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Items: 1 to 20 of 107

1.

Population-based association and gene by environment interactions in Genetic Analysis Workshop 18.

Satten GA, Biswas S, Papachristou C, Turkmen A, König IR.

Genet Epidemiol. 2014 Sep;38 Suppl 1:S49-56. doi: 10.1002/gepi.21825.

PMID:
25112188
2.

Drinking from the Holy Grail: analysis of whole-genome sequencing from the Genetic Analysis Workshop 18.

Paterson AD.

Genet Epidemiol. 2014 Sep;38 Suppl 1:S1-4. doi: 10.1002/gepi.21818.

PMID:
25112182
3.

Testing genetic association with rare and common variants in family data.

Chen H, Malzahn D, Balliu B, Li C, Bailey JN.

Genet Epidemiol. 2014 Sep;38 Suppl 1:S37-43. doi: 10.1002/gepi.21823.

4.

Challenges of linkage analysis in the era of whole-genome sequencing.

Santorico SA, Edwards KL.

Genet Epidemiol. 2014 Sep;38 Suppl 1:S92-6. doi: 10.1002/gepi.21832.

PMID:
25112196
5.
6.

Longitudinal data analysis in genome-wide association studies.

Beyene J, Hamid JS.

Genet Epidemiol. 2014 Sep;38 Suppl 1:S68-73. doi: 10.1002/gepi.21828.

PMID:
25112192
7.

Rare-variant genome-wide association studies: a new frontier in genetic analysis of complex traits.

Wagner MJ.

Pharmacogenomics. 2013 Mar;14(4):413-24. doi: 10.2217/pgs.13.36. Review.

PMID:
23438888
9.

Association studies for next-generation sequencing.

Luo L, Boerwinkle E, Xiong M.

Genome Res. 2011 Jul;21(7):1099-108. doi: 10.1101/gr.115998.110. Epub 2011 Apr 26.

10.

Longitudinal data analysis for genetic studies in the whole-genome sequencing era.

Wu Z, Hu Y, Melton PE.

Genet Epidemiol. 2014 Sep;38 Suppl 1:S74-80. doi: 10.1002/gepi.21829.

PMID:
25112193
11.

Applications of machine learning and data mining methods to detect associations of rare and common variants with complex traits.

Lu AT, Austin E, Bonner A, Huang HH, Cantor RM.

Genet Epidemiol. 2014 Sep;38 Suppl 1:S81-5. doi: 10.1002/gepi.21830.

PMID:
25112194
12.

A robust model-free approach for rare variants association studies incorporating gene-gene and gene-environmental interactions.

Fan R, Lo SH.

PLoS One. 2013 Dec 17;8(12):e83057. doi: 10.1371/journal.pone.0083057. eCollection 2013. Erratum in: PLoS One. 2014;9(5):e98083.

13.

Between candidate genes and whole genomes: time for alternative approaches in blood pressure genetics.

Basson J, Simino J, Rao DC.

Curr Hypertens Rep. 2012 Feb;14(1):46-61. doi: 10.1007/s11906-011-0241-8. Review.

PMID:
22161147
14.

How important are rare variants in common disease?

Saint Pierre A, Génin E.

Brief Funct Genomics. 2014 Sep;13(5):353-61. doi: 10.1093/bfgp/elu025. Epub 2014 Jul 8.

PMID:
25005607
15.
16.

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.

17.

Methods for collapsing multiple rare variants in whole-genome sequence data.

Sung YJ, Korthauer KD, Swartz MD, Engelman CD.

Genet Epidemiol. 2014 Sep;38 Suppl 1:S13-20. doi: 10.1002/gepi.21820.

18.

A fast and noise-resilient approach to detect rare-variant associations with deep sequencing data for complex disorders.

Cheung YH, Wang G, Leal SM, Wang S.

Genet Epidemiol. 2012 Nov;36(7):675-85. doi: 10.1002/gepi.21662. Epub 2012 Aug 3.

PMID:
22865616
19.

Systematic inference of copy-number genotypes from personal genome sequencing data reveals extensive olfactory receptor gene content diversity.

Waszak SM, Hasin Y, Zichner T, Olender T, Keydar I, Khen M, Stütz AM, Schlattl A, Lancet D, Korbel JO.

PLoS Comput Biol. 2010 Nov 11;6(11):e1000988. doi: 10.1371/journal.pcbi.1000988.

20.

Local and global ancestry inference and applications to genetic association analysis for admixed populations.

Thornton TA, Bermejo JL.

Genet Epidemiol. 2014 Sep;38 Suppl 1:S5-S12. doi: 10.1002/gepi.21819.

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