The DOI matches its Crossref record; 64 of the 65 references it cites were found in a registry or an index.
Searching for missing heritability: Designing rare variant association studies
Open accessAbstract
Significance: Discovering the genetic basis of common diseases, such as diabetes, heart disease, and schizophrenia, is a key goal in biomedicine. Genomic studies have revealed thousands of common genetic variants underlying disease, but these variants explain only a portion of the heritability. Rare variants are also likely to play an important role, but few examples are known thus far, and initial discovery efforts with small sample sizes have had only limited success. In this paper, we describe an analytical framework for the design of rare variant association studies of disease. It provides guidance with respect to sample size, as well as the roles of selection, disruptive and missense alleles, gene-specific allele frequency thresholds, isolated populations, gene sets, and coding vs. noncoding regions.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“However, the analysis of URVs has had limited success in delivering individual gene discovery in schizophrenia because of power limitations, with only a single gene, SETD1A, identified as robustly associated 13,18 .”
From Exome sequencing identifies rare coding variants in 10 genes which confer substantial risk for schizophrenia (2020) · cites this paper as [13]
In the citing paper
“The most natural grouping for rare variants is within a gene, based on predicted functional consequence or evidence for deleteriousness 13,14 .”
From Exome sequencing identifies rare coding variants in 10 genes which confer substantial risk for schizophrenia (2020) · cites this paper as [13]
In the citing paper
“Theory predicts that the forces of natural selection will tend to keep large effect risk variants at much lower frequencies in the population, especially in disorders such as schizophrenia that are associated with reduced fecundity 13 .”
From Exome sequencing identifies rare coding variants in 10 genes which confer substantial risk for schizophrenia (2020) · cites this paper as [13]
In the citing paper
“Because individuals affected with schizophrenia have fewer offspring, purifying selection is expected to prevent high-risk alleles from reaching even modest allele frequencies6.”
From Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia (2016) · cites this paper as [6]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A method and server for predicting damaging missense mutations.
Adzhubei, I. A., Schmidt, S., Peshkin, L., Ramensky, V. E., Gerasimova, A., Bork, P., Kondrashov, A. S., & Sunyaev, S. R. (2010) · Nature Methods · doi:10.1038/nmeth0410-248 · Cited by 13,194
Self-citationFinding the missing heritability of complex diseases
Manolio, T. A., Collins, F. S., Cox, N. J., Goldstein, D. B., Hindorff, L. A., Hunter, D. J., McCarthy, M. I., Ramos, E. M., Cardon, L. R., Chakravarti, A., et al. (2009) · Nature · doi:10.1038/nature08494 · Cited by 8,336
Mapping mendelian factors underlying quantitative traits using RFLP linkage maps.
Lander, E. S., & Botstein, D. (1989) · Genetics · doi:10.1093/genetics/121.1.185 · Cited by 5,236
Self-citationCommon SNPs explain a large proportion of the heritability for human height
Yang, J., Benyamin, B., McEvoy, B. P., Gordon, S., Henders, A. K., Nyholt, D. R., Madden, P. A., Heath, A. C., Martin, N. G., Montgomery, G. W., et al. (2010) · Nature Genetics · doi:10.1038/ng.608 · Cited by 4,446
Biological, clinical and population relevance of 95 loci for blood lipids
Teslovich, T. M., Musunuru, K., Smith, A. V., Edmondson, A. C., Stylianou, I. M., Koseki, M., Pirruccello, J. P., Ripatti, S., Chasman, D. I., Willer, C. J., et al. (2010) · Nature · doi:10.1038/nature09270 · Cited by 3,487
Self-citationSequence Variations in PCSK9, Low LDL, and Protection against Coronary Heart Disease
Cohen, J. C., Boerwinkle, E., Mosley, T. H., & Hobbs, H. H. (2006) · New England Journal of Medicine · doi:10.1056/nejmoa054013 · Cited by 3,181
THE NUMBER OF ALLELES THAT CAN BE MAINTAINED IN A FINITE POPULATION
Kimura, M., & Crow, J. F. (1964) · Genetics · doi:10.1093/genetics/49.4.725 · Cited by 2,621
Rare-Variant Association Testing for Sequencing Data with the Sequence Kernel Association Test
Wu, M. C., Lee, S., Cai, T., Li, Y., Boehnke, M., & Lin, X. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.05.029 · Cited by 2,373
Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations
O’Roak, B. J., Vives, L., Girirajan, S., Karakoc, E., Krumm, N., Coe, B. P., Levy, R., Ko, A., Lee, C., Smith, J. D., et al. (2012) · Nature · doi:10.1038/nature10989 · Cited by 2,165 · cited 2×
“For example, CHD8 was associated with autism with mental retardation (prevalence < 1/300) (52) based on the observation of de novo disruptive mutations in 3 of 1,078 cases (53, 54).”
