Power comparisons between similarity‐based multilocus association methods, logistic regression, and score tests for haplotypes
Open accessAbstract
Recently, a genomic distance‐based regression for multilocus associations was proposed (Wessel and Schork [2006] Am. J. Hum. Genet. 79:792–806) in which either locus or haplotype scoring can be used to measure genetic distance. Although it allows various measures of genomic similarity and simultaneous analyses of multiple phenotypes, its power relative to other methods for case‐control analyses is not well known. We compare the power of traditional methods with this new distance‐based approach, for both locus‐scoring and haplotype‐scoring strategies. We discuss the relative power of these association methods with respect to five properties: (1) the marker informativity; (2) the number of markers; (3) the causal allele frequency; (4) the preponderance of the most common high‐risk haplotype; (5) the correlation between the causal single‐nucleotide polymorphism (SNP) and its flanking markers. We found that locus‐based logistic regression and the global score test for haplotypes suffered from power loss when many markers were included in the analyses, due to many degrees of freedom. In contrast, the distance‐based approach was not as vulnerable to more markers or more haplotypes. A genotype counting measure was more sensitive to the marker informativity and the correlation between the causal SNP and its flanking markers. After examining the impact of the five properties on power, we found that on average, the genomic distance‐based regression that uses a matching measure for diplotypes was the most powerful and robust method among the seven methods we compared. Genet. Epidemiol. 2009. © 2008 Wiley‐Liss, Inc.
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
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?
Similarity-based strategies can be as powerful, if not more so, than some traditional tests of association in many settings involving common variations.
“Many recent papers have described flexible strategies for testing genetic associations that leverage individual sequence similarity information,20, 52–57 and it has been shown that such strategies can be as powerful, if not more so, than some traditional tests of association in many settings involving common variations.58”
From Statistical analysis strategies for association studies involving rare variants (2010) · cites this paper as [58]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
A new method for non-parametric multivariate analysis of variance
Anderson, M. J. (2001) · Austral Ecology · doi:10.1111/j.1442-9993.2001.01070.pp.x · Cited by 13,828 · see citing works
The International HapMap Project
†The International HapMap Consortium, Genotyping centres: Baylor College of Medicine and ParAllele BioScience, Gibbs, R. A., Belmont, J. W., Hardenbol, P., Willis, T. D., Yu, F., Chinese HapMap Consortium, Yang, H., Ch'ang, L.-Y., et al. (2003) · Nature · doi:10.1038/nature02168 · Cited by 6,057 · see citing works
A haplotype map of the human genome
The International HapMap Consortium (2005) · Nature · doi:10.1038/nature04226 · Cited by 5,858 · see citing works
Some Distance Properties of Latent Root and Vector Methods Used in Multivariate Analysis
Gower, J. C. (1966) · Biometrika · doi:10.1093/biomet/53.3-4.325 · Cited by 4,274 · see citing works
FITTING MULTIVARIATE MODELS TO COMMUNITY DATA: A COMMENT ON DISTANCE-BASED REDUNDANCY ANALYSIS
McArdle, B. H., & Anderson, M. J. (2001) · Ecology · doi:10.1890/0012-9658(2001)082[0290:fmmtcd]2.0.co;2 · Cited by 4,001 · see citing works
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 · see citing works
Methods of Multivariate Analysis
Rencher, A. C. (2002) · Wiley series in probability and statistics · doi:10.1002/0471271357 · Cited by 2,057 · see citing works
