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Items: 1 to 20 of 120

1.

PleioGRiP: genetic risk prediction with pleiotropy.

Hartley SW, Sebastiani P.

Bioinformatics. 2013 Apr 15;29(8):1086-8. doi: 10.1093/bioinformatics/btt081. Epub 2013 Feb 17.

2.

Bayesian methods for multivariate modeling of pleiotropic SNP associations and genetic risk prediction.

Hartley SW, Monti S, Liu CT, Steinberg MH, Sebastiani P.

Front Genet. 2012 Sep 11;3:176. doi: 10.3389/fgene.2012.00176. eCollection 2012.

3.

A Bayesian method for comparing and combining binary classifiers in the absence of a gold standard.

Keith JM, Davey CM, Boyd SE.

BMC Bioinformatics. 2012 Jul 27;13:179. doi: 10.1186/1471-2105-13-179.

4.

Bag of Naïve Bayes: biomarker selection and classification from genome-wide SNP data.

Sambo F, Trifoglio E, Di Camillo B, Toffolo GM, Cobelli C.

BMC Bioinformatics. 2012;13 Suppl 14:S2. doi: 10.1186/1471-2105-13-S14-S2. Epub 2012 Sep 7.

5.

Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes.

Wang Y, Goh W, Wong L, Montana G; Alzheimer's Disease Neuroimaging Initiative.

BMC Bioinformatics. 2013;14 Suppl 16:S6. doi: 10.1186/1471-2105-14-S16-S6. Epub 2013 Oct 22.

6.

Estimation of pleiotropy between complex diseases using single-nucleotide polymorphism-derived genomic relationships and restricted maximum likelihood.

Lee SH, Yang J, Goddard ME, Visscher PM, Wray NR.

Bioinformatics. 2012 Oct 1;28(19):2540-2. Epub 2012 Jul 26.

7.

Assessing multivariate gene-metabolome associations with rare variants using Bayesian reduced rank regression.

Marttinen P, Pirinen M, Sarin AP, Gillberg J, Kettunen J, Surakka I, Kangas AJ, Soininen P, O'Reilly P, Kaakinen M, Kähönen M, Lehtimäki T, Ala-Korpela M, Raitakari OT, Salomaa V, Järvelin MR, Ripatti S, Kaski S.

Bioinformatics. 2014 Jul 15;30(14):2026-34. doi: 10.1093/bioinformatics/btu140. Epub 2014 Mar 24.

8.

Implementing a QTL detection study (GWAS) using genomic prediction methodology.

Garrick DJ, Fernando RL.

Methods Mol Biol. 2013;1019:275-98. doi: 10.1007/978-1-62703-447-0_11.

PMID:
23756895
9.

A Bayesian approach using covariance of single nucleotide polymorphism data to detect differences in linkage disequilibrium patterns between groups of individuals.

Clark TG, Campino SG, Anastasi E, Auburn S, Teo YY, Small K, Rockett KA, Kwiatkowski DP, Holmes CC.

Bioinformatics. 2010 Aug 15;26(16):1999-2003. doi: 10.1093/bioinformatics/btq327. Epub 2010 Jun 16.

10.

GAPIT: genome association and prediction integrated tool.

Lipka AE, Tian F, Wang Q, Peiffer J, Li M, Bradbury PJ, Gore MA, Buckler ES, Zhang Z.

Bioinformatics. 2012 Sep 15;28(18):2397-9. Epub 2012 Jul 13.

11.

repfdr: a tool for replicability analysis for genome-wide association studies.

Heller R, Yaacoby S, Yekutieli D.

Bioinformatics. 2014 Oct 15;30(20):2971-2. doi: 10.1093/bioinformatics/btu434. Epub 2014 Jul 9.

12.

Hierarchical Naive Bayes for genetic association studies.

Malovini A, Barbarini N, Bellazzi R, de Michelis F.

BMC Bioinformatics. 2012;13 Suppl 14:S6. doi: 10.1186/1471-2105-13-S14-S6. Epub 2012 Sep 7.

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.

Genome-wide prediction of discrete traits using Bayesian regressions and machine learning.

González-Recio O, Forni S.

Genet Sel Evol. 2011 Feb 17;43:7. doi: 10.1186/1297-9686-43-7.

15.

Efficient network-guided multi-locus association mapping with graph cuts.

Azencott CA, Grimm D, Sugiyama M, Kawahara Y, Borgwardt KM.

Bioinformatics. 2013 Jul 1;29(13):i171-9. doi: 10.1093/bioinformatics/btt238.

16.

SNPHarvester: a filtering-based approach for detecting epistatic interactions in genome-wide association studies.

Yang C, He Z, Wan X, Yang Q, Xue H, Yu W.

Bioinformatics. 2009 Feb 15;25(4):504-11. doi: 10.1093/bioinformatics/btn652. Epub 2008 Dec 19.

17.

Path: a tool to facilitate pathway-based genetic association analysis.

Zamar D, Tripp B, Ellis G, Daley D.

Bioinformatics. 2009 Sep 15;25(18):2444-6. doi: 10.1093/bioinformatics/btp431. Epub 2009 Jul 23.

18.

The Bayesian lasso for genome-wide association studies.

Li J, Das K, Fu G, Li R, Wu R.

Bioinformatics. 2011 Feb 15;27(4):516-23. doi: 10.1093/bioinformatics/btq688. Epub 2010 Dec 14.

19.

Predicting unobserved phenotypes for complex traits from whole-genome SNP data.

Lee SH, van der Werf JH, Hayes BJ, Goddard ME, Visscher PM.

PLoS Genet. 2008 Oct;4(10):e1000231. doi: 10.1371/journal.pgen.1000231. Epub 2008 Oct 24.

20.

Bayesian variable and model selection methods for genetic association studies.

Fridley BL.

Genet Epidemiol. 2009 Jan;33(1):27-37. doi: 10.1002/gepi.20353.

PