., Finch, S. J., & Kim, W. (2020) · Statistics for biology and health · doi:10.1007/978-3-030-61121-7_5 · Cited by 1

Converging Findings from Linkage and Association Analyses on Susceptibility Genes for Smoking Addiction

Li, M. D. (2018) · Springer eBooks · doi:10.1007/978-981-10-7530-8_10 · Cited by 1

Association Testing of a Group of Genetic Markers Based on Next-Generation Sequencing Data and Continuous Response Using a Linear Model Framework

Xu, Z. Q. (2023) · Mathematics · doi:10.3390/math11061285 · Cited by 1

E -value: a superior alternative to P -value and its adjustments in DNA methylation studies

Yang, Y., Liu, H., Liu, Y., Zhou, L., Zheng, X., Yue, R., Mattson, D. L., Kidambi, S., Liang, M., Liu, P., et al. (2023) · Briefings in Bioinformatics · doi:10.1093/bib/bbad241 · Cited by 1

Ethical Issues in Statistical Genetics

Wallace, S. E., & Ashcroft, R. E. (2019) · Wiley eBooks · doi:10.1002/9781119487845.ch19 · Cited by 1

Powered for Success: Considerations for Using the Candidate Gene Approach in Rheumatic Diseases in the Post-genomics Era

O’Rielly, D. D., Zhai, G., & Rahman, P. (2014) · The Journal of Rheumatology · doi:10.3899/jrheum.140692 · Cited by 1

Discovery of genetic determinants for refractive error

Shah, R. L. (2018) · ORCA Online Research @Cardiff (Cardiff University) · Cited by 1

Changing perspectives: Towards detailed phenotyping in geneticsPreprint

Nagel, M. (2020) · Thesis Commons (OSF Preprints) · doi:10.31237/osf.io/a4nz2 · Cited by 1

Polymorphism in maternal HLA-DRB5 is associated with the risk of preeclampsia in Chinese populationPreprint

Xu, C., Zhou, L., Fang, Q., Liu, Y., Yang, J., Luo, L., Li, S., Guo, P., Niu, Y., Deng, W., et al. (2023) · Research Square · doi:10.21203/rs.3.rs-2746165/v1 · Cited by 1

The genetic architecture of gene expression in individuals of African and European ancestryPreprint

Fletez‐Brant, K., Sauteraud, R., Liang, Y., Micheletti, S. J., Nandakumar, P., Sugathan, A., Song, K. S., Cavazos, T. B., Thomas, A. L., Tunney, R. J., et al. (2024) · medRxiv · doi:10.1101/2024.12.13.24318019 · Cited by 1

Characterizing the impact of plasma protein levels on human brain structure and disorders leveraging integrative multi-omics analysisPreprint

Ayubcha, C., Dennis, E., Bhattacharyya, U., John, J., Lam, M., Lencz, T., Ge, T., & Chen, C. (2026) · medRxiv · doi:10.64898/2026.07.13.26358006 · Cited by 1

Genomics approaches to study music perception and performance

Kanduri, C. (2015) · Työväentutkimus Vuosikirja

Statistical Methods for the Analysis of Copy Number Variation

Nguyen, T. H. (2015) · Otago University Research Archive (University of Otago)

Editorial: A Novel Genetic Association With Systemic Sclerosis: The Utility of Whole‐Exome Sequencing in Autoimmune Disease

Aslibekyan, S. W., Laufer, V. A., Arnett, D. K., & Bridges, S. L. (2015) · Arthritis & Rheumatology · doi:10.1002/art.39451

Genetic association studies in allergic rhinitis

Carlberg, D. (2014) · Figshare

Identification of Genomic Variants Associated with Adolescent Idiopathic Scoliosis (AIS) in French-Canadian Population

Tang, Q. (2014) · doi:10.71781/30203

Mapping and fine-mapping of genetic factors affecting bovine milk composition

Duchemin, S. I. (2016) · doi:10.18174/370103

Enhancing power of rare variant association test by Zoom-Focus Algorithm (ZFA) to locate optimal testing regionPreprint

Wang, M. H., Weng, H., Sun, R., & Zee, B. C.-Y. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1606.08941

Admixture mapping for disease gene discovery

Johnson, R. C., Winkler, C. A., & Yeager, M. (2015) · Cambridge University Press eBooks · doi:10.1017/cbo9781107337459.009

Genetic and Genomic Approaches to Acute Lung Injury

Yang, I. V. (2016) · Respiratory medicine · doi:10.1007/978-3-319-46527-2_9

Genetic approaches to neurodegenerative disease

Takada, L. T. (2016) · Cambridge University Press eBooks · doi:10.1017/9781139924771.006

The Ethical Implications of Emerging Genetic Predictors of Poor Organ Transplant Outcomes

Freeman, M. A. R. (2016) · D-Scholarship@Pitt (University of Pittsburgh)

Nicotine Dependence – Identifying the Contribution of Specific Genes

Hällfors, J. (2017) · Työväentutkimus Vuosikirja

Perfil poligênico de atletas brasileiros: distribuição de polimorfismos associados ao desempenho físico

Guilherme, J. P. L. F. (2017) · Digital Library of Theses and Dissertations (Universidade de São Paulo) · doi:10.11606/t.39.2017.tde-10042017-134032

Gene Discovery and Glutamate Signaling Defects in Intellectual Disability and Autism