Score Tests for Association between Traits and Haplotypes when Linkage Phase Is Ambiguous
Schaid, D. J., Rowland, C. M., Tines, D. E., Jacobson, R. M., & Poland, G. A. (2002) · The American Journal of Human Genetics · doi:10.1086/338688 · Cited by 1,772 · see citing works
Self-citationA tutorial on statistical methods for population association studies
Balding, D. J. (2006) · Nature Reviews Genetics · doi:10.1038/nrg1916 · Cited by 1,328 · see citing works
A global test for groups of genes: testing association with a clinical outcome
Goeman, J. J., van de Geer, S., de Kort, F., & van Houwelingen, H. C. (2003) · Bioinformatics · doi:10.1093/bioinformatics/btg382 · Cited by 1,052 · see citing works
Zaykin, D. V., Westfall, P. H., Young, S. S., Karnoub, M. A., Wagner, M. J., & Ehm, M. G. (2002) · Human Heredity · doi:10.1159/000057986 · Cited by 655 · see citing works
Chapman, J. M., Cooper, J. D., Todd, J. A., & Clayton, D. G. (2003) · Human Heredity · doi:10.1159/000073729 · Cited by 414 · see citing works
Cordell, H. J., & Clayton, D. G. (2002) · The American Journal of Human Genetics · doi:10.1086/338007 · Cited by 411 · see citing works
The complex genetic epidemiology of prostate cancer
Schaid, D. J. (2004) · Human Molecular Genetics · doi:10.1093/hmg/ddh072 · Cited by 369 · see citing works
Self-citationUsing haplotype blocks to map human complex trait loci
Cardon, L. R., & Abecasis, G. R. (2003) · Trends in Genetics · doi:10.1016/s0168-9525(03)00022-2 · Cited by 367 · see citing works
Evaluating associations of haplotypes with traits
Schaid, D. J. (2004) · Genetic Epidemiology · doi:10.1002/gepi.20037 · Cited by 315 · see citing works
Self-citationAn Introduction to Generalized Linear Models
Ziegel, E. R. (2002) · Technometrics · doi:10.1198/tech.2002.s91 · Cited by 257 · see citing works
Kuusisto, J., Koivisto, K. J., Kervinen, K., Mykkänen, L. M., Helkala, E.-L., Vanhanen, M., Hänninen, T., Pyörälä, K., Kesäniemi, Y. A., Riekkinen, P. J., et al. (1994) · BMJ · doi:10.1136/bmj.309.6955.636 · Cited by 207 · see citing works
Generalized Genomic Distance–Based Regression Methodology for Multilocus Association Analysis
Wessel, J., & Schork, N. J. (2006) · The American Journal of Human Genetics · doi:10.1086/508346 · Cited by 190 · see citing works
Use of unphased multilocus genotype data in indirect association studies
Clayton, D., Chapman, J., & Cooper, J. (2004) · Genetic Epidemiology · doi:10.1002/gepi.20032 · Cited by 186 · see citing works
Heidema, A. G., Boer, J. M. A., Nagelkerke, N. J. D., Mariman, E. C. M., van der A, D. L., & Feskens, E. J. M. (2006) · BMC Genetics · doi:10.1186/1471-2156-7-23 · Cited by 170 · see citing works
Douglas, J. A., Boehnke, M., Gillanders, E. M., Trent, J. M., & Gruber, S. B. (2001) · Nature Genetics · doi:10.1038/ng582 · Cited by 158 · see citing works
The impact of genotyping error on family-based analysis of quantitative traits
Abecasis, G. R., Cherny, S. S., & Cardon, L. R. (2001) · European Journal of Human Genetics · doi:10.1038/sj.ejhg.5200594 · Cited by 142 · see citing works
Nonparametric Tests of Association of Multiple Genes with Human Disease
Schaid, D. J., McDonnell, S. K., Hebbring, S. J., Cunningham, J. M., & Thibodeau, S. N. (2005) · The American Journal of Human Genetics · doi:10.1086/429838 · Cited by 135 · see citing works
Self-citationTzeng, J., Devlin, B., Wasserman, L., & Roeder, K. (2003) · The American Journal of Human Genetics · doi:10.1086/373881 · Cited by 135 · see citing works
Haplotype-Based Association Analysis via Variance-Components Score Test
Tzeng, J., & Zhang, D. (2007) · The American Journal of Human Genetics · doi:10.1086/521558 · Cited by 71 · see citing works
Relative efficiency of ambiguous vs. directly measured haplotype frequencies
