An evaluation of statistical approaches to rare variant analysis in genetic association studies

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

A haplotype map of the human genome

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

The Wellcome Trust Case Control Consortium, U.K.

Mossman, K. (2008) · Scientific American · doi:10.1038/scientificamerican0108-42a · Cited by 2,714

Genome-wide association defines more than 30 distinct susceptibility loci for Crohn's disease

the NIDDK IBD Genetics Consortium, Barrett, J. C., the Belgian-French IBD Consortium, the Wellcome Trust Case Control Consortium, Hansoul, S., Nicolae, D. L., Cho, J. H., Duerr, R. H., Rioux, J. D., Brant, S. R., et al. (2008) · Nature Genetics · doi:10.1038/ng.175 · Cited by 2,593

Generating samples under a Wright–Fisher neutral model of genetic variation

Hudson, R. R. (2002) · Bioinformatics · doi:10.1093/bioinformatics/18.2.337 · Cited by 2,397

Maximum-likelihood estimation of molecular haplotype frequencies in a diploid population.

(1995) · Molecular Biology and Evolution · doi:10.1093/oxfordjournals.molbev.a040269 · Cited by 1,950

Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes

Wellcome Trust Case Control Consortium, Zeggini, E., Scott, L. J., Saxena, R., Voight, B. F., Marchini, J. L., Hu, T., de Bakker, P. I., Abecasis, G. R., Almgren, P., et al. (2008) · Nature Genetics · doi:10.1038/ng.120 · Cited by 1,864

Six new loci associated with body mass index highlight a neuronal influence on body weight regulation

the GIANT Consortium (2009) · Nature Genetics · doi:10.1038/ng.287 · Cited by 1,720

Methods for Detecting Associations with Rare Variants for Common Diseases: Application to Analysis of Sequence Data

Li, B., & Leal, S. M. (2008) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2008.06.024 · Cited by 1,527

Multiple Rare Alleles Contribute to Low Plasma Levels of HDL Cholesterol

Cohen, J. C., Kiss, R. S., Pertsemlidis, A., Marcel, Y. L., McPherson, R., & Hobbs, H. H. (2004) · Science · doi:10.1126/science.1099870 · Cited by 1,108

Unraveling the biological mechanisms in Alzheimer's disease — Lessons from genomics

Borovečki, F., Klepac, N., Mück‐Šeler, D., Hajnšek, S., Mubrin, Z., & Pivac, N. (2010) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2010.12.019 · Cited by 16

A Unified Framework for Detecting Rare Variant Quantitative Trait Associations in Pedigree and Unrelated Individuals via Sequence Data

Liu, D. J., & Leal, S. M. (2012) · Human Heredity · doi:10.1159/000336293 · Cited by 15

A data-driven method for identifying rare variants with heterogeneous trait effects

Zhang, Q., Irvin, M. R., Arnett, D. K., Province, M. A., & Borecki, I. B. (2011) · Genetic Epidemiology · doi:10.1002/gepi.20618 · Cited by 16

Genetic Epidemiology and Public Health: The Evolution From Theory to Technology

Fallin, M. D., Duggal, P., & Beaty, T. H. (2016) · American Journal of Epidemiology · doi:10.1093/aje/kww001 · Cited by 15

‘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

A comprehensive evaluation of collapsing methods using simulated and real data: excellent annotation of functionality and large sample sizes required

Dering, C., König, I. R., Ramsey, L. B., Relling, M. V., Yang, W., & Ziegler, A. (2014) · Frontiers in Genetics · doi:10.3389/fgene.2014.00323 · Cited by 16

Rare-Variant Kernel Machine Test for Longitudinal Data from Population and Family Samples

Yan, Q., Weeks, D. E., Tiwari, H. K., Yi, N., Zhang, K., Gao, G., Lin, W., Lou, X., Chen, W., & Liu, N. (2015) · Human Heredity · doi:10.1159/000445057 · Cited by 15

