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Identifying Rare Variants Associated with Complex Traits via Sequencing

dc.contributor.authorLi, Bingshan
dc.contributor.authorLiu, Dajiang J.
dc.contributor.authorLeal, Suzanne M.
dc.date.accessioned2020-01-13T15:07:43Z
dc.date.available2020-01-13T15:07:43Z
dc.date.issued2013-07
dc.identifier.citationLi, Bingshan; Liu, Dajiang J.; Leal, Suzanne M. (2013). "Identifying Rare Variants Associated with Complex Traits via Sequencing." Current Protocols in Human Genetics 78(1): 1.26.1-1.26.22.
dc.identifier.issn1934-8266
dc.identifier.issn1934-8258
dc.identifier.urihttps://hdl.handle.net/2027.42/152695
dc.description.abstractAlthough genome‐wide association studies have been successful in detecting associations with common variants, there is currently an increasing interest in identifying low‐frequency and rare variants associated with complex traits. Next‐generation sequencing technologies make it feasible to survey the full spectrum of genetic variation in coding regions or the entire genome. The association analysis for rare variants is challenging, and traditional methods are ineffective, however, due to the low frequency of rare variants, coupled with allelic heterogeneity. Recently a battery of new statistical methods has been proposed for identifying rare variants associated with complex traits. These methods test for associations by aggregating multiple rare variants across a gene or a genomic region or among a group of variants in the genome. In this unit, we describe key concepts for rare variant association for complex traits, survey some of the recent methods, discuss their statistical power under various scenarios, and provide practical guidance on analyzing next‐generation sequencing data for identifying rare variants associated with complex traits. Curr. Protoc. Hum. Genet. 78:1.26.1‐1.26.22. © 2013 by John Wiley & Sons, Inc.
dc.publisherChapman and Hall
dc.publisherWiley Periodicals, Inc.
dc.subject.otheraggregation analysis
dc.subject.otherexome
dc.subject.othersequencing
dc.subject.otherrare variants
dc.subject.othercomplex traits
dc.subject.otherassociation tests
dc.titleIdentifying Rare Variants Associated with Complex Traits via Sequencing
dc.typeArticle
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelBiological Chemistry
dc.subject.hlbsecondlevelGenetics
dc.subject.hlbsecondlevelMolecular, Cellular and Developmental Biology
dc.subject.hlbtoplevelHealth Sciences
dc.subject.hlbtoplevelScience
dc.description.peerreviewedPeer Reviewed
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/152695/1/cphg0126.pdf
dc.identifier.doi10.1002/0471142905.hg0126s78
dc.identifier.sourceCurrent Protocols in Human Genetics
dc.identifier.citedreferenceNelson, M.R., Wegmann, D., Ehm, M.G., Kessner, D., St. Jean, P., Verzilli, C., Shen, J., Tang, Z., Bacanu, S.‐A., Fraser, D., Warren, L., Aponte, J., Zawistowski, M., Liu, X., Zhang, H., Zhang, Y., Li, J., Li, Y., Li, L., Woollard, P., Topp, S., Hall, M.D., Nangle, K., Wang, J., Abecasis, G., Cardon, L.R., Zöllner, S., Whittaker, J.C., Chissoe, S.L., Novembre, J., and Mooser, V. 2012. An abundance of rare functional variants in 202 drug target genes sequenced in 14,002 people. Science 337: 100 ‐ 104.
dc.identifier.citedreferenceNg, P.C. and Henikoff, S. 2003. SIFT: Predicting amino acid changes that affect protein function. Nucleic Acids Res. 31: 3812 ‐ 3814.
dc.identifier.citedreferenceNg, S.B., Turner, E.H., Robertson, P.D., Flygare, S.D., Bigham, A.W., Lee, C., Shaffer, T., Wong, M., Bhattacharjee, A., Eichler, E.E., Bamshad, M., Nickerson, D.A., and Shendure, J. 2009. Targeted capture and massively parallel sequencing of 12 human exomes. Nature 461: 272 ‐ 276.
dc.identifier.citedreferenceNielsen, R., Paul, J.S., Albrechtsen, A., and Song, Y.S. 2011. Genotype and SNP calling from next‐generation sequencing data. Nature Rev. Genet. 12: 443 ‐ 451.
