Practical aspects of imputation-driven meta-analysis of genome-wide association studies

doi:10.1093/hmg/ddn288

. 2008 Oct 15;17(R2):R122-8.

doi: 10.1093/hmg/ddn288.

Practical aspects of imputation-driven meta-analysis of genome-wide association studies

Paul I W de Bakker¹, Manuel A R Ferreira, Xiaoming Jia, Benjamin M Neale, Soumya Raychaudhuri, Benjamin F Voight

Affiliations

Affiliation

¹ Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School-Partners Healthcare Systems Center for Genetics and Genomics, Boston, MA 02115, USA. pdebakker@rics.bwh.harvard.edu

PMID: 18852200
PMCID: PMC2782358
DOI: 10.1093/hmg/ddn288

Practical aspects of imputation-driven meta-analysis of genome-wide association studies

Paul I W de Bakker et al. Hum Mol Genet. 2008.

. 2008 Oct 15;17(R2):R122-8.

doi: 10.1093/hmg/ddn288.

Authors

Paul I W de Bakker¹, Manuel A R Ferreira, Xiaoming Jia, Benjamin M Neale, Soumya Raychaudhuri, Benjamin F Voight

Affiliation

¹ Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School-Partners Healthcare Systems Center for Genetics and Genomics, Boston, MA 02115, USA. pdebakker@rics.bwh.harvard.edu

PMID: 18852200
PMCID: PMC2782358
DOI: 10.1093/hmg/ddn288

Abstract

Motivated by the overwhelming success of genome-wide association studies, droves of researchers are working vigorously to exchange and to combine genetic data to expediently discover genetic risk factors for common human traits. The primary tools that fuel these new efforts are imputation, allowing researchers who have collected data on a diversity of genotype platforms to share data in a uniformly exchangeable format, and meta-analysis for pooling statistical support for a genotype-phenotype association. As many groups are forming collaborations to engage in these efforts, this review collects a series of guidelines, practical detail and learned experiences from a variety of individuals who have contributed to the subject.

PubMed Disclaimer

Cited by

Meta-analysis methods for genome-wide association studies and beyond.
Evangelou E, Ioannidis JP. Evangelou E, et al. Nat Rev Genet. 2013 Jun;14(6):379-89. doi: 10.1038/nrg3472. Epub 2013 May 9. Nat Rev Genet. 2013. PMID: 23657481 Review.
Individual differences in amygdala-medial prefrontal anatomy link negative affect, impaired social functioning, and polygenic depression risk.
Holmes AJ, Lee PH, Hollinshead MO, Bakst L, Roffman JL, Smoller JW, Buckner RL. Holmes AJ, et al. J Neurosci. 2012 Dec 12;32(50):18087-100. doi: 10.1523/JNEUROSCI.2531-12.2012. J Neurosci. 2012. PMID: 23238724 Free PMC article.
Effectively identifying eQTLs from multiple tissues by combining mixed model and meta-analytic approaches.
Sul JH, Han B, Ye C, Choi T, Eskin E. Sul JH, et al. PLoS Genet. 2013 Jun;9(6):e1003491. doi: 10.1371/journal.pgen.1003491. Epub 2013 Jun 13. PLoS Genet. 2013. PMID: 23785294 Free PMC article.
Meta-analysis identifies common variants associated with body mass index in east Asians.
Wen W, Cho YS, Zheng W, Dorajoo R, Kato N, Qi L, Chen CH, Delahanty RJ, Okada Y, Tabara Y, Gu D, Zhu D, Haiman CA, Mo Z, Gao YT, Saw SM, Go MJ, Takeuchi F, Chang LC, Kokubo Y, Liang J, Hao M, Le Marchand L, Zhang Y, Hu Y, Wong TY, Long J, Han BG, Kubo M, Yamamoto K, Su MH, Miki T, Henderson BE, Song H, Tan A, He J, Ng DP, Cai Q, Tsunoda T, Tsai FJ, Iwai N, Chen GK, Shi J, Xu J, Sim X, Xiang YB, Maeda S, Ong RT, Li C, Nakamura Y, Aung T, Kamatani N, Liu JJ, Lu W, Yokota M, Seielstad M, Fann CS; Genetic Investigation of ANthropometric Traits (GIANT) Consortium; Wu JY, Lee JY, Hu FB, Tanaka T, Tai ES, Shu XO. Wen W, et al. Nat Genet. 2012 Feb 19;44(3):307-11. doi: 10.1038/ng.1087. Nat Genet. 2012. PMID: 22344219 Free PMC article.
Twenty bone-mineral-density loci identified by large-scale meta-analysis of genome-wide association studies.
Rivadeneira F, Styrkársdottir U, Estrada K, Halldórsson BV, Hsu YH, Richards JB, Zillikens MC, Kavvoura FK, Amin N, Aulchenko YS, Cupples LA, Deloukas P, Demissie S, Grundberg E, Hofman A, Kong A, Karasik D, van Meurs JB, Oostra B, Pastinen T, Pols HA, Sigurdsson G, Soranzo N, Thorleifsson G, Thorsteinsdottir U, Williams FM, Wilson SG, Zhou Y, Ralston SH, van Duijn CM, Spector T, Kiel DP, Stefansson K, Ioannidis JP, Uitterlinden AG; Genetic Factors for Osteoporosis (GEFOS) Consortium. Rivadeneira F, et al. Nat Genet. 2009 Nov;41(11):1199-206. doi: 10.1038/ng.446. Epub 2009 Oct 4. Nat Genet. 2009. PMID: 19801982 Free PMC article.

