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Items: 1 to 20 of 76

1.

Power of a reproducing kernel-based method for testing the joint effect of a set of single-nucleotide polymorphisms.

He H, Zhang H, Maity A, Zou Y, Hussey J, Karmaus W.

Genetica. 2012 Dec;140(10-12):421-7. doi: 10.1007/s10709-012-9690-5.

2.

Kernel machine SNP-set testing under multiple candidate kernels.

Wu MC, Maity A, Lee S, Simmons EM, Harmon QE, Lin X, Engel SM, Molldrem JJ, Armistead PM.

Genet Epidemiol. 2013 Apr;37(3):267-75. doi: 10.1002/gepi.21715.

3.

A simulation study to assess a variable selection method for selecting single nucleotide polymorphisms associated with disease.

Rabie HS, Saunders IW.

J Comput Biol. 2012 Oct;19(10):1151-61. doi: 10.1089/cmb.2011.0105.

PMID:
23057824
4.

Prioritizing individual genetic variants after kernel machine testing using variable selection.

He Q, Cai T, Liu Y, Zhao N, Harmon QE, Almli LM, Binder EB, Engel SM, Ressler KJ, Conneely KN, Lin X, Wu MC.

Genet Epidemiol. 2016 Dec;40(8):722-731. doi: 10.1002/gepi.21993.

PMID:
27488097
5.

GLOSSI: a method to assess the association of genetic loci-sets with complex diseases.

Chai HS, Sicotte H, Bailey KR, Turner ST, Asmann YW, Kocher JP.

BMC Bioinformatics. 2009 Apr 3;10:102. doi: 10.1186/1471-2105-10-102.

6.

A multi-SNP association test for complex diseases incorporating an optimal P-value threshold algorithm in nuclear families.

Wang YT, Sung PY, Lin PL, Yu YW, Chung RH.

BMC Genomics. 2015 May 15;16:381. doi: 10.1186/s12864-015-1620-3.

7.

Association tests using kernel-based measures of multi-locus genotype similarity between individuals.

Mukhopadhyay I, Feingold E, Weeks DE, Thalamuthu A.

Genet Epidemiol. 2010 Apr;34(3):213-21. doi: 10.1002/gepi.20451.

8.

Power-based, phase-informed selection of single nucleotide polymorphisms for disease association screens.

Saccone SF, Rice JP, Saccone NL.

Genet Epidemiol. 2006 Sep;30(6):459-70.

PMID:
16685721
9.
10.

A Hierarchical Clustering Method of Selecting Kernel SNP to Unify Informative SNP and Tag SNP.

Liao B, Li X, Cai L, Cao Z, Chen H.

IEEE/ACM Trans Comput Biol Bioinform. 2015 Jan-Feb;12(1):113-22. doi: 10.1109/TCBB.2014.2351797.

PMID:
26357082
11.
12.
13.

SNP-based pathway enrichment analysis for genome-wide association studies.

Weng L, Macciardi F, Subramanian A, Guffanti G, Potkin SG, Yu Z, Xie X.

BMC Bioinformatics. 2011 Apr 15;12:99. doi: 10.1186/1471-2105-12-99.

14.

Part 1. Statistical Learning Methods for the Effects of Multiple Air Pollution Constituents.

Coull BA, Bobb JF, Wellenius GA, Kioumourtzoglou MA, Mittleman MA, Koutrakis P, Godleski JJ.

Res Rep Health Eff Inst. 2015 Jun;(183 Pt 1-2):5-50.

PMID:
26333238
15.

Genome-wide algorithm for detecting CNV associations with diseases.

Xu Y, Peng B, Fu Y, Amos CI.

BMC Bioinformatics. 2011 Aug 9;12:331. doi: 10.1186/1471-2105-12-331.

16.

Bivariate association analysis for quantitative traits using generalized estimation equation.

Yang F, Tang Z, Deng H.

J Genet Genomics. 2009 Dec;36(12):733-43. doi: 10.1016/S1673-8527(08)60166-6.

PMID:
20129400
17.

Dynamic variable selection in SNP genotype autocalling from APEX microarray data.

Podder M, Welch WJ, Zamar RH, Tebbutt SJ.

BMC Bioinformatics. 2006 Nov 30;7:521.

18.

Unified variable selection in semi-parametric models.

Terry W, Zhang H, Maity A, Arshad H, Karmaus W.

Stat Methods Med Res. 2015 Oct 20. pii: 0962280215610928. [Epub ahead of print]

PMID:
26489906
19.
20.

Weighted SNP set analysis in genome-wide association study.

Dai H, Zhao Y, Qian C, Cai M, Zhang R, Chu M, Dai J, Hu Z, Shen H, Chen F.

PLoS One. 2013 Sep 30;8(9):e75897. doi: 10.1371/journal.pone.0075897.

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