114
R. E. Graff et al.
understanding of the disease process, risks, and response to therapy in this era of
genomic discovery.
Acknowledgments This work was supported by National Institutes of Health grants
R25CA112355, R01CA088164, and R01CA201358.
References
Altshuler D, Daly MJ, Lander ES (2008) Genetic mapping in human disease. Science 322:881–888
Aragaki CC, Greenland S, Probst-Hensch N, Haile RW (1997) Hierarchical modeling of geneenvironment interactions: estimating NAT2 genotype-specific dietary effects on adenomatous
polyps. Cancer Epidemiol Biomark Prev 6:307–314
Asimit J, Zeggini E (2010) Rare variant association analysis methods for complex traits. Annu Rev
Genet 44:293–308
Asimit JL, Day-Williams AG, Morris AP, Zeggini E (2012) ARIEL and AMELIA: testing for an
accumulation of rare variants using next-generation sequencing data. Hum Hered 73:84–94
Aulchenko YS, Ripke S, Isaacs A, van Duijn CM (2007) GenABEL: an R library for genome-wide
association analysis. Bioinformatics 23:1294–1296
Barbeira AN, Dickinson SP, Bonazzola R et al (2018) Exploring the phenotypic consequences of
tissue specific gene expression variation inferred from GWAS summary statistics. Nat Commun
9:1825
Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful
approach to multiple testing. J R Stat Soc Series B 57:289–300
Bhattacharjee S, Rajaraman P, Jacobs KB et al (2012) A subset-based approach improves power
and interpretation for the combined analysis of genetic association studies of heterogeneous
traits. Am J Hum Genet 90:821–835
Botstein D, White RL, Skolnick M, Davis RW (1980) Construction of a genetic linkage map in
man using restriction fragment length polymorphisms. Am J Hum Genet 32:314–331
Bowden J, Del Greco MF, Minelli C, Davey Smith G, Sheehan N, Thompson J (2017) A framework
for the investigation of pleiotropy in two-sample summary data Mendelian randomization. Stat
Med 36:1783–1802
Brzyski D, Peterson CB, Sobczyk P, Candes EJ, Bogdan M, Sabatti C (2017) Controlling the rate
of GWAS false discoveries. Genetics 205:61–75
Bulik-Sullivan B, Loh P-R, Finucane H et al (2015) LD score regression distinguishes confounding
from polygenicity in genome-wide association studies. Nat Genet 47:291–295
Buniello A, MacArthur JAL, Cerezo M et al (2019) The NHGRI-EBI GWAS catalog of published
genome-wide association studies, targeted arrays and summary statistics 2019. Nucleic Acids
Res 47:D1005–D1012
Burgess S, Butterworth A, Thompson SG (2013) Mendelian randomization analysis with multiple
genetic variants using summarized data. Genet Epidemiol 37:658–665
Burton PR, Clayton DG, Cardon LR et al (2007) Genome-wide association study of 14,000 cases
of seven common diseases and 3,000 shared controls. Nature 447:661–678
Cantor RM, Lange K, Sinsheimer JS (2010) Prioritizing GWAS results: a review of statistical
methods and recommendations for their application. Am J Hum Genet 86:6–22
Cardin NJ, Mefford JA, Witte JS (2012) Joint association testing of common and rare genetic
variants using hierarchical modeling. Genet Epidemiol 36:642–651
Carlson CS, Matise TC, North KE et al (2013) Generalization and dilution of association results
from European GWAS in populations of non-European ancestry: the PAGE study. PLoS Biol
11:e1001661
Chanock SJ, Manolio T, Boehnke M et al (2007) Replicating genotype-phenotype associations.
Nature 447:655–660
R. E. Graff et al.
understanding of the disease process, risks, and response to therapy in this era of
genomic discovery.
Acknowledgments This work was supported by National Institutes of Health grants
R25CA112355, R01CA088164, and R01CA201358.
References
Altshuler D, Daly MJ, Lander ES (2008) Genetic mapping in human disease. Science 322:881–888
Aragaki CC, Greenland S, Probst-Hensch N, Haile RW (1997) Hierarchical modeling of geneenvironment interactions: estimating NAT2 genotype-specific dietary effects on adenomatous
polyps. Cancer Epidemiol Biomark Prev 6:307–314
Asimit J, Zeggini E (2010) Rare variant association analysis methods for complex traits. Annu Rev
Genet 44:293–308
Asimit JL, Day-Williams AG, Morris AP, Zeggini E (2012) ARIEL and AMELIA: testing for an
accumulation of rare variants using next-generation sequencing data. Hum Hered 73:84–94
Aulchenko YS, Ripke S, Isaacs A, van Duijn CM (2007) GenABEL: an R library for genome-wide
association analysis. Bioinformatics 23:1294–1296
Barbeira AN, Dickinson SP, Bonazzola R et al (2018) Exploring the phenotypic consequences of
tissue specific gene expression variation inferred from GWAS summary statistics. Nat Commun
9:1825
Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful
approach to multiple testing. J R Stat Soc Series B 57:289–300
Bhattacharjee S, Rajaraman P, Jacobs KB et al (2012) A subset-based approach improves power
and interpretation for the combined analysis of genetic association studies of heterogeneous
traits. Am J Hum Genet 90:821–835
Botstein D, White RL, Skolnick M, Davis RW (1980) Construction of a genetic linkage map in
man using restriction fragment length polymorphisms. Am J Hum Genet 32:314–331
Bowden J, Del Greco MF, Minelli C, Davey Smith G, Sheehan N, Thompson J (2017) A framework
for the investigation of pleiotropy in two-sample summary data Mendelian randomization. Stat
Med 36:1783–1802
Brzyski D, Peterson CB, Sobczyk P, Candes EJ, Bogdan M, Sabatti C (2017) Controlling the rate
of GWAS false discoveries. Genetics 205:61–75
Bulik-Sullivan B, Loh P-R, Finucane H et al (2015) LD score regression distinguishes confounding
from polygenicity in genome-wide association studies. Nat Genet 47:291–295
Buniello A, MacArthur JAL, Cerezo M et al (2019) The NHGRI-EBI GWAS catalog of published
genome-wide association studies, targeted arrays and summary statistics 2019. Nucleic Acids
Res 47:D1005–D1012
Burgess S, Butterworth A, Thompson SG (2013) Mendelian randomization analysis with multiple
genetic variants using summarized data. Genet Epidemiol 37:658–665
Burton PR, Clayton DG, Cardon LR et al (2007) Genome-wide association study of 14,000 cases
of seven common diseases and 3,000 shared controls. Nature 447:661–678
Cantor RM, Lange K, Sinsheimer JS (2010) Prioritizing GWAS results: a review of statistical
methods and recommendations for their application. Am J Hum Genet 86:6–22
Cardin NJ, Mefford JA, Witte JS (2012) Joint association testing of common and rare genetic
variants using hierarchical modeling. Genet Epidemiol 36:642–651
Carlson CS, Matise TC, North KE et al (2013) Generalization and dilution of association results
from European GWAS in populations of non-European ancestry: the PAGE study. PLoS Biol
11:e1001661
Chanock SJ, Manolio T, Boehnke M et al (2007) Replicating genotype-phenotype associations.
Nature 447:655–660