dc.identifier.citedreferencePan, W. 2009. Asymptotic tests of association with multiple SNPs in linkage disequilibrium. Genet. Epidemiol. 33: 497 ‐ 507.
dc.identifier.citedreferencePan, W. and Shen, X. 2011. Adaptive tests for association analysis of rare variants. Genet. Epidemiol. 35: 381 ‐ 388.
dc.identifier.citedreferencePeng, B., Li, B., Han, Y., and Amos, C.I. 2010. Power analysis for case‐control association studies of samples with known family histories. Hum. Genet. 127: 699 ‐ 704.
dc.identifier.citedreferencePrice, A.L., Patterson, N.J., Plenge, R.M., Weinblatt, M.E., Shadick, N.A., and Reich, D. 2006. Principal components analysis corrects for stratification in genome‐wide association studies. Nat. Genet. 38: 904 ‐ 909.
dc.identifier.citedreferencePrice, A.L., Kryukov, G.V., de Bakker, P.I.W., Purcell, S.M., Staples, J., Wei, L.‐J., and Sunyaev, S.R. 2010. Pooled association tests for rare variants in exon‐resequencing studies. Am. J. Hum. Genet. 86: 832 ‐ 838.
dc.identifier.citedreferencePritchard, J.K. and Przeworski, M. 2001. Linkage disequilibrium in humans: Models and data. Am. J. Hum. Genet. 69: 1 ‐ 14.
dc.identifier.citedreferenceR Development Core Team. 2008. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna.
dc.identifier.citedreferenceRamensky, V., Bork, P., and Sunyaev, S. 2002. Human non‐synonymous SNPs: Server and survey. Nucleic Acids Res. 30: 3894 ‐ 3900.
dc.identifier.citedreferenceRomeo, S., Pennacchio, L.A., Fu, Y., Boerwinkle, E., Tybjaerg‐Hansen, A., Hobbs, H.H., and Cohen, J.C. 2007. Population‐based resequencing of ANGPTL4 uncovers variations that reduce triglycerides and increase HDL. Nat. Genet. 39: 513 ‐ 516.
dc.identifier.citedreferenceSan Lucas, F.A., Wang, G., Scheet, P., and Peng, B. 2012. Integrated annotation and analysis of genetic variants from next‐generation sequencing studies with variant tools. Bioinformatics 28: 421 ‐ 422.
dc.identifier.citedreferenceSanger, F., Nicklen, S., and Coulson, A.R. 1977. DNA sequencing with chain‐terminating inhibitors. Proc. Natl. Acad. Sci. U.S.A. 74: 5463 ‐ 5467.
dc.identifier.citedreferenceSchork, N.J., Murray, S.S., Frazer, K.A., and Topol, E.J. 2009. Common vs. rare allele hypotheses for complex diseases. Curr. Opin. Genet. Dev. 19: 212 ‐ 219.
dc.identifier.citedreferenceSchwarz, J.M., Rödelsperger, C., Schuelke, M., and Seelow, D. 2010. MutationTaster evaluates disease‐causing potential of sequence alterations. Nat. Methods 7: 575 ‐ 576.
dc.identifier.citedreferenceShendure, J. and Ji, H. 2008. Next‐generation DNA sequencing. Nat. Biotechnol. 26: 1135 ‐ 1145.
dc.identifier.citedreferenceSiepel, A., Bejerano, G., Pedersen, J.S., Hinrichs, A.S., Hou, M., Rosenbloom, K., Clawson, H., Spieth, J., Hillier, L.W., Richards, S., Weinstock, G.M., Wilson, R.K., Gibbs, R.A., Kent, W.J., Miller, W., and Haussler, D. 2005. Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes. Genome Res. 15: 1034 ‐ 1050.
dc.identifier.citedreferenceSlager, S.L., Huang, J., and Vieland, V.J. 2000. Effect of allelic heterogeneity on the power of the transmission disequilibrium test. Genet. Epidemiol. 18: 143 ‐ 156.
dc.identifier.citedreferenceSmith, D.J. and Lusis, A.J. 2002. The allelic structure of common disease. Hum. Mol. Genet. 11: 2455 ‐ 2461.