Background
Cited by
Sorted by citations
Items 501–600 of 636
Systematic Cell-Based Phenotyping of Missense Alleles
Thormaehlen, A. S., & Runz, H. (2017) · Methods in molecular biology · doi:10.1007/978-1-4939-6960-9_17 · Cited by 1
DNA Markers Evaluation to Preparing a Genetic Database for Identification in Crimes and Incidents
Mohammadi, A., & Ramezani, M. (2018) · International Journal of Medical Reviews · doi:10.29252/ijmr-050202 · Cited by 1
Ito, S., Yadome, M., Nishiki, T., Ishiduki, S., Inoue, H., Yamaguchi, R., & Miyano, S. (2018) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm.2018.8621285 · Cited by 1
From human genome epidemiology to systems epidemiology: current progress and future perspective
Ma, H., & Shen, H. (2020) · Journal of Biomedical Research · doi:10.7555/jbr.34.20200027 · Cited by 1
The natural history of defences
Schmid‐Hempel, P. (2021) · Oxford University Press eBooks · doi:10.1093/oso/9780198832140.003.0004 · Cited by 1
DNA sequencing and other methods of exonic and genomic analyses
Mitsui, J., Ishiura, H., & Tsuji, S. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-813955-4.00008-8 · Cited by 2
Wang, J., Zhou, F., Li, C., Yin, N., Liu, H., Zhuang, B., Huang, Q., & Wen, Y. (2023) · Genes · doi:10.3390/genes14040834 · Cited by 1
How Early Domestication and Modern Genomics Contribute to Camel Welfare
Ciani, E., Burger, P. A., Zappaterra, M., & Pastrana, C. I. (2024) · Animal welfare · doi:10.1007/978-3-031-48600-5_2 · Cited by 1
An expression-directed linear mixed model discovering low-effect genetic variants
Li, Q., Bian, J., Qian, Y., Kossinna, P., Gau, C., Gordon, P. M. K., Zhou, X., Guo, X., Yan, J. Y., Wu, J., et al. (2024) · Genetics · doi:10.1093/genetics/iyae018 · Cited by 1
Using gene and gene-set association tests to identify lethal prostate cancer genes
Feng, B., Boyle, J. L., Wei, J., Carroll, C., Snyder, N. A., Shi, Z., Zheng, S. L., Xu, J., Isaacs, W. B., & Cooney, K. A. (2024) · Prostate Cancer and Prostatic Diseases · doi:10.1038/s41391-024-00879-z · Cited by 1
Darbani, B., & Nicolaisen, M. (2026) · BMC Bioinformatics · doi:10.1186/s12859-026-06464-6 · Cited by 1
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
Assessment of a glyoxalase I frameshift variant, p.P122fs, in Japanese patients with schizophrenia
Ishizuka, K., Kimura, H., Kushima, I., Inada, T., Okahisa, Y., Ikeda, M., Iwata, N., Mori, D., Aleksić, B., & Ozaki, N. (2018) · Psychiatric Genetics · doi:10.1097/ypg.0000000000000204 · Cited by 1
Basic Genetics and Epigenetics of Childhood Lung Disease
Wambach, J., Chaudhari, B. P., & Hamvas, A. (2019) · Elsevier eBooks · doi:10.1016/b978-0-323-44887-1.00003-1 · Cited by 1
Hsieh, A., Chen, L.-S., Li, Y.-J., & Fann, C. S. J. (2019) · Psychiatric Genetics · doi:10.1097/ypg.0000000000000227 · Cited by 1
Rivas, M. A., Cho, J. H., McGovern, D. P. B., & Daly, M. J. (2017) · Gastroenterology · doi:10.1016/s0016-5085(17)33337-1 · Cited by 1
Self-citationCorvin, A. P., Ormond, C., & Cole, A. M. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-813176-3.00015-8 · Cited by 1
VCSEL: Prioritizing SNP-set by penalized variance component selection