A Flexible Approach for the Analysis of Rare Variants Allowing for a Mixture of Effects on Binary or Quantitative Traits

Clarke, G. M., Rivas, M. A., & Morris, A. P. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003694 · Cited by 15

Sequence Kernel Association Analysis of Rare Variant Set Based on the Marginal Regression Model for Binary Traits

Wu, B., Pankow, J. S., & Guan, W. (2015) · Genetic Epidemiology · doi:10.1002/gepi.21913 · Cited by 14

Assessment of rare BRCA1 and BRCA2 variants of unknown significance using hierarchical modeling

Capanu, M., CONCANNON, P. J., Haile, R. W., Bernstein, L., Malone, K. E., Lynch, C. F., Liang, X., Teraoka, S. N., Diep, A. T., Thomas, D. C., et al. (2011) · Genetic Epidemiology · doi:10.1002/gepi.20587 · Cited by 14

Exon sequencing and association analysis of EPHX1 genetic variants with maintenance warfarin dose in a multiethnic Asian population

Chan, S. L., Thalamuthu, A., Goh, B. C., Chia, K. S., Chuah, B., Wong, A. L., & Lee, S. C. (2010) · Pharmacogenetics and Genomics · doi:10.1097/fpc.0b013e328341b68f · Cited by 14

Genotype distribution-based inference of collective effects in genome-wide association studies: insights to age-related macular degeneration disease mechanism

Woo, H. J., Yu, C., Kumar, K., Gold, B., & Jaques Reifman, A. (2016) · BMC Genomics · doi:10.1186/s12864-016-2871-3 · Cited by 14

Identification of Grouped Rare and Common Variants via Penalized Logistic Regression

Ayers, K. L., & Cordell, H. J. (2013) · Genetic Epidemiology · doi:10.1002/gepi.21746 · Cited by 14

Longitudinal SNP‐set association analysis of quantitative phenotypes

Wang, Z., Xu, K., Zhang, X., Wu, X., & Wang, Z. (2016) · Genetic Epidemiology · doi:10.1002/gepi.22016 · Cited by 14

Methods and Tools in Genome-wide Association Studies

Gumpinger, A., Roqueiro, D., Grimm, D. G., & Borgwardt, K. M. (2018) · Methods in molecular biology · doi:10.1007/978-1-4939-8618-7_5 · Cited by 15

Population‐Based Case‐Control Association Studies

Hancock, D. B., & Scott, W. K. (2012) · Current Protocols in Human Genetics · doi:10.1002/0471142905.hg0117s74 · Cited by 14

Advantages of genotype imputation with ethnically matched reference panel for rare variant association analysesPreprint

Kals, M., Nikopensius, T., Läll, K., Pärn, K., Sikka, T. T., Suvisaari, J., Salomaa, V. V., Ripatti, S., Palotie, A. V., Metspalu, A., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/579201 · 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

A statistical framework for multi-trait rare variant analysis in large-scale whole-genome sequencing studies

Li, X., Chen, H., Selvaraj, M. S., Buren, E. V., Zhou, H., Wang, Y., Sun, R., McCaw, Z. R., Yu, Z., Jiang, M.-Z., et al. (2025) · Nature Computational Science · doi:10.1038/s43588-024-00764-8 · Cited by 13

Flexible and Robust Methods for Rare-Variant Testing of Quantitative Traits in Trios and Nuclear Families

Jiang, Y., Conneely, K. N., & Epstein, M. P. (2014) · Genetic Epidemiology · doi:10.1002/gepi.21839 · Cited by 13

Set‐based tests for genetic association in longitudinal studies

He, Z., Zhang, M., Lee, S., Smith, J. A., Guo, X., Palmas, W., Kardia, S. L. R., Roux, A. V. D., & Mukherjee, B. (2015) · Biometrics · doi:10.1111/biom.12310 · Cited by 13

Weighted selective collapsing strategy for detecting rare and common variants in genetic association study