dc.identifier.citedreferenceStitziel, N.O., Kiezun, A., and Sunyaev, S. 2011. Computational and statistical approaches to analyzing variants identified by exome sequencing. Genome Biol. 12: 227.
dc.identifier.citedreferenceTennessen, J.A., Bigham, A.W., O’Connor, T.D., Fu, W., Kenny, E.E., Gravel, S., McGee, S., Do, R., Liu, X., Jun, G., Kang, H.M., Jordan, D., Leal, S.M., Gabriel, S., Rieder, M.J., Abecasis, G., Altshuler, D., Nickerson, D.A., Boerwinkle, E., Sunyaev, S., Bustamante, C.D., Bamshad, M.J., and Akey, J.M. 2012. Evolution and functional impact of rare coding variation from deep sequencing of human exomes. Science 337: 64 ‐ 69.
dc.identifier.citedreferenceWang, K., Li, M., and Hakonarson, H. 2010. ANNOVAR: Functional annotation of genetic variants from high‐throughput sequencing data. Nucleic Acids Res. 38: e164.
dc.identifier.citedreferenceWu, M.C., Lee, S., Cai, T., Li, Y., Boehnke, M., and Lin, X. 2011. Rare‐variant association testing for sequencing data with the sequence kernel association test. Am. J. Hum. Genet. 89: 82 ‐ 93.
dc.identifier.citedreferenceZhang, Y., Guan, W., and Pan, W. 2013. Adjustment for population stratification via principal components in association analysis of rare variants. Genet. Epidemiol. 37: 99 ‐ 109.
dc.identifier.citedreferenceZhu, X., Feng, T., Li, Y., Lu, Q., and Elston, R.C. 2010. Detecting rare variants for complex traits using family and unrelated data. Genet. Epidemiol. 34: 171 ‐ 187.
dc.identifier.citedreferenceZhu, Y. and Xiong, M. 2012. Family‐based association studies for next‐generation sequencing. Am. J. Hum. Genet. 90: 1028 ‐ 1045.
dc.identifier.citedreference1000 Genomes Project Consortium. 2010. A map of human genome variation from population‐scale sequencing. Nature 467: 1061 ‐ 1073.
dc.identifier.citedreferenceAbecasis, G.R., Auton, A., Brooks, L.D., DePristo, M.A., Durbin, R.M., Handsaker, R.E., Kang, H.M., Marth, G.T., and McVean, G.A. 2012. An integrated map of genetic variation from 1,092 human genomes. Nature 491: 56 ‐ 65.
dc.identifier.citedreferenceAdzhubei, I.A., Schmidt, S., Peshkin, L., Ramensky, V.E., Gerasimova, A., Bork, P., Kondrashov, A.S., and Sunyaev, S.R. 2010. A method and server for predicting damaging missense mutations. Nat. Methods 7: 248 ‐ 249.
dc.identifier.citedreferenceAhituv, N., Kavaslar, N., Schackwitz, W., Ustaszewska, A., Martin, J., Hébert, S., Doelle, H., Ersoy, B., Kryukov, G., Schmidt, S., Yosef, N., Ruppin, E., Sharan, R., Vaisse, C., Sunyaev, S., Dent, R., Cohen, J., McPherson, R., and Pennacchio, L.A. 2007. Medical sequencing at the extremes of human body mass. Am. J. Hum. Genet. 80: 779 ‐ 791.
