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Items: 11

1.

Concept, design and implementation of a cardiovascular gene-centric 50 k SNP array for large-scale genomic association studies.

Keating BJ, Tischfield S, Murray SS, Bhangale T, Price TS, Glessner JT, Galver L, Barrett JC, Grant SF, Farlow DN, Chandrupatla HR, Hansen M, Ajmal S, Papanicolaou GJ, Guo Y, Li M, Derohannessian S, de Bakker PI, Bailey SD, Montpetit A, Edmondson AC, Taylor K, Gai X, Wang SS, Fornage M, Shaikh T, Groop L, Boehnke M, Hall AS, Hattersley AT, Frackelton E, Patterson N, Chiang CW, Kim CE, Fabsitz RR, Ouwehand W, Price AL, Munroe P, Caulfield M, Drake T, Boerwinkle E, Reich D, Whitehead AS, Cappola TP, Samani NJ, Lusis AJ, Schadt E, Wilson JG, Koenig W, McCarthy MI, Kathiresan S, Gabriel SB, Hakonarson H, Anand SS, Reilly M, Engert JC, Nickerson DA, Rader DJ, Hirschhorn JN, Fitzgerald GA.

PLoS One. 2008;3(10):e3583. doi: 10.1371/journal.pone.0003583. Epub 2008 Oct 31.

2.

Alcohol Dependence Genetics: Lessons Learned From Genome-Wide Association Studies (GWAS) and Post-GWAS Analyses.

Hart AB, Kranzler HR.

Alcohol Clin Exp Res. 2015 Aug;39(8):1312-27. doi: 10.1111/acer.12792. Epub 2015 Jun 25. Review.

3.

Lipoprotein association studies: taking stock and moving forward.

Talmud PJ, Yiannakouris N, Humphries SE.

Curr Opin Lipidol. 2011 Apr;22(2):106-12. doi: 10.1097/MOL.0b013e3283423f81. Review.

PMID:
21178771
4.

Prioritizing GWAS results: A review of statistical methods and recommendations for their application.

Cantor RM, Lange K, Sinsheimer JS.

Am J Hum Genet. 2010 Jan;86(1):6-22. doi: 10.1016/j.ajhg.2009.11.017. Review.

5.

Using biological knowledge to uncover the mystery in the search for epistasis in genome-wide association studies.

Ritchie MD.

Ann Hum Genet. 2011 Jan;75(1):172-82. doi: 10.1111/j.1469-1809.2010.00630.x. Review.

6.

GWAS as a Driver of Gene Discovery in Cardiometabolic Diseases.

Atanasovska B, Kumar V, Fu J, Wijmenga C, Hofker MH.

Trends Endocrinol Metab. 2015 Dec;26(12):722-32. doi: 10.1016/j.tem.2015.10.004. Epub 2015 Nov 18. Review.

PMID:
26596674
7.

Identifying functional noncoding variants from genome-wide association studies for cardiovascular disease and related traits.

Smith AJ, Humphries SE, Talmud PJ.

Curr Opin Lipidol. 2015 Apr;26(2):120-6. doi: 10.1097/MOL.0000000000000158. Review.

PMID:
25692342
8.

Candidate gene association studies: a comprehensive guide to useful in silico tools.

Patnala R, Clements J, Batra J.

BMC Genet. 2013 May 9;14:39. doi: 10.1186/1471-2156-14-39. Review.

9.

The genetics of cardiovascular disease: new insights from emerging approaches.

Chico TJ, Milo M, Crossman DC.

J Pathol. 2010 Jan;220(2):186-97. doi: 10.1002/path.2641. Review.

PMID:
19921712
10.

Genetics of the Framingham Heart Study population.

Govindaraju DR, Cupples LA, Kannel WB, O'Donnell CJ, Atwood LD, D'Agostino RB Sr, Fox CS, Larson M, Levy D, Murabito J, Vasan RS, Splansky GL, Wolf PA, Benjamin EJ.

Adv Genet. 2008;62:33-65. doi: 10.1016/S0065-2660(08)00602-0. Review.

11.

Genome-Wide Association Studies of Chemotherapeutic Toxicities: Genomics of Inequality.

Mapes B, El Charif O, Al-Sawwaf S, Dolan ME.

Clin Cancer Res. 2017 Aug 1;23(15):4010-4019. doi: 10.1158/1078-0432.CCR-17-0429. Epub 2017 Apr 25. Review.

PMID:
28442506

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