Dai, Y., Jiang, R., & Dong, J. (2012) · BMC Genetics · doi:10.1186/1471-2156-13-7 · Cited by 14

A Variational Bayes Discrete Mixture Test for Rare Variant Association

Logsdon, B. A., Dai, J. Y., Auer, P. L., Johnsen, J. M., Ganesh, S. K., Smith, N. L., Wilson, J. G., Tracy, R. P., Lange, L. A., Jiao, S., et al. (2013) · Genetic Epidemiology · doi:10.1002/gepi.21772 · Cited by 13

Introduction to Deep Sequencing and Its Application to Drug Addiction Research with a Focus on Rare Variants

Wang, S., Yang, Z., Ma, J. Z., Payne, T. J., & Li, M. D. (2013) · Molecular Neurobiology · doi:10.1007/s12035-013-8541-4 · Cited by 13

A rare-variant test for high-dimensional data

Kaakinen, M., Mägi, R., Fischer, K., Heikkinen, J., Järvelin, M., Morris, A. P., & Prokopenko, I. (2017) · European Journal of Human Genetics · doi:10.1038/ejhg.2017.90 · Cited by 13

PSCAN: Spatial scan tests guided by protein structures improve complex disease gene discovery and signal variant detection

Tang, Z.-Z., Sliwoski, G. R., Chen, G., Jin, B., Bush, W. S., Li, B., & Capra, J. A. (2020) · Genome biology · doi:10.1186/s13059-020-02121-0 · Cited by 13

Understanding the immunological impact of the human mutation explosion

Andrews, T. D., Sjollema, G., & Goodnow, C. C. (2013) · Trends in Immunology · doi:10.1016/j.it.2012.12.001 · Cited by 14

Association Testing of Clustered Rare Causal Variants in Case-Control Studies

Lin, W. (2014) · PLoS ONE · doi:10.1371/journal.pone.0094337 · Cited by 13

A new multivariate test formulation: theory, implementation, and applications to genome-scale sequencing and expression

Xu, L. (2016) · Applied Informatics · doi:10.1186/s40535-015-0016-4 · Cited by 13

Gene-Based Association Analysis for Censored Traits Via Fixed Effect Functional Regressions

Fan, R., Wang, Y., Yan, Q., Ding, Y., Weeks, D. E., Lu, Z., Ren, H., Cook, R. J., Xiong, M., Swaroop, A., et al. (2016) · Genetic Epidemiology · doi:10.1002/gepi.21947 · Cited by 13

Identifying individual risk rare variants using protein structure guided local tests (POINT)

West, R. M., Lu, W., Rotroff, D. M., Kuenemann, M. A., Chang, S., Wu, M. C., Wagner, M. J., Buse, J. B., Motsinger‐Reif, A. A., Fourches, D., et al. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006722 · Cited by 13

Investigation of Exomic Variants Associated with Overall Survival in Ovarian Cancer

Winham, S. J., Ewing, A., Chen, Y. A., Larson, M. C., Fogarty, Z. C., Earp, M. A., Anton‐Culver, H., Bandera, E. V., Cramer, D. W., Doherty, J. A., et al. (2016) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-15-0240 · Cited by 13

The role of genomics and genetics in pulmonary arterial hypertension

Swietlik, E. M., Gräf, S., & Morrell, N. W. (2020) · Global Cardiology Science and Practice · doi:10.21542/gcsp.2020.13 · Cited by 14

FiMAP: A fast identity-by-descent mapping test for biobank-scale cohorts

Chen, H., Naseri, A., & Zhi, D. (2023) · PLoS Genetics · doi:10.1371/journal.pgen.1011057 · Cited by 12

On the Aggregation of Multimarker Information for Marker-Set and Sequencing Data Analysis: Genotype Collapsing vs. Similarity Collapsing

Pongpanich, M., Neely, M. L., & Tzeng, J. (2012) · Frontiers in Genetics · doi:10.3389/fgene.2011.00110 · Cited by 12