Schaid, D. J. (2002) · Genetic Epidemiology · doi:10.1002/gepi.10184 · Cited by 59 · see citing works
Self-citationGenomic control for association studies: a semiparametric test to detect excess-haplotype sharing
Devlin, B. (2000) · Biostatistics · doi:10.1093/biostatistics/1.4.369 · Cited by 53 · see citing works
Bourgain, C., Génin, E., Holopainen, P., Mustalahti, K., Mäki, M., Partanen, J., & Clerget‐Darpoux, F. (2001) · The American Journal of Human Genetics · doi:10.1086/316933 · Cited by 46 · see citing works
Outlier Detection and False Discovery Rates for Whole-Genome DNA Matching
Tzeng, J., Byerley, W., Devlin, B., Roeder, K., & Wasserman, L. (2003) · Journal of the American Statistical Association · doi:10.1198/016214503388619256 · Cited by 33 · see citing works
Genetic analysis with hierarchical models
Witte, J. S. (1997) · Genetic Epidemiology · doi:10.1002/(sici)1098-2272(1997)14:6 · Cited by 33 · see citing works
Power and Sample Size for Testing Associations of Haplotypes with Complex Traits
Schaid, D. J. (2005) · Annals of Human Genetics · doi:10.1111/j.1529-8817.2005.00215.x · Cited by 32 · see citing works
Self-citationGenomic Mismatch Scanning Identifies Human Genomic DNA Shared Identical by Descent
Cheung, V. G., & Nelson, S. F. (1998) · Genomics · doi:10.1006/geno.1997.5082 · Cited by 31 · see citing works
Testing for association with a case‐parents design in the presence of genotyping errors
Morris, R. W., & Kaplan, N. L. (2004) · Genetic Epidemiology · doi:10.1002/gepi.10297 · Cited by 31 · see citing works
A new association test using haplotype similarity
Sha, Q., Chen, H., & Zhang, S. (2007) · Genetic Epidemiology · doi:10.1002/gepi.20230 · Cited by 24 · see citing works
Tintle, N., Ahn, K., Mendell, N. R., Gordon, D., & Finch, S. J. (2005) · BMC Genetics · doi:10.1186/1471-2156-6-s1-s154 · Cited by 21 · see citing works
Significance testing for direct identity‐by‐descent mapping
Grant, G. R., Manduchi, E., Cheung, V. G., & Ewens, W. J. (1999) · Annals of Human Genetics · doi:10.1046/j.1469-1809.1999.6350441.x · Cited by 17 · see citing works
North, B. V., Sham, P. C., Knight, J., Martin, E. R., & Curtis, D. (2006) · Annals of Human Genetics · doi:10.1111/j.1469-1809.2006.00301.x · Cited by 14 · see citing works
Cheng, K. F., & Lin, W. (2007) · The American Journal of Human Genetics · doi:10.1086/520962 · Cited by 14 · see citing works
Self-citationClustering of haplotypes based on phylogeny: how good a strategy for association testing?
Bardel, C., Darlu, P., & Génin, E. (2005) · European Journal of Human Genetics · doi:10.1038/sj.ejhg.5201501 · Cited by 10 · see citing works
Detecting disease gene in DNA haplotype sequences by nonparametric dissimilarity test
Yuan, A., Yue, Q., Apprey, V., & Bonney, G. E. (2006) · Human Genetics · doi:10.1007/s00439-006-0216-z · Cited by 9 · see citing works
Testing for association based on excess allele sharing in a sample of related cases and controls
Klei, L., & Roeder, K. (2007) · Human Genetics · doi:10.1007/s00439-007-0345-z · Cited by 6 · see citing works
Fine-scale mapping in case-control samples using locus scoring and haplotype-sharing methods
Humphreys, K., & Iles, M. M. (2005) · BMC Genetics · doi:10.1186/1471-2156-6-s1-s74 · Cited by 5 · see citing works
Tzeng, J., Chang, S.-M., Zhang, D., Thomas, D. C., & Davidian, M. (2007) · NCSU Libraries Repository (North Carolina State University Libraries) · Cited by 3 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Powerful SNP-Set Analysis for Case-Control Genome-wide Association Studies
Wu, M. C., Kraft, P., Epstein, M. P., Taylor, D. M., Chanock, S. J., Hunter, D. J., & Lin, X. (2010) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2010.05.002 · Cited by 589 · see citing works
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 · see citing works