dc.identifier.citedreferenceAltshuler, D.M., Gibbs, R.A., Peltonen, L., Altshuler, D.M., Gibbs, R.A., Peltonen, L., Dermitzakis, E., Schaffner, S.F., Yu, F., Peltonen, L., Dermitzakis, E., Bonnen, P.E., Altshuler, D.M., Gibbs, R.A., de Bakker, P.I.W., Deloukas, P., Gabriel, S.B., Gwilliam, R., Hunt, S., Inouye, M., Jia, X., Palotie, A., Parkin, M., Whittaker, P., Yu, F., Chang, K., Hawes, A., Lewis, L.R., Ren, Y., Wheeler, D., Gibbs, R.A., Muzny, D.M., Barnes, C., Darvishi, K., Hurles, M., Korn, J.M., Kristiansson, K., Lee, C., McCarrol, S.A., Nemesh, J., Dermitzakis, E., Keinan, A., Montgomery, S.B., Pollack, S., Price, A.L., Soranzo, N., Bonnen, P.E., Gibbs, R.A., Gonzaga‐Jauregui, C., Keinan, A., Price, A.L., Yu, F., Anttila, V., Brodeur, W., Daly, M.J., Leslie, S., McVean, G., Moutsianas, L., Nguyen, H., Schaffner, S.F., Zhang, Q., Ghori, M.J.R., McGinnis, R., McLaren, W., Pollack, S., Price, A.L., Schaffner, S.F., Takeuchi, F., Grossman, S.R., Shlyakhter, I., Hostetter, E.B., Sabeti, P.C., Adebamowo, C.A., Foster, M.W., Gordon, D.R., Licinio, J., Manca, M.C., Marshall, P.A., Matsuda, I., Ngare, D., Wang, V.O., Reddy, D., Rotimi, C.N., Royal, C.D., Sharp, R.R., Zeng, C., Brooks, L.D., and McEwen, J.E. 2010. Integrating common and rare genetic variation in diverse human populations. Nature 467: 52 ‐ 58.
dc.identifier.citedreferenceAsimit, J. and Zeggini, E. 2010. Rare variant association analysis methods for complex traits. Ann. Rev. Genet. 44: 293 ‐ 308.
dc.identifier.citedreferenceBansal, V., Libiger, O., Torkamani, A., and Schork, N.J. 2010. Statistical analysis strategies for association studies involving rare variants. Nat. Rev. Genet. 11: 773 ‐ 785.
dc.identifier.citedreferenceBarnett, I.J., Lee, S., and Lin, X. 2013. Detecting rare variant effects using extreme phenotype sampling in sequencing association studies. Genet. Epidemiol. 37: 142 ‐ 151.
dc.identifier.citedreferenceBhatia, G., Bansal, V., Harismendy, O., Schork, N.J., Topol, E.J., Frazer, K., and Bafna, V. 2010. A covering method for detecting genetic associations between rare variants and common phenotypes. PLoS Comp. Biol. 6: e100954.
dc.identifier.citedreferenceBodmer, W. and Bonilla, C. 2008. Common and rare variants in multifactorial susceptibility to common diseases. Nat. Genet. 40: 695 ‐ 701.
dc.identifier.citedreferenceBromberg, Y. and Rost, B. 2007. SNAP: Predict effect of non‐synonymous polymorphisms on function. Nucleic Acids Res. 35: 3823 ‐ 3835.
dc.identifier.citedreferenceChen, W., Li, B., Zeng, Z., Sanna, S., Sidore, C., Busonero, F., Kang, H.M., Li, Y., and Abecasis, G.R. 2013. Genotype calling and haplotyping in parent‐offspring trios. Genome Res. 23: 142 ‐ 151.
dc.identifier.citedreferenceChoi, M., Scholl, U.I., Ji, W., Liu, T., Tikhonova, I.R., Zumbo, P., Nayir, A., Bakkaloğlu, A., Özen, S., Sanjad, S., Nelson‐Williams, C., Farhi, A., Mane, S., and Lifton, R.P. 2009. Genetic diagnosis by whole exome capture and massively parallel DNA sequencing. Proc. Natl. Acad. Sci. U.S.A. 106: 19096 ‐ 19101.
dc.identifier.citedreferenceChun, S. and Fay, J.C. 2009. Identification of deleterious mutations within three human genomes. Genome Res. 19: 1553 ‐ 1561.
dc.identifier.citedreferenceCirulli, E.T. and Goldstein, D.B. 2010. Uncovering the roles of rare variants in common disease through whole‐genome sequencing. Nat. Rev. Genet. 11: 415 ‐ 425.
dc.identifier.citedreferenceCohen, J., Pertsemlidis, A., Kotowski, I.K., Graham, R., Garcia, C.K., and Hobbs, H.H. 2005. Low LDL cholesterol in individuals of African descent resulting from frequent nonsense mutations in PCSK9. Nat. Genet. 37: 161 ‐ 165.
dc.identifier.citedreferenceCohen, J.C., Kiss, R.S., Pertsemlidis, A., Marcel, Y.L., McPherson, R., and Hobbs, H.H. 2004. Multiple rare alleles contribute to low plasma levels of HDL cholesterol. Science 305: 869 ‐ 872.