On Sample Size and Power Calculation for Variant Set‐Based Association Tests

Wu, B., & Pankow, J. S. (2016) · Annals of Human Genetics · doi:10.1111/ahg.12147 · Cited by 12

A biologically informed method for detecting rare variant associations

Moore, C., Basile, A. O., Wallace, J. R., Frase, A., & Ritchie, M. D. (2016) · BioData Mining · doi:10.1186/s13040-016-0107-3 · Cited by 12

Rapid and Robust Resampling-Based Multiple-Testing Correction with Application in a Genome-Wide Expression Quantitative Trait Loci Study

Zhang, X., Huang, S., Sun, W., & Wang, W. W. (2012) · Genetics · doi:10.1534/genetics.111.137737 · Cited by 12

Rare LPL gene variants attenuate triglyceride reduction and HDL cholesterol increase in response to fenofibric acid therapy in individuals with mixed dyslipidemia

Gao, F., Ballantyne, C. M., Ma, L., Virani, S. S., Keinan, A., & Brautbar, A. (2014) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2014.03.010 · Cited by 12

SEQSpark: A Complete Analysis Tool for Large-Scale Rare Variant Association Studies Using Whole-Genome and Exome Sequence Data

Zhang, D., Zhao, L., Li, B., He, Z., Wang, G. T., Liu, D. J., & Leal, S. M. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.05.017 · Cited by 14

Imputation of Rare Variants in Next-Generation Association Studies

Asimit, J. L., & Zeggini, E. (2012) · Human Heredity · doi:10.1159/000345602 · Cited by 12

A Comparison Study of Fixed and Mixed Effect Models for Gene Level Association Studies of Complex Traits

Fan, R., Chiu, C., Jung, J., Weeks, D. E., Wilson, A. F., Wilson, J., Amos, C. I., Chen, Z., Mills, J. L., & Xiong, M. (2016) · Genetic Epidemiology · doi:10.1002/gepi.21984 · Cited by 12

Statistical Challenges in Sequence-Based Association Studies with Population- and Family-Based Designs

Ionita‐Laza, I., Cho, M. H., & Laird, N. M. (2012) · Statistics in Biosciences · doi:10.1007/s12561-012-9062-9 · Cited by 11

A Linkage Disequilibrium–Based Approach to Selecting Disease-Associated Rare Variants

Talluri, R., & Shete, S. S. (2013) · PLoS ONE · doi:10.1371/journal.pone.0069226 · Cited by 11

Comparison of statistical approaches to rare variant analysis for quantitative traits

Chen, H., Hendricks, A. E., Cheng, Y., Cupples, L. A., Dupuis, J., & Liu, C. (2011) · BMC Proceedings · doi:10.1186/1753-6561-5-s9-s113 · Cited by 11

Logistic Principal Component Analysis for Rare Variants in Gene-Environment Interaction Analysis

Lu, M., Lee, H., Hadley, D., Huang, J. Z., & Qian, X. (2014) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2014.2322371 · Cited by 11

Model-Based Multifactor Dimensionality Reduction for Rare Variant Association Analysis

Fouladi, R., Bessonov, K., Lishout, F. V., & Steen, K. V. (2015) · Human Heredity · doi:10.1159/000381286 · Cited by 13

Old lessons learned anew: family-based methods for detecting genes responsible for quantitative and qualitative traits in the Genetic Analysis Workshop 17 mini-exome sequence data

Simpson, C. L., Justice, C. M., Krishnan, M., Wojciechowski, R., Sung, H., Cai, J., Green, T., Lewis, D. D., Behneman, D., Wilson, A. F., et al. (2011) · BMC Proceedings · doi:10.1186/1753-6561-5-s9-s83 · Cited by 11

The Role of Rare Variants in Systolic Blood Pressure: Analysis of ExomeChip Data in HyperGEN African Americans