See all "Cited by" articles

References

1. Barrett J.C., Cardon L.R. Evaluating coverage of genome-wide association studies. Nat. Genet. 2006;38:659–662. - PubMed
1. Pe’er I., de Bakker P.I.W., Maller J., Yelensky R., Altshuler D., Daly M.J. Evaluating and improving power in whole-genome association studies using fixed marker sets. Nat. Genet. 2006;38:663–667. - PubMed
1. Saxena R., Voight B.F., Lyssenko V., Burtt N.P., de Bakker P.I.W., Chen H., Roix J.J., Kathiresan S., Hirschhorn J.N., Daly M.J., et al. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science. 2007;316:1331–1336. - PubMed
1. Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature. 2007;447:661–678. - PMC - PubMed
1. Zeggini E., Weedon M.N., Lindgren C.M., Frayling T.M., Elliott K.S., Lango H., Timpson N.J., Perry J.R., Rayner N.W., Freathy R.M., et al. Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science. 2007;316:1336–1341. - PMC - PubMed

Publication types

Actions
Actions

MeSH terms

Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions

Grants and funding

LinkOut - more resources

Full Text Sources
Other Literature Sources
- The Lens - Patent Citations Database
Research Materials
- NCI CPTC Antibody Characterization Program

[1] Barrett J.C., Cardon L.R. Evaluating coverage of genome-wide association studies. Nat. Genet. 2006;38:659–662. - PubMed

[2] Barrett J.C., Cardon L.R. Evaluating coverage of genome-wide association studies. Nat. Genet. 2006;38:659–662. - PubMed

[3] Pe’er I., de Bakker P.I.W., Maller J., Yelensky R., Altshuler D., Daly M.J. Evaluating and improving power in whole-genome association studies using fixed marker sets. Nat. Genet. 2006;38:663–667. - PubMed

[4] Pe’er I., de Bakker P.I.W., Maller J., Yelensky R., Altshuler D., Daly M.J. Evaluating and improving power in whole-genome association studies using fixed marker sets. Nat. Genet. 2006;38:663–667. - PubMed

[5] Saxena R., Voight B.F., Lyssenko V., Burtt N.P., de Bakker P.I.W., Chen H., Roix J.J., Kathiresan S., Hirschhorn J.N., Daly M.J., et al. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science. 2007;316:1331–1336. - PubMed

[6] Saxena R., Voight B.F., Lyssenko V., Burtt N.P., de Bakker P.I.W., Chen H., Roix J.J., Kathiresan S., Hirschhorn J.N., Daly M.J., et al. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science. 2007;316:1331–1336. - PubMed

[7] Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature. 2007;447:661–678. - PMC - PubMed

[8] Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature. 2007;447:661–678. - PMC - PubMed

[9] Zeggini E., Weedon M.N., Lindgren C.M., Frayling T.M., Elliott K.S., Lango H., Timpson N.J., Perry J.R., Rayner N.W., Freathy R.M., et al. Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science. 2007;316:1336–1341. - PMC - PubMed

[10] Zeggini E., Weedon M.N., Lindgren C.M., Frayling T.M., Elliott K.S., Lango H., Timpson N.J., Perry J.R., Rayner N.W., Freathy R.M., et al. Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science. 2007;316:1336–1341. - PMC - PubMed

Save citation to file

Email citation

Add to Collections

Add to My Bibliography

Your saved search

Create a file for external citation management software

Your RSS Feed

Practical aspects of imputation-driven meta-analysis of genome-wide association studies

Affiliation

Practical aspects of imputation-driven meta-analysis of genome-wide association studies

Authors

Affiliation

Abstract

Similar articles

Cited by

References

Publication types

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources

Other Literature Sources

Research Materials