Kim, J., Shen, J., Wang, A., Mehrotra, D. V., Ko, S., Zhou, J. J., & Zhou, H. (2021) · The Annals of Applied Statistics · doi:10.1214/21-aoas1491 · Cited by 1
Schmid‐Hempel, P. (2021) · Oxford University Press eBooks · doi:10.1093/oso/9780198832140.003.0007 · Cited by 1
Genetic and Biological Influences
Skuse, D. (2017) · Wiley eBooks · doi:10.1002/9781119170235.ch4 · Cited by 1
Minică, C. C., Genovese, G., Hultman, C. M., Pool, R., Vink, J. M., Dolan, C. V., & Neale, B. M. (2015) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/020198 · Cited by 1
Self-citationExploring molecular links between obesity and breast cancer.
Crake, R. (2015) · Otago University Research Archive (University of Otago) · Cited by 1
Derkach, A., Zhang, H., & Chatterjee, N. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/100891 · Cited by 1
Exome sequencing identifies high-impact trait-associated alleles enriched in FinnsPreprint
Locke, A. E., Steinberg, K. M., Chiang, C. W., Service, S. K., Havulinna, A. S., Stell, L., Pirinen, M., Abel, H., Chiang, C., Fulton, R. S., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/464255 · Cited by 1
Detection of rare disease-related genetic variants using the birthday modelPreprint
Berstein, Y., McCarthy, S., Kramer, M., & McCombie, W. R. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/464842 · Cited by 1
Cheng, W., Ramachandran, S., & Crawford, L. A. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/597484 · 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
Mapping Genetic Interactions for Rare Disease-Associated Genes
Kantautas, K. (2020) · TSpace (University of Toronto) · Cited by 1
Robinson, E. (2021) · Biological Psychiatry · doi:10.1016/j.biopsych.2020.12.018 · Cited by 1
Liu, J., Copland, D. A., Clare, A. J., Gorski, M., Richards, B. T., Scott, L. M., Theodoropoulou, S., Greferath, U., Cox, K. H. M., Bell, O. H., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.09.27.559733 · Cited by 1
Mapping rare protein-coding variants on multi-organ imaging traitsPreprint
Fan, Y., Chen, J., Fan, Z., Chirinos, J. A., Stein, J. L., Sullivan, P. F., Wang, R., Nadig, A., Zhang, D. Y., Huang, S., et al. (2024) · medRxiv · doi:10.1101/2024.11.16.24317443 · Cited by 1
CLUSTERING OF RARE VARIANTS FOR CAUSAL VARIANTS IDENTIFICATION AND EFFECT DIRECTION CLASSIFICATIONPreprint
Sun, X., Liu, X., & Liu, C. (2024) · medRxiv · doi:10.1101/2024.02.22.24303151 · Cited by 1
Understanding Risk Aversion in Older Americans: New Approaches Using Genetic Data
Harrati, A. (2014) · eScholarship (California Digital Library) · Cited by 1
A Permutation Test for Oligoset DNA Pooling Studies
Huang, H.-Y., Lin, J., & Lee, W. (2015) · PLoS ONE · doi:10.1371/journal.pone.0119096
expression across multiple tissues from RNA-seq read data
Pirinen, M., Lappalainen, T., Zaitlen, N., Dermitzakis, E. T., Donnelly, P., McCarthy, M. I., & Rivas, M. A. (2014)
Inactivating Mutations in NPC1L1 and Protection from Coronary Heart Disease
Lander, E. S. (2014) · DSpace@MIT (Massachusetts Institute of Technology)