Sung, Y. J., Basson, J., Cheng, N., Nguyen, K.-D. H., Nandakumar, P., Hunt, S. C., Arnett, D. K., Dávila‐Román, V. G., Rao, D. C., & Chakravarti, A. (2015) · Human Heredity · doi:10.1159/000375373 · Cited by 11

Assessing the impact of missing genotype data in rare variant association analysis

Mägi, R., Kumar, A., & Morris, A. P. (2011) · BMC Proceedings · doi:10.1186/1753-6561-5-s9-s107 · Cited by 11

Meta-Analysis of Common and Rare Variants

Michailidou, K. (2018) · Methods in molecular biology · doi:10.1007/978-1-4939-7868-7_6 · Cited by 11

Stabilized Sparse Online Learning for Sparse DataPreprint

Ma, Y., & Zheng, T. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1604.06498 · Cited by 11

Comparison of Statistical Tests for Association between Rare Variants and Binary Traits

Bacanu, S., Nelson, M. R., & Whittaker, J. C. (2012) · PLoS ONE · doi:10.1371/journal.pone.0042530 · Cited by 11

Integrated Quantile RAnk Test (iQRAT) for gene-level associations

Wang, T., Ionita‐Laza, I., & Wei, Y. (2022) · The Annals of Applied Statistics · doi:10.1214/21-aoas1548 · Cited by 10

Gene-based association study of rare variants in children of diverse ancestries implicates TNFRSF21 in the development of allergic asthma

Clay, S. M., Alladina, J. W., Smith, N. P., Visness, C. M., Wood, R. A., O’Connor, G. T., Cohen, R. T., Hershey, G. K. K., Kercsmar, C. M., Gruchalla, R. S., et al. (2023) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2023.10.023 · Cited by 12

Adaptive Ridge Regression for Rare Variant Detection

Zhan, H., & Xu, S. (2012) · PLoS ONE · doi:10.1371/journal.pone.0044173 · Cited by 11

Comparison of genetic association strategies in the presence of rare alleles

John, J. M., Cattaert, T., Lobel, L. D., Lishout, F. V., Empain, A., & Steen, K. V. (2011) · BMC Proceedings · doi:10.1186/1753-6561-5-s9-s32 · Cited by 10

Evaluating methods for combining rare variant data in pathway-based tests of genetic association

Petersen, A. J., Sitarik, A. R., Luedtke, A. R., Powers, S., Bekmetjev, A., & Tintle, N. (2011) · BMC Proceedings · doi:10.1186/1753-6561-5-s9-s48 · Cited by 10

Evaluation of pooled association tests for rare variant identification

Lin, W., Zhang, B., Yi, N., Gao, G., & Liu, N. (2011) · BMC Proceedings · doi:10.1186/1753-6561-5-s9-s118 · Cited by 10

A flexible likelihood framework for detecting associations with secondary phenotypes in genetic studies using selected samples: application to sequence data

Liu, D. J., & Leal, S. M. (2011) · European Journal of Human Genetics · doi:10.1038/ejhg.2011.211 · Cited by 10

Statistical Techniques for Genetic Analysis

Lasky-Su, J. A. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-802101-9.00019-3 · Cited by 12

Comparison of single-marker and multi-marker tests in rare variant association studies of quantitative traits

Konigorski, S., Yilmaz, Y. E., & Pischon, T. (2017) · PLoS ONE · doi:10.1371/journal.pone.0178504 · Cited by 10

GxGrare: gene-gene interaction analysis method for rare variants from high-throughput sequencing data

Kwon, M., Leem, S., Yoon, J. H., & Park, T. (2018) · BMC Systems Biology · doi:10.1186/s12918-018-0543-4 · Cited by 10

A generalized model for combining dependent SNP-level summary statistics and its extensions to statistics of other levels

Svishcheva, G. R. (2019) · Scientific Reports · doi:10.1038/s41598-019-41827-5 · Cited by 10

Are quantitative trait-dependent sampling designs cost-effective for analysis of rare and common variants?