Niranjan, T. (2015)

A Genetic Association Study of Glutamate Transporter Genes SLC1A1 and SLC1A3 in Tourette Syndrome and Attention-Deficit/Hyperactivity Disorder

Kentebe, A. (2014) · TSpace (University of Toronto)

Integrating Human Population Genetics And Genomics To Elucidate The Etiology Of Brain Disorders

Sulovari, A. (2017) · ScholarWorks -A service of University of Vermont Libraries (University of Vermont)

Regulation of NKX2-5 in blood vessels

Dritsoula, A. (2017) · UCL Discovery (University College London)

From Hype to Hope: Genome-Wide Association Studies in Soybean

Zhu, C., Valliyodan, B., Li, Y., Gai, J., & Nguyen, H. T. (2017) · Compendium of plant genomes · doi:10.1007/978-3-319-64198-0_7

La investigación biomédica en la encrucijada y vías de salida

Pons, J. M. V., & Adam, P. (2018) · Medicina Clínica · doi:10.1016/j.medcli.2017.12.013

SimPEL: Simulation‐based power estimation for sequencing studies of low‐prevalence conditions

Mak, L. E., Li, M., Cao, C., Gordon, P. M. K., Tarailo‐Graovac, M., Bousman, C., Wang, P., & Long, Q. (2018) · Genetic Epidemiology · doi:10.1002/gepi.22129

A multiple regression method for genomewide association studies using only linkage information

Mei, B., & Wang, Z. (2018) · Journal of Genetics · doi:10.1007/s12041-018-0936-6

An INSIGHT OF PAKISTAN’S BIO-STATISTICAL PROFICIENCY IN PLANT HUSBANDRY SCIENCES

Ullah, R., Ullah, S., Khan, M. Z., Ullah, K., Saleem, F. Y., & Khattak, S. I. (2015)

Fine-tuned adaptation of embryo-endometrium pairs at implantation revealed by gene regulatory networks Tailored conceptus-maternal communication at implantationPreprint

Biase, F. H., Hue, I., Dickinson, S. E., Jaffrézic, F., Laloë, D., Lewin, H. A., & Sandra, O. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/427310

Short-Stay Palliative Pain Management for Southwestern VA

Rumsey, C. M. (2019) · Journal of Hospice and Palliative Nursing · doi:10.1097/njh.0000000000000549

Current progress and future direction in the genetics of PTSD: Focus on the development and contributions of the PGC-PTSD working group

Junglen, A. G., Sheerin, C. M., Delahanty, D. L., Hauser, M. A., Lori, A., Morey, R. A., Nievergelt, C. M., Nugent, N. R., Sebat, J. L., Smith, A. K., et al. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-813176-3.00023-7

Genotyping and Statistical Analysis

Lysenko, A., Boroevich, K. A., & Tsunoda, T. (2019) · Springer eBooks · doi:10.1007/978-981-13-8177-5_1

Pharmacogenetic biomarkers for chemotherapy-induced adverse drug reactions

Björn, N. (2019) · Linköping University medical dissertations · doi:10.3384/diss.diva-162138

Association Genetics and Local Adaptation of Populus trichocarpa Torr. & Gray

Chhetri, H. B. (2019) · The Research Repository @ WVU (West Virginia University) · doi:10.33915/etd.7478

A powerful MAF-neutral allele-based test for case-control association studiesPreprint

Jonker, M. A., & Pecanka, J. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2002.05048

Mechanisms of Gene Regulation in Alcoholism: Role of α-Synuclein in the Pathophysiology of Alcohol Misuse

Janeczek, P. (2016) · Griffith Research Online · doi:10.25904/1912/1266

Genetic analysis and epistatic interaction association of lipid traits in a C57xBalb/c F2 mice

Kumar, M., Srivastav, A. K., & Parmar, D. (2020) · Gene Reports · doi:10.1016/j.genrep.2020.100729

Clinical Pain Phenotyping for Omics Studies

Smith, S. B. (2020) · Springer eBooks · doi:10.1007/978-3-030-21657-3_5

Significance Thresholds for Rare Variant Signals

Greenwood, C. M. T., Xu, C., & Ciampi, A. (2015) · Springer eBooks · doi:10.1007/978-1-4939-2824-8_12 · Cited by 1

The Power of Gene-Based Rare Variant Methods to Detect Disease-Associated Variation and Test Hypotheses About Complex Disease

Moutsianas, L., Agarwala, V., Fuchsberger, C., Flannick, J. A., Rivas, M. A., Gaulton, K. J., Albers, P. K., McVean, G., Boehnke, M., Altshuler, D., et al. (2015) · PLoS Genetics · doi:10.1371/journal.pgen.1005165 · Cited by 135

Pooled Association Tests for Rare Genetic Variants: A Review and Some New Results

Derkach, A., Lawless, J. F., & Sun, L. (2014) · Statistical Science · doi:10.1214/13-sts456 · Cited by 78

Assessment of Pooled Association Tests for Rare Genetic Variants within a Unified FrameworkPreprint

Derkach, A., Lawless, J. F., & Sun, L. (2012) · arXiv (Cornell University) · Cited by 2

Power Analysis Provides Bounds for Genetic Architecture and Insights to Challenges for Rare Variant Association StudiesPreprint

Derkach, A., Zhang, H., & Chatterjee, N. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/100891 · Cited by 1