Self-citationAas, M., Blokland, G. A. M., Chawner, S. J. R. A., Choi, S. W., Estrada, J., Forsingdal, A., Friedrich, M. U., Ganesham, S., Hall, L. S., Haslinger, D., et al. (2015) · Psychiatric Genetics · doi:10.1097/ypg.0000000000000112
The Roles of Iddm30 and Iddm24 in the Immunopathogenesis of Type 1 Diabetes in BioBreeding Rats
Chao, Y.-C. G. (2015) · TSpace (University of Toronto)
Understanding the Genetic Etiology of Complex Phenotypes using Bayesian Neural Networks
Beam, A. L. (2014) · NCSU Libraries Repository (North Carolina State University Libraries)
Genome-Wide Association Studies of Quantitative Glycaemic Traits
Barroso, I., & Scott, R. A. (2016) · Springer eBooks · doi:10.1007/978-3-319-01574-3_3 · Cited by 1
Corvin, A. P. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-800105-9.00027-5
Nature or Nurture? Heritability in the Classroom
Hiramatsu, L., & Garland, T. (2016) · Physiological and Biochemical Zoology · doi:10.1086/688289
Novel insights into the genetic basis of chronic obstructive pulmonary disease
Radder, J. E. (2016) · D-Scholarship@Pitt (University of Pittsburgh)
Familial Studies in Whole Exome and Genome Sequencing
Farlow, J. L. (2015) · IUScholarWorks (Indiana University) · doi:10.7912/c2/1958
Genetic and Genomic Approaches to Acute Lung Injury
Yang, I. V. (2016) · Respiratory medicine · doi:10.1007/978-3-319-46527-2_9
Family-Based Genetic Association Analysis: Methods and Applications to Addiction Phenotypes
Minică, C. C. (2012) · Digital Academic REpository of VU University Amsterdam (Vrije Universiteit Amsterdam)
Psychiatric Disorders: The Search for Genes
McMahon, F. J. (2017) · Wiley eBooks · doi:10.1002/9780470015902.a0005418.pub2
«Vanishing heritability» – a new paradox in the context of an old problem
Марютина, Т. М. (2016) · Journal of Modern Foreign Psychology · doi:10.17759/jmfp.2016050401
Evolutionary and functional data power search for obsessive-compulsive disorder genesPreprint
Noh, H. J., Tang, R., Flannick, J. A., O’Dushlaine, C. T., Swofford, R., Howrigan, D. P., Genereux, D. P., Johnson, J., van Grootheest, G., Grünblatt, E., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/107193
Human AGT -p.Met268Thr and coronary heart disease risk: a case-control study and meta-analysis
Mohammadi, H., Razavi, N. S., Abbasi, A. A., Babaei, F., Seyedrezazadeh, E., & Colagar, A. H. (2018) · Family Medicine & Primary Care Review · doi:10.5114/fmpcr.2018.73699
Identification of Pre-eclampsia susceptibility genes
Gokhale-Agashe, D. (2018) · UWA Profiles and Research Repository (UWA) · doi:10.4225/23/5abc48e7391bc
Genetic Interactions and Complex Human Diseases
Wang, W. (2017) · University of Minnesota Digital Conservancy (University of Minnesota)
Genetic epidemiology of cardiometabolic biomarkers : twin studies in the genomic era
Chen, X. (2018) · Figshare
Narang, A., Bhattacharya, A., Mukerji, M., & Dash, D. (2018) · Springer eBooks · doi:10.1007/978-981-13-1562-6_4
Inheritance of epigenome variants across generations during evolution
Varriale, A. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-816363-4.00016-x
Shadrin, A. A., Mucha, S., Ellinghaus, D., Makarious, M. B., Blauwendraat, C., Sreelatha, A. A. K., Heras‐Garvin, A., Ding, J., Hammer, M. B., Foubert‐Samier, A., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/751354
