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Items: 1 to 20 of 70

1.

Synthetic associations created by rare variants do not explain most GWAS results.

Wray NR, Purcell SM, Visscher PM.

PLoS Biol. 2011 Jan 18;9(1):e1000579. doi: 10.1371/journal.pbio.1000579. No abstract available.

2.

Predicting signatures of "synthetic associations" and "natural associations" from empirical patterns of human genetic variation.

Chang D, Keinan A.

PLoS Comput Biol. 2012;8(7):e1002600. doi: 10.1371/journal.pcbi.1002600. Epub 2012 Jul 5.

3.

Identifying rare variants associated with complex traits via sequencing.

Li B, Liu DJ, Leal SM.

Curr Protoc Hum Genet. 2013 Jul;Chapter 1:Unit 1.26. doi: 10.1002/0471142905.hg0126s78. Review.

4.

Synthetic associations are unlikely to account for many common disease genome-wide association signals.

Anderson CA, Soranzo N, Zeggini E, Barrett JC.

PLoS Biol. 2011 Jan 18;9(1):e1000580. doi: 10.1371/journal.pbio.1000580. No abstract available.

5.

New statistical approaches exploit the polygenic architecture of schizophrenia--implications for the underlying neurobiology.

Schork AJ, Wang Y, Thompson WK, Dale AM, Andreassen OA.

Curr Opin Neurobiol. 2016 Feb;36:89-98. doi: 10.1016/j.conb.2015.10.008. Epub 2015 Nov 8. Review.

6.

Common variants in polygenic schizophrenia.

Glessner JT, Hakonarson H.

Genome Biol. 2009;10(9):236. doi: 10.1186/gb-2009-10-9-236. Epub 2009 Sep 29. Review.

7.

Sporadic, Global Linkage Disequilibrium Between Unlinked Segregating Sites.

Skelly DA, Magwene PM, Stone EA.

Genetics. 2016 Feb;202(2):427-37. doi: 10.1534/genetics.115.177816. Epub 2015 Dec 29.

8.

[Progress in genetic association study for multifactorial diseases].

Yamamoto K.

Nihon Rinsho. 2009 Jun;67(6):1063-7. Review. Japanese.

PMID:
19507493
9.

Utilizing population controls in rare-variant case-parent association tests.

Jiang Y, Satten GA, Han Y, Epstein MP, Heinzen EL, Goldstein DB, Allen AS.

Am J Hum Genet. 2014 Jun 5;94(6):845-53. doi: 10.1016/j.ajhg.2014.04.014. Epub 2014 May 15.

10.
11.

Polygenic modeling of genome-wide association studies: an application to prostate and breast cancer.

Witte JS, Hoffmann TJ.

OMICS. 2011 Jun;15(6):393-8. doi: 10.1089/omi.2010.0090. Epub 2011 Feb 24.

12.

Genetics: finding genes for schizophrenia.

Flint J, Munafò MR.

Curr Biol. 2014 Aug 18;24(16):R755-7. doi: 10.1016/j.cub.2014.07.018.

13.

Evaluating empirical bounds on complex disease genetic architecture.

Agarwala V, Flannick J, Sunyaev S; GoT2D Consortium, Altshuler D.

Nat Genet. 2013 Dec;45(12):1418-27. doi: 10.1038/ng.2804. Epub 2013 Oct 20.

14.

Efficient strategy for detecting gene × gene joint action and its application in schizophrenia.

Won S, Kwon MS, Mattheisen M, Park S, Park C, Kihara D, Cichon S, Ophoff R, Nöthen MM, Rietschel M, Baur M, Uitterlinden AG, Hofmann A; GROUP Investigators, Lange C.

Genet Epidemiol. 2014 Jan;38(1):60-71. doi: 10.1002/gepi.21779. Epub 2013 Nov 23.

PMID:
24272960
15.

Probing the Association between Early Evolutionary Markers and Schizophrenia.

Srinivasan S, Bettella F, Hassani S, Wang Y, Witoelar A, Schork AJ, Thompson WK, Collier DA, Desikan RS, Melle I, Dale AM, Djurovic S, Andreassen OA.

PLoS One. 2017 Jan 12;12(1):e0169227. doi: 10.1371/journal.pone.0169227. eCollection 2017.

16.

Weighted selective collapsing strategy for detecting rare and common variants in genetic association study.

Dai Y, Jiang R, Dong J.

BMC Genet. 2012 Feb 6;13:7. doi: 10.1186/1471-2156-13-7.

17.

Genetic architecture of type 2 diabetes.

Hara K, Shojima N, Hosoe J, Kadowaki T.

Biochem Biophys Res Commun. 2014 Sep 19;452(2):213-20. doi: 10.1016/j.bbrc.2014.08.012. Epub 2014 Aug 8. Review.

PMID:
25111817
18.

[Genetic study of schizophrenia-focusing on GWAS-].

Ikeda M.

Seishin Shinkeigaku Zasshi. 2012;114(7):857-60. Japanese. No abstract available.

PMID:
23136690
19.

Exploiting Linkage Disequilibrium for Ultrahigh-Dimensional Genome-Wide Data with an Integrated Statistical Approach.

Carlsen M, Fu G, Bushman S, Corcoran C.

Genetics. 2016 Feb;202(2):411-26. doi: 10.1534/genetics.115.179507. Epub 2015 Dec 12.

20.

Hidden Markov models for controlling false discovery rate in genome-wide association analysis.

Wei Z.

Methods Mol Biol. 2012;802:337-44. doi: 10.1007/978-1-61779-400-1_22.

PMID:
22130891

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