Yilmaz, Y. E., & Bull, S. B. (2011) · BMC Proceedings · doi:10.1186/1753-6561-5-s9-s111 · Cited by 10

False Discovery Rates for Rare Variants From Sequenced Data

Capanu, M., & Seshan, V. (2014) · Genetic Epidemiology · doi:10.1002/gepi.21880 · Cited by 10

Rare and Low-Frequency Variants in RNF213 Confer Susceptibility to Moyamoya Syndrome Associated with Hyperthyroidism

Nomura, S., Akagawa, H., Yamaguchi, K., Ishikawa, T., Kawashima, A., Kasuya, H., Mukawa, M., Nariai, T., Maehara, T., Okada, Y., et al. (2019) · World Neurosurgery · doi:10.1016/j.wneu.2019.03.172 · Cited by 10

Testing Genetic Association With Rare and Common Variants in Family Data

Chen, H., Malzahn, D., Balliu, B., Li, C., & Bailey, J. N. (2014) · Genetic Epidemiology · doi:10.1002/gepi.21823 · Cited by 9

Mutation analysis of RAD51L1 (RAD51B/REC2) in multiple-case, non-BRCA1/2 breast cancer families

kConFab, Johnson, J., Healey, S. C., Khanna, K. K., & Chenevix‐Trench, G. (2011) · Breast Cancer Research and Treatment · doi:10.1007/s10549-011-1539-6 · Cited by 10

Evaluating the impact of genotype errors on rare variant tests of association

Cook, K. A., Benitez, A., Fu, C. L., & Tintle, N. (2014) · Frontiers in Genetics · doi:10.3389/fgene.2014.00062 · Cited by 9

Localization of Association Signal from Risk and Protective Variants in Sequencing Studies

Brisbin, A. G., Jenkins, G. D., Ellsworth, K. A., Wang, L., & Fridley, B. L. (2012) · Frontiers in Genetics · doi:10.3389/fgene.2012.00173 · Cited by 9

Linear mixed models for association analysis of quantitative traits with next‐generation sequencing data

Chiu, C., Yuan, F., Zhang, B., Yuan, A., Li, X., Fang, H., Lange, K. L., Weeks, D. E., Wilson, A. F., Wilson, J., et al. (2018) · Genetic Epidemiology · doi:10.1002/gepi.22177 · Cited by 9

Novel directions in data pre-processing and genome-wide association study (GWAS) methodologies to overcome ongoing challenges

Mortezaei, Z., & Tavallaei, M. (2021) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2021.100586 · Cited by 9

Consideration of plausible genetic architectures for schizophrenia and implications for analytic approaches in the era of next generation sequencing

Curtis, D. (2012) · Psychiatric Genetics · doi:10.1097/ypg.0b013e32835d7e5a · Cited by 10

Gene-set association tests for next-generation sequencing data

Lee, J., Kim, Y. J., Lee, J., Kim, B.-J., Lee, S., & Park, T. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw429 · Cited by 9

Illustrating, Quantifying, and Correcting for Bias in Post-hoc Analysis of Gene-Based Rare Variant Tests of Association

Grinde, K. E., Arbet, J., Green, A., O’Connell, M. J., Valcarcel, A. M., Westra, J., & Tintle, N. (2017) · Frontiers in Genetics · doi:10.3389/fgene.2017.00117 · Cited by 9

Stage 2 Registered Report: Variation in neurodevelopmental outcomes in children with sex chromosome trisomies: testing the double hit hypothesis

Newbury, D. F., Simpson, N. H., Thompson, P. A., & Bishop, D. (2018) · Wellcome Open Research · doi:10.12688/wellcomeopenres.14677.2 · Cited by 9

Use of Bayesian networks to dissect the complexity of genetic disease: application to the Genetic Analysis Workshop 17 simulated data