dc.identifier.citedreferenceCohen, J.C., Pertsemlidis, A., Fahmi, S., Esmail, S., Vega, G.L., Grundy, S.M., and Hobbs, H.H. 2006. Multiple rare variants in NPC1L1 associated with reduced sterol absorption and plasma low‐density lipoprotein levels. Proc. Natl. Acad. Sci. U.S.A. 103: 1810 ‐ 1815.
dc.identifier.citedreferenceCooper, G.M., Stone, E.A., Asimenos, G., Green, E.D., Batzoglou, S., and Sidow, A. 2005. Distribution and intensity of constraint in mammalian genomic sequence. Genome Res. 15: 901 ‐ 913.
dc.identifier.citedreferenceCox, D.R. and Hinkley, D.V. 1979. Theoretical Statistics, Chapman and Hall, London, England.
dc.identifier.citedreferenceDanecek, P., Auton, A., Abecasis, G., Albers, C.A., Banks, E., DePristo, M.A., Handsaker, R.E., Lunter, G., Marth, G.T., Sherry, S.T., McVean, G., and Durbin, R. 2011. The variant call format and VCFtools. Bioinformatics 27: 2156 ‐ 2158.
dc.identifier.citedreferenceDePristo, M.A., Banks, E., Poplin, R., Garimella, K.V., Maguire, J.R., Hartl, C., Philippakis, A.A., del Angel, G., Rivas, M.A., Hanna, M., McKenna, A., Fennell, T.J., Kernytsky, A.M., Sivachenko, A.Y., Cibulskis, K., Gabriel, S.B., Altshuler, D., and Daly, M.J. 2011. A framework for variation discovery and genotyping using next‐generation DNA sequencing data. Nat. Genet. 43: 491 ‐ 498.
dc.identifier.citedreferenceDering, C., Hemmelmann, C., Pugh, E., and Ziegler, A. 2011. Statistical analysis of rare sequence variants: An overview of collapsing methods. Genet. Epidemiol. 35: S12 ‐ S17.
dc.identifier.citedreferenceDo, R., Kathiresan, S., and Abecasis, G.R. 2012. Exome sequencing and complex disease: Practical aspects of rare variant association studies. Hum. Mol. Genet. 21: R1 ‐ R9.
dc.identifier.citedreferenceDudbridge, F. and Gusnanto, A. 2008. Estimation of significance thresholds for genomewide association scans. Genet. Epidemiol. 32: 227 ‐ 234.
dc.identifier.citedreferenceEmond, M.J., Louie, T., Emerson, J., Zhao, W., Mathias, R.A., Knowles, M.R., Wright, F.A., Rieder, M.J., Tabor, H.K., Nickerson, D.A., Barnes, K.C., Gibson, R.L., and Bamshad, M.J. 2012. Exome sequencing of extreme phenotypes identifies DCTN4 as a modifier of chronic Pseudomonas aeruginosa infection in cystic fibrosis. Nat. Genet. 44: 886 ‐ 889.
dc.identifier.citedreferenceFang, S., Sha, Q., and Zhang, S. 2012. Two adaptive weighting methods to test for rare variant associations in family‐based designs. Genet. Epidemiol. 36: 499 ‐ 507.
dc.identifier.citedreferenceFerrer‐Costa, C., Gelpi, J.L., Zamakola, L., Parraga, I., de la Cruz, X., and Orozco, M. 2005. PMUT: A web‐based tool for the annotation of pathological mutations on proteins. Bioinformatics 21: 3176 ‐ 3178.
dc.identifier.citedreferenceGorlov, I.P., Gorlova, O.Y., Sunyaev, S.R., Spitz, M.R., and Amos, C.I. 2008. Shifting paradigm of association studies: Value of rare single‐nucleotide polymorphisms. Am. J. Hum. Genet. 82: 100 ‐ 112.
dc.identifier.citedreferenceHan, F. and Pan, W. 2010. A data‐adaptive sum test for disease association with multiple common or rare variants. Hum. Hered. 70: 42 ‐ 54.
dc.identifier.citedreferenceHartl, D.L. and Clark, A.G. 2007. Principles of Population Genetics, 4th ed. Sinauer Associates, Sunderland, Massachusetts.