Variant Interpretation and Genomic Medicine
Carss, K., Goldstein, D. B., Aggarwal, V. S., & Petrovski, S. (2019) · Wiley eBooks · doi:10.1002/9781119487845.ch27 · Cited by 1
Genome-wide analyses identify a role for SLC17A4 and AADAT in thyroid hormone regulation
Teumer, A., Chaker, L., Groeneweg, S., Li, Y., Munno, C. D., & Barbieri, C. (2019) · Yearbook of pediatric endocrinology · doi:10.1530/ey.16.3.3
The Association of Single Nucleotide Polymorphisms with Cancer Risk
Matsuda, K. (2019) · Springer eBooks · doi:10.1007/978-981-13-8177-5_5
Virtual Grid Engine: a simulated grid engine environment for large-scale supercomputers
Ito, S., Yadome, M., Nishiki, T., Ishiduki, S., Inoue, H., Yamaguchi, R., & Miyano, S. (2019) · BMC Bioinformatics · doi:10.1186/s12859-019-3085-x
Wang, Y. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/865196
Chen, R., Chen, J., Gao, C., Wu, C., Pan, D., Zhang, J., Zhou, J., Wang, K., Zhang, Q., Yang, Q., et al. (2020) · The World Journal of Biological Psychiatry · doi:10.1080/15622975.2020.1738550
Thyroid Genetics and the Cardiovascular System
Kuś, A., Teumer, A., Chaker, L., & Medici, M. (2020) · Springer eBooks · doi:10.1007/978-3-030-36871-5_15
A novel phylogenetic analysis and machine learning predict pathogenicity of human mtDNA variantsPreprint
Akpınar, B. A., Carlson, P., Paavilainen, V. O., & Dunn, C. D. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.01.10.902239
Neale, B. M. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-800105-9.00009-3
Self-citationWu, Y., Gettler, K., Giri, M., Li, D., Bayrak, Ç. S., Jain, A., Maffucci, P., Sabic, K., Vleck, T. T. V., Nadkarni, G. N., et al. (2020) · medRxiv · doi:10.1101/2020.07.01.20143750
Self-citationMolecular epidemiology studies on risk factors for breast cancer and disease aggressiveness
Ugalde‐Morales, E. (2020) · Figshare
de Bellefon, S. M., Thibord, F., Auer, P. L., Blangero, J., Coban‐Akdemir, Z., Floyd, J. S., Fornage, M., Johnsen, J. M., Lange, L. A., Lewis, J. P., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.11.23.394296
Post-transcriptional gene expression regulation in developmental disorders
Kitaygorodsky, A. (2021) · doi:10.7916/d8-qejw-xf90
Statistical Methods, Analyses and Applications for Next-Generation Sequencing Studies.
Lo, Y. (2015) · Deep Blue (University of Michigan)
Between-host dynamics (Epidemiology)
Schmid‐Hempel, P. (2021) · Oxford University Press eBooks · doi:10.1093/oso/9780198832140.003.0011
Parasites and their significance
Schmid‐Hempel, P. (2021) · Oxford University Press eBooks · doi:10.1093/oso/9780198832140.003.0001
Within-host dynamics and evolution
Schmid‐Hempel, P. (2021) · Oxford University Press eBooks · doi:10.1093/oso/9780198832140.003.0012
Transmission, infection, and pathogenesis
Schmid‐Hempel, P. (2021) · Oxford University Press eBooks · doi:10.1093/oso/9780198832140.003.0009
Genetic Mutations that Cause Coronary Artery Disease
Heidari, M., & Khatami, M. R. (2020)
Genetic and functional analysis of rat mammary cancer susceptibility.