Kang, J., Zheng, W., Li, L., Lee, J. S., Yan, X., & Zhao, H. (2011) · BMC Proceedings · doi:10.1186/1753-6561-5-s9-s37 · Cited by 8

Network-guided search for genetic heterogeneity between gene pairs

Gumpinger, A., Rieck, B., Grimm, D. G., & Borgwardt, K. M. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btaa581 · Cited by 8

Rare variant association on unrelated individuals in case–control studies using aggregation tests: existing methods and current limitations

Boutry, S., Helaers, R., Lenaerts, T., & Vikkula, M. (2023) · Briefings in Bioinformatics · doi:10.1093/bib/bbad412 · Cited by 8

Effects of endocrine disrupting chemicals and their interactions with genetic risk scores on cardiometabolic traits

Lu, X., Xie, T., van Faassen, M. H. J. R., Kema, I. P., van Beek, A. P., Xu, X., Huo, X., Wolffenbuttel, B. H. R., van Vliet‐Ostaptchouk, J. V., Nolte, I. M., et al. (2024) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2024.169972 · Cited by 8

A methodology for gene level omics-WAS integration identifies genes influencing traits associated with cardiovascular risks: the Long Life Family Study

Acharya, S., Liao, S., Jung, W. J., Kang, Y. S., Moghaddam, V. A., Feitosa, M. F., Wojczynski, M. K., Lin, S. J., Anema, J. A., Schwander, K., et al. (2024) · Human Genetics · doi:10.1007/s00439-024-02701-1 · Cited by 8

α1-Antitrypsin Gene Variation Associates With Asthma Exacerbations and Related Health Care Utilization

Ortega, V. E., Tejwani, V., Shrivastav, A. K., Pasha, S. N., Zein, J., Boorgula, M. P., Castro, M., Denlinger, L. C., ERZURUM, S. C., Fahy, J. V., et al. (2025) · The Journal of Allergy and Clinical Immunology In Practice · doi:10.1016/j.jaip.2025.01.039 · Cited by 8

Assessing the Contribution Family Data Can Make to Case-Control Studies of Rare Variants

Curtis, D. (2011) · Annals of Human Genetics · doi:10.1111/j.1469-1809.2011.00660.x · Cited by 8

Hierarchical Bayesian Model for Rare Variant Association Analysis Integrating Genotype Uncertainty in Human Sequence Data

He, L., Pitkäniemi, J. M., Sarin, A., Salomaa, V. V., Sillanpää, M. J., & Ripatti, S. (2014) · Genetic Epidemiology · doi:10.1002/gepi.21871 · Cited by 8

Kernel machine regression in neuroimaging genetics

Ge, T., Smoller, J. W., & Sabuncu, M. R. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-804076-8.00002-5 · Cited by 8

Comparing family-based rare variant association tests for dichotomous phenotypes

Wang, L., Choi, S., Lee, S., Park, T., & Won, S. (2016) · BMC Proceedings · doi:10.1186/s12919-016-0027-8 · Cited by 8

Adaptive combination of Bayes factors as a powerful method for the joint analysis of rare and common variants

Lin, W., Chen, W. J., Liu, C., Hwu, H., McCarroll, S. A., Glatt, S. J., & Tsuang, M. T. (2017) · Scientific Reports · doi:10.1038/s41598-017-13177-7 · Cited by 8

Weighted functional linear regression models for gene-based association analysis

Belonogova, N. M., Svishcheva, G. R., Wilson, J. F., Campbell, H. J., & Axenovich, T. I. (2018) · PLoS ONE · doi:10.1371/journal.pone.0190486 · Cited by 8

Examining the overlap between genome-wide rare variant association signals and linkage peaks in rheumatoid arthritis

Eyre, S., Ke, X., Lawrence, R., Bowes, J., Panoutsopoulou, K., Barton, A. C., Thomson, W., Worthington, J., & Zeggini, E. (2011) · Arthritis & Rheumatism · doi:10.1002/art.30315 · Cited by 8