Comparison of statistical tests for disease association with rare variants
Basu, S., & Pan, W. (2011) · Genetic Epidemiology · doi:10.1002/gepi.20609 · Cited by 215 · see citing works
A multivariate distance-based analytic framework for connectome-wide association studies
Shehzad, Z. E., Kelly, C. A. M., Reiss, P. T., Craddock, R. C., Emerson, J. W., McMahon, K. L., Copland, D. A., Castellanos, F. X., & Milham, M. P. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.02.024 · Cited by 178 · see citing works
SNP Set Association Analysis for Familial Data
Schifano, E. D., Epstein, M. P., Bielak, L. F., Jhun, M. A., Kardia, S. L. R., Peyser, P. A., & Lin, X. (2012) · Genetic Epidemiology · doi:10.1002/gepi.21676 · Cited by 107 · see citing works
Association tests using kernel‐based measures of multi‐locus genotype similarity between individuals
Mukhopadhyay, I., Feingold, E., Weeks, D. E., & Thalamuthu, A. (2009) · Genetic Epidemiology · doi:10.1002/gepi.20451 · Cited by 79 · see citing works
Functional Linear Models for Association Analysis of Quantitative Traits
Fan, R., Wang, Y., Mills, J. L., Wilson, A. F., Wilson, J., & Xiong, M. (2013) · Genetic Epidemiology · doi:10.1002/gepi.21757 · Cited by 76 · see citing works
Pan, W. (2011) · Genetic Epidemiology · doi:10.1002/gepi.20567 · Cited by 71 · see citing works
Ballard, D. H., Cho, J. H., & Zhao, H. (2009) · Genetic Epidemiology · doi:10.1002/gepi.20448 · Cited by 74 · see citing works
Kernel machine SNP-set analysis for censored survival outcomes in genome-wide association studies
Lin, X., Cai, T., Wu, M. C., Zhou, Q., Liu, G., Christiani, D. C., & Lin, X. (2011) · Genetic Epidemiology · doi:10.1002/gepi.20610 · Cited by 62 · see citing works
Pleiotropy Analysis of Quantitative Traits at Gene Level by Multivariate Functional Linear Models
Wang, Y., Liu, A., Mills, J. L., Boehnke, M., Wilson, A. F., Wilson, J., Xiong, M., Wu, C. O., & Fan, R. (2015) · Genetic Epidemiology · doi:10.1002/gepi.21895 · Cited by 56 · see citing works
AssocTests: An R Package for Genetic Association Studies
Wang, L., Zhang, W., & Li, Q. (2020) · Journal of Statistical Software · doi:10.18637/jss.v094.i05 · Cited by 33 · see citing works
Generalized Functional Linear Models for Gene‐Based Case‐Control Association Studies
Fan, R., Wang, Y., Mills, J. L., Carter, T. C., Lobach, I. V., Wilson, A. F., Wilson, J., Weeks, D. E., & Xiong, M. (2014) · Genetic Epidemiology · doi:10.1002/gepi.21840 · Cited by 30 · see citing works
Haplotype‐Based Methods for Detecting Uncommon Causal Variants With Common SNPs
Lin, W., Yi, N., Zhi, D., Zhang, K., Gao, G., Tiwari, H. K., & Liu, N. (2012) · Genetic Epidemiology · doi:10.1002/gepi.21650 · Cited by 30 · see citing works
Self-citationDetecting the footprints of divergent selection in oaks with linked markers
Goicoechea, P. G., Petit, R. J., & Kremer, A. (2012) · Heredity · doi:10.1038/hdy.2012.51 · Cited by 26 · see citing works
Fang, H., & Pan, W. (2010) · Genetic Epidemiology · doi:10.1002/gepi.20529 · Cited by 23 · see citing works
Zuo, L., Wang, K., & Luο, X. (2014) · Europe PMC (PubMed Central) · doi:10.3969/j.issn.1002-0829.2014.03.009 · Cited by 19 · see citing works
SNP-set analysis replicates acute lung injury genetic risk factors
Meyer, N. J., Daye, Z. J., Rushefski, M., Aplenc, R., Lanken, P. N., Shashaty, M. G. S., Christie, J. D., & Feng, R. (2012) · BMC Medical Genetics · doi:10.1186/1471-2350-13-52 · Cited by 19 · see citing works
Multilocus association testing with penalized regression
Basu, S., Pan, W., Shen, X., & Oetting, W. S. (2011) · Genetic Epidemiology · doi:10.1002/gepi.20625 · Cited by 16 · see citing works
Fang, H., & Pan, W. (2011) · Biometrics · doi:10.1111/j.1541-0420.2011.01649.x · Cited by 14 · see citing works