Duderstadt, E. L. (2021) · ThinkIR: The University of Louisville's Institutional Repository (University of Louisville) · doi:10.18297/etd/3628
Schmid‐Hempel, P. (2021) · Oxford University Press eBooks · doi:10.1093/oso/9780198832140.003.0015
The study of evolutionary parasitology
Schmid‐Hempel, P. (2021) · Oxford University Press eBooks · doi:10.1093/oso/9780198832140.003.0002
Parasites, immunity, and sexual selection
Schmid‐Hempel, P. (2021) · Oxford University Press eBooks · doi:10.1093/oso/9780198832140.003.0006 · Cited by 1
Schmid‐Hempel, P. (2021) · Oxford University Press eBooks · doi:10.1093/oso/9780198832140.003.0010
Exon variants associated with asthma and allergy 1Preprint
Wjst, M. (2022) · medRxiv · doi:10.1101/2022.02.09.22270730
Ryan, N., Ormond, C., Brady, P., Heron, E. A., & Corvin, A. P. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-819602-1.00002-4
Wang, Y., Liu, X., & Joseph, P. V. (2022) · Research Square · doi:10.21203/rs.3.rs-1323648/v1
Alkuraya, F. S. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.736300835.793563460
Parasite immune evasion and manipulation of host phenotype
Schmid‐Hempel, P. (2021) · Oxford University Press eBooks · doi:10.1093/oso/9780198832140.003.0008 · Cited by 1
Wen, C., Li, R., Cai, J., & Tan, H. (2020) · doi:10.21203/rs.3.rs-116709/v1
Barroso, I., & Wheeler, E. (2018) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.733320749.793549010
Integration of single cell gene expression data in Bayesian association analysis of rare variantsPreprint
Zhong, G., Choi, Y. A., & Shen, Y. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.05.13.491893
Liu, D., Billington, C. J., Raja, N., Wong, Z. C., Levin, M. D., Resch, W., Alba, C., Hupalo, D. N., Biamino, E., Bedeschi, M. F., et al. (2022) · medRxiv · doi:10.1101/2022.09.21.22280107
Landini, A., Timmers, P. R. H. J., Frkatović-Hodžić, A., Trbojević‐Akmačić, I., Vučković, F., Pribić, T., Tzoneva, G., Shuldiner, A. R., Polašek, O., Hayward, C., et al. (2022) · medRxiv · doi:10.1101/2022.12.26.22283911
Child with Alterations of Mood
Dopp, R. R., Reddy, P., & Hanna, G. L. (2022) · Springer eBooks · doi:10.1007/978-3-031-10494-7_6
Genome-wide association study reveals loci with sex-specific effects on plasma bile acidsPreprint
Landini, A., Ghasemi-Semeskandeh, D., Johansson, Å., Ahmad, S., Liebisch, G., Gnewuch, C., Tzoneva, G., Shuldiner, A. R., Hicks, A. A., Pramstaller, P. P., et al. (2022) · medRxiv · doi:10.1101/2022.12.16.22283452
Metadata
- Authors
- Zuk, O., Schaffner, S. F., Samocha, K., Do, R., Hechter, E., Kathiresan, S., Daly, M. J., Neale, B. M., Sunyaev, S. R., & Lander, E. S.
- Affiliations
- Broad Institute (US)
- ORCID
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2014-01-17
- Volume
- 111
- Issue
- 4
- Pages
- E455-64
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC3910587
- OpenAlex
- W1986818660
- Cited by
- 635
- References
- 65
- Citations by year
- 2026: 11 · 2025: 18 · 2024: 36 · 2023: 40 · 2022: 35 · 2021: 64 · 2020: 41 · 2019: 59 · 2018: 52 · 2017: 71 · 2016: 86 · 2015: 70 · 2014: 48
- FWCI
- 59.70
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- Funders
- National Human Genome Research Institute (U54HG003067)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- missing heritability, research design, sample size, isolated populations, gene set analysis, de novo mutations, selection coefficients, replication
- MeSH terms
- Gene Frequency, Humans, Mutation, Genetic Variation, Genetic Predisposition to Disease, Genome-Wide Association Study
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review