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Items: 1 to 20 of 239

1.

Bioinformatics challenges for genome-wide association studies.

Moore JH, Asselbergs FW, Williams SM.

Bioinformatics. 2010 Feb 15;26(4):445-55. doi: 10.1093/bioinformatics/btp713. Epub 2010 Jan 6. Review.

2.

Accuracy of genome-wide imputation of untyped markers and impacts on statistical power for association studies.

Hao K, Chudin E, McElwee J, Schadt EE.

BMC Genet. 2009 Jun 16;10:27. doi: 10.1186/1471-2156-10-27.

3.

GWAS Integrator: a bioinformatics tool to explore human genetic associations reported in published genome-wide association studies.

Yu W, Yesupriya A, Wulf A, Hindorff LA, Dowling N, Khoury MJ, Gwinn M.

Eur J Hum Genet. 2011 Oct;19(10):1095-9. doi: 10.1038/ejhg.2011.91. Epub 2011 May 25.

4.

Multi-locus test conditional on confirmed effects leads to increased power in genome-wide association studies.

Ma L, Han S, Yang J, Da Y.

PLoS One. 2010 Nov 16;5(11):e15006. doi: 10.1371/journal.pone.0015006.

5.

GWAS analyzer: integrating genotype, phenotype and public annotation data for genome-wide association study analysis.

Fong C, Ko DC, Wasnick M, Radey M, Miller SI, Brittnacher M.

Bioinformatics. 2010 Feb 15;26(4):560-4. doi: 10.1093/bioinformatics/btp714. Epub 2010 Jan 6.

6.

Biostatistical aspects of genome-wide association studies.

Ziegler A, König IR, Thompson JR.

Biom J. 2008 Feb;50(1):8-28. doi: 10.1002/bimj.200710398. Review.

PMID:
18217698
7.

SNPranker 2.0: a gene-centric data mining tool for diseases associated SNP prioritization in GWAS.

Merelli I, Calabria A, Cozzi P, Viti F, Mosca E, Milanesi L.

BMC Bioinformatics. 2013;14 Suppl 1:S9. doi: 10.1186/1471-2105-14-S1-S9. Epub 2013 Jan 14.

8.

Translating genome wide association study results to associations among common diseases: in silico study with an electronic medical record.

Anand V, Rosenman MB, Downs SM.

Int J Med Inform. 2013 Sep;82(9):864-74. doi: 10.1016/j.ijmedinf.2013.05.003. Epub 2013 Jun 3.

PMID:
23743324
9.

Gene, pathway and network frameworks to identify epistatic interactions of single nucleotide polymorphisms derived from GWAS data.

Liu Y, Maxwell S, Feng T, Zhu X, Elston RC, Koyutürk M, Chance MR.

BMC Syst Biol. 2012;6 Suppl 3:S15. doi: 10.1186/1752-0509-6-S3-S15. Epub 2012 Dec 17.

10.

An open access database of genome-wide association results.

Johnson AD, O'Donnell CJ.

BMC Med Genet. 2009 Jan 22;10:6. doi: 10.1186/1471-2350-10-6.

11.

Strategies for pathway analysis from GWAS data.

Yaspan BL, Veatch OJ.

Curr Protoc Hum Genet. 2011 Oct;Chapter 1:Unit1.20. doi: 10.1002/0471142905.hg0120s71.

PMID:
21975938
12.

The pursuit of genome-wide association studies: where are we now?

Ku CS, Loy EY, Pawitan Y, Chia KS.

J Hum Genet. 2010 Apr;55(4):195-206. doi: 10.1038/jhg.2010.19. Epub 2010 Mar 19. Review.

PMID:
20300123
13.

Integrative pathway analysis of genome-wide association studies and gene expression data in prostate cancer.

Jia P, Liu Y, Zhao Z.

BMC Syst Biol. 2012;6 Suppl 3:S13. doi: 10.1186/1752-0509-6-S3-S13. Epub 2012 Dec 17.

14.

Detecting two-locus associations allowing for interactions in genome-wide association studies.

Wan X, Yang C, Yang Q, Xue H, Tang NL, Yu W.

Bioinformatics. 2010 Oct 15;26(20):2517-25. doi: 10.1093/bioinformatics/btq486. Epub 2010 Aug 24.

15.

A hidden two-locus disease association pattern in genome-wide association studies.

Yang C, Wan X, Yang Q, Xue H, Tang NL, Yu W.

BMC Bioinformatics. 2011 May 14;12:156. doi: 10.1186/1471-2105-12-156.

16.

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.

17.

Genome-wide association data classification and SNPs selection using two-stage quality-based Random Forests.

Nguyen TT, Huang J, Wu Q, Nguyen T, Li M.

BMC Genomics. 2015;16 Suppl 2:S5. doi: 10.1186/1471-2164-16-S2-S5. Epub 2015 Jan 21.

18.

Planning a genome-wide association study: points to consider.

Hakonarson H, Grant SF.

Ann Med. 2011;43(6):451-60. doi: 10.3109/07853890.2011.573803. Epub 2011 May 19. Review.

PMID:
21595511
19.

The SNP ratio test: pathway analysis of genome-wide association datasets.

O'Dushlaine C, Kenny E, Heron EA, Segurado R, Gill M, Morris DW, Corvin A.

Bioinformatics. 2009 Oct 15;25(20):2762-3. doi: 10.1093/bioinformatics/btp448. Epub 2009 Jul 20.

20.

Advances in genomic analysis of stroke: what have we learned and where are we headed?

Lanktree MB, Dichgans M, Hegele RA.

Stroke. 2010 Apr;41(4):825-32. doi: 10.1161/STROKEAHA.109.570523. Epub 2010 Feb 18. Review.

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