Ak, A., Abid, M., Silva, M. P. D., & Callet, P. L. (2021) · IEEE International Conference on Multimedia & Expo Workshops (ICMEW) · doi:10.1109/icmew53276.2021.9455992 · Cited by 14 · see citing works
Pongpanich, M., Neely, M. L., & Tzeng, J. (2012) · Frontiers in Genetics · doi:10.3389/fgene.2011.00110 · Cited by 12 · see citing works
Gene-level pharmacogenetic analysis on survival outcomes using gene-trait similarity regression
Tzeng, J., Lu, W., & Hsu, F.-C. (2014) · The Annals of Applied Statistics · doi:10.1214/14-aoas735 · Cited by 10 · see citing works
Tong, L., Yang, J., & Cooper, R. (2010) · Annals of Human Genetics · doi:10.1111/j.1469-1809.2010.00574.x · Cited by 9 · see citing works
Group analysis of distance matrices
Wang, J., Li, J., Xiong, W., & Li, Q. (2020) · Genetic Epidemiology · doi:10.1002/gepi.22329 · Cited by 7 · see citing works
Salem, R. M., O’Connor, D. T., & Schork, N. J. (2010) · Physiological Genomics · doi:10.1152/physiolgenomics.00118.2009 · Cited by 7 · see citing works
Similarity‐Based Multimarker Association Tests for Continuous Traits
Lin, W., Tiwari, H. K., Gao, G., Zhang, K., Arcaroli, J. J., Abraham, E. H., & Liu, N. (2012) · Annals of Human Genetics · doi:10.1111/j.1469-1809.2012.00706.x · Cited by 5 · see citing works
Self-citationBeckmann, L. (2010) · Encyclopedia of Life Sciences · doi:10.1002/9780470015902.a0022496 · Cited by 5 · see citing works
Distance-based phenotypic association analysis of DNA sequence data
Chung, D., Zhang, Q., Kraja, A. T., Borecki, I. B., & Province, M. A. (2011) · BMC Proceedings · doi:10.1186/1753-6561-5-s9-s54 · Cited by 4 · see citing works
The EGFR rs2233947 polymorphism is associated with lung cancer risk: a study from Jordan
Bashir, N. A., Morad, F. R., Khabour, O. F., Alfaqih, M. A., & Khassawneh, B. Y. (2019) · Acta Biochimica Polonica · doi:10.18388/abp.2019_2781 · Cited by 4 · see citing works
Discovering joint associations between disease and gene pairs with a novel similarity test
Lin, W., & Lee, W. (2010) · BMC Genetics · doi:10.1186/1471-2156-11-86 · Cited by 3 · see citing works
Self-citationEffects of Video Enhancement in a Stated-Choice Experiment on Medical Decision Making
Hoffmann, S., Winter, J., Francis, G., & Gottlieb, A. S. (2014) · Cited by 3 · see citing works
Minnier, J. (2012) · Digital Access to Scholarship at Harvard (DASH) (Harvard University) · Cited by 1 · see citing works
Kernel machine methods for analysis of genomic data from different sources
Zhao, N. (2019) · Carolina Digital Repository (University of North Carolina at Chapel Hill) · doi:10.17615/z57b-dm04 · Cited by 1 · see citing works
Gene and Gene-Set Analysis for Genome-Wide Association StudiesPreprint
Pedroso, I. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1308.4102
- Authors
- Lin, W., & Schaid, D. J.
- Affiliations
- National Taiwan University (TW)
- Mayo Clinic (US)
- Corresponding author
- Schaid, Daniel J.
- Venue
- Genetic Epidemiology
- Publisher
- Wiley
- Published
- 2008-09-22
- Volume
- 33
- Issue
- 3
- Pages
- 183-197
- ISSN
- 0741-0395 (ISSN-L)
- 1098-2272
- PMC
- PMC2674317
- OpenAlex
- W2111503388
- Cited by
- 35
- References
- 44
- Citations by year
- 2021: 1 · 2020: 2 · 2019: 2 · 2015: 1 · 2014: 5 · 2013: 2 · 2012: 7
- FWCI
- 2.85
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Genetic Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Science Council
- National Institute of General Medical Sciences (GM065450, R01GM065450)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
- Keywords
- statistical power, logistic regression, score test, case-control association, diplotypes, single nucleotide polymorphisms, marker correlation
- MeSH terms
- Alleles, Genetic Markers, Genetic Techniques, Genotype, Haplotypes, Genetic Linkage, Mathematics, Models, Genetic, Logistic Models, Polymorphism, Single Nucleotide
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