dc.identifier.citedreferenceHirschhorn, J.N. and Daly, M.J. 2005. Genome‐wide association studies for common diseases and complex traits. Nat. Rev. Genet. 6: 95 ‐ 108.
dc.identifier.citedreferenceHowie, B., Fuchsberger, C., Stephens, M., Marchini, J., and Abecasis, G.R. 2012. Fast and accurate genotype imputation in genome‐wide association studies through pre‐phasing. Nat. Genet. 44: 955 ‐ 959.
dc.identifier.citedreferenceHowie, B.N., Donnelly, P., and Marchini, J. 2009. A flexible and accurate genotype imputation method for the next generation of genome‐wide association studies. PLoS Genet. 5: e100529.
dc.identifier.citedreferenceHuang, B.E. and Lin, D.Y. 2007. Efficient association mapping of quantitative trait loci with selective genotyping. Am. J. Hum. Genet. 80: 567 ‐ 576.
dc.identifier.citedreferenceIyengar, S.K. and Elston, R.C. 2007. The genetic basis of complex traits: Rare variants or “common gene, common disease” ? Methods Mol. Biol. 376: 71 ‐ 84.
dc.identifier.citedreferenceJi, W., Foo, J.N., O’Roak, B.J., Zhao, H., Larson, M.G., Simon, D.B., Newton‐Cheh, C., State, M.W., Levy, D., and Lifton, R.P. 2008. Rare independent mutations in renal salt handling genes contribute to blood pressure variation. Nat. Genet. 40: 592 ‐ 599.
dc.identifier.citedreferenceJun, G., Flickinger, M., Hetrick, K.N., Romm, J.M., Doheny, K.F., Abecasis, G.R., Boehnke, M., and Kang, R.P. 2012. Detecting and estimating contamination of human DNA samples in sequencing and array‐based genotype data. Am. J. Hum. Genet. 91: 839 ‐ 848.
dc.identifier.citedreferenceKang, H.M., Sul, J.H., Service, S.K., Zaitlen, N.A., Kong, S.‐y., Freimer, N.B., Sabatti, C., and Eskin, E. 2010. Variance component model to account for sample structure in genome‐wide association studies. Nat. Genet. 42: 348 ‐ 354.
dc.identifier.citedreferenceKeinan, A. and Clark, A.G. 2012. Recent explosive human population growth has resulted in an excess of rare genetic variants. Science 336: 740 ‐ 743.
dc.identifier.citedreferenceLadouceur, M., Dastani, Z., Aulchenko, Y.S., Greenwood, C.M.T., and Richards, J.B. 2012. The empirical power of rare variant association methods: Results from Sanger sequencing in 1,998 individuals. PLoS Genet. 8: e1002496.
dc.identifier.citedreferenceLee, S., Emond, M.J., Bamshad, M.J., Barnes, K.C., Rieder, M.J., Nickerson, D.A., Christiani, D.C., Wurfel, M.M., and Lin, X. 2012a. Optimal unified approach for rare‐variant association testing with application to small‐sample case‐control whole‐exome sequencing studies. Am. J. Hum. Genet. 91: 224 ‐ 237.
dc.identifier.citedreferenceLee, S., Wu, M.C., and Lin, X. 2012b. Optimal tests for rare variant effects in sequencing association studies. Biostatistics 13: 762 ‐ 775.
dc.identifier.citedreferenceLi, B. and Leal, S.M. 2008. Methods for detecting associations with rare variants for common diseases: Application to analysis of sequence data. Am. J. Hum. Genet. 83: 311 ‐ 321.
dc.identifier.citedreferenceLi, B. and Leal, S.M. 2009. Discovery of rare variants via sequencing: Implications for the design of complex trait association studies. PLoS Genet. 5: e100481.
dc.identifier.citedreferenceLi, B., Chen, W., Zhan, X., Busonero, F., Sanna, S., Sidore, C., Cucca, F., Kang, H.M., and Abecasis, G.R. 2012a. A likelihood‐based framework for variant calling and de novo mutation detection in families. PLoS Genet. 8: e1002944.