Collapsing-based and kernel-based single-gene analyses applied to Genetic Analysis Workshop 17 mini-exome data

Li, L., Zheng, W., Lee, J. S., Zhang, X., Ferguson, J. P., Yan, X., & Zhao, H. (2011) · BMC Proceedings · doi:10.1186/1753-6561-5-s9-s117 · Cited by 8

SEQCHIP: a powerful method to integrate sequence and genotype data for the detection of rare variant associations

Liu, D. J., & Leal, S. M. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts263 · Cited by 8

Two-stage study designs combining genome-wide association studies, tag single-nucleotide polymorphisms, and exome sequencing: accuracy of genetic effect estimates

Faye, L. L., & Bull, S. B. (2011) · BMC Proceedings · doi:10.1186/1753-6561-5-s9-s64 · Cited by 8

Gene‐based sequential burden association test

Chen, Z., & Wang, K. (2019) · Statistics in Medicine · doi:10.1002/sim.8111 · Cited by 8

Adjusting Family Relatedness in Data-driven Burden Test of Rare Variants

Zhang, Q., Wang, L., Koboldt, D., Borecki, I. B., & Province, M. A. (2014) · Genetic Epidemiology · doi:10.1002/gepi.21848 · Cited by 8

Strategies in Aggregation Tests for Rare Variants

Rajabli, F., & Kunkle, B. W. (2023) · Current Protocols · doi:10.1002/cpz1.931 · Cited by 8

Trans-Ancestral Genetic Risk Factors for Treatment-Related Type 2 Diabetes Mellitus in Survivors of Childhood Cancer

Im, C., Neupane, A., Baedke, J. L., Lenny, B., Delaney, A., Dixon, S. B., Chow, E. J., Mostoufi‐Moab, S., Yang, T., Richard, M. A., et al. (2024) · Journal of Clinical Oncology · doi:10.1200/jco.23.02281 · Cited by 7

Whole-exome sequencing and Drosophila modelling reveal mutated genes and pathways contributing to human ovarian failure

Henarejos-Castillo, I., Sanz, F., Solana‐Manrique, C., Sebastián-León, P., Medina, I., Remohi, J., Sr., Paricio, N., & Díaz-Gimeno, P. (2024) · Reproductive Biology and Endocrinology · doi:10.1186/s12958-024-01325-4 · Cited by 7

Joint Association Testing of Common and Rare Genetic Variants Using Hierarchical Modeling

Cardin, N. J., Mefford, J., & Witte, J. S. (2012) · Genetic Epidemiology · doi:10.1002/gepi.21659 · Cited by 7

A scan statistic to extract causal gene clusters from case-control genome-wide rare CNV data

Nishiyama, T., Takahashi, K., Tango, T., Pinto, D., Scherer, S. W., Takami, S., & Kishino, H. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-205 · Cited by 7

Statistical analysis strategies for association studies involving rare variants

Bansal, V., Libiger, O., Torkamani, A., & Schork, N. J. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2867 · Cited by 455

Identifying Rare Variants Associated with Complex Traits via Sequencing

Li, B., Liu, D. J., & Leal, S. M. (2013) · Current Protocols in Human Genetics · doi:10.1002/0471142905.hg0126s78 · Cited by 41

Rare-variant collapsing analyses for complex traits: guidelines and applications

Povysil, G., Petrovski, S., Hostyk, J. A., Aggarwal, V. S., Allen, A. S., & Goldstein, D. B. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0177-4 · Cited by 211

Rare-Variant Genome-Wide Association Studies: A New Frontier in Genetic Analysis of Complex Traits

Wagner, M. J. (2013) · Pharmacogenomics · doi:10.2217/pgs.13.36 · Cited by 42

Methodology for the analysis of rare genetic variation in genome-wide association and re-sequencing studies of complex human traits

Moutsianas, L., & Morris, A. P. (2014) · Briefings in Functional Genomics · doi:10.1093/bfgp/elu012 · Cited by 20