dc.identifier.citedreferenceLi, B., Wang, G., and Leal, S.M. 2012b. SimRare: A program to generate and analyze sequence‐based data for association studies of quantitative and qualitative traits. Bioinformatics 28: 2703 ‐ 2704.
dc.identifier.citedreferenceLi, H. 2011. A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics 27: 2987 ‐ 2993.
dc.identifier.citedreferenceLi, H. and Durbin, R. 2010. Fast and accurate long‐read alignment with Burrows‐Wheeler transform. Bioinformatics 26: 589 ‐ 595.
dc.identifier.citedreferenceLi, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., and Durbin, R. 2009. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25: 2078 ‐ 2079.
dc.identifier.citedreferenceLi, Y., Byrnes, A.E., and Li, M. 2010a. To identify associations with rare variants, just WHaIT: W eighted h aplotype a nd i mputation‐based t ests. Am. J. Hum. Genet. 87: 728 ‐ 735.
dc.identifier.citedreferenceLi, Y., Willer, C.J., Ding, J., Scheet, P., and Abecasis, G.R. 2010b. MaCH: Using sequence and genotype data to estimate haplotypes and unobserved genotypes. Genet. Epidemiol. 34: 816 ‐ 834.
dc.identifier.citedreferenceLi, Y., Sidore, C., Kang, H.M., Boehnke, M., and Abecasis, G.R. 2011. Low‐coverage sequencing: Implications for design of complex trait association studies. Genome Res. 21: 940 ‐ 951.
dc.identifier.citedreferenceLin, D.‐Y. and Tang, Z.‐Z. 2011. A general framework for detecting disease associations with rare variants in sequencing studies. Am. J. Hum. Genet. 89: 354 ‐ 367.
dc.identifier.citedreferenceLiu, D.J. and Leal, S.M. 2010a. A novel adaptive method for the analysis of next‐generation sequencing data to detect complex trait associations with rare variants due to gene main effects and interactions. PLoS Genet. 6: e1001156.
dc.identifier.citedreferenceLiu, D.J. and Leal, S.M. 2010b. Replication strategies for rare variant complex trait association studies via next‐generation sequencing. Am. J. Hum. Genet. 87: 790 ‐ 801.
dc.identifier.citedreferenceLiu, D.J. and Leal, S.M. 2012a. Estimating genetic effects and quantifying missing heritability explained by identified rare‐variant associations. Am. J. Hum. Genet. 91: 585 ‐ 596.
dc.identifier.citedreferenceLiu, D.J. and Leal, S.M. 2012b. A unified framework for detecting rare variant quantitative trait associations in pedigree and unrelated individuals via sequence data. Hum. Hered. 73: 105 ‐ 122.
dc.identifier.citedreferenceLiu, X., Jian, X., and Boerwinkle, E. 2011. dbNSFP: A lightweight database of human nonsynonymous SNPs and their functional predictions. Hum. Mutat. 32: 894 ‐ 899.
dc.identifier.citedreferenceMaher, B. 2008. Personal genomes: The case of the missing heritability. Nature 456: 18 ‐ 21.
dc.identifier.citedreferenceManolio, 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., Cho, J.H., Guttmacher, A.E., Kong, A., Kruglyak, L., Mardis, E., Rotimi, C.N., Slatkin, M., Valle, D., Whittemore, A.S., Boehnke, M., Clark, A.G., Eichler, E.E., Gibson, G., Haines, J.L., Mackay, T.F.C., McCarroll, S.A., and Visscher, P.M. 2009. Finding the missing heritability of complex diseases. Nature 461: 747 ‐ 753.
dc.identifier.citedreferenceMardis, E.R. 2008. Next‐generation DNA sequencing methods. Ann. Rev. Genom. Hum. Genet. 9: 387 ‐ 402.
dc.identifier.citedreferenceMathieson, I. and McVean, G. 2012. Differential confounding of rare and common variants in spatially structured populations. Nat. Genet. 44: 243 ‐ 246.
dc.identifier.citedreferenceNeale, B.M., Rivas, M.A., Voight, B.F., Altshuler, D., Devlin, B., Orho‐Melander, M., Kathiresan, S., Purcell, S.M., Roeder, K., and Daly, M.J. 2011. Testing for an unusual distribution of rare variants. PLoS Genet. 7: e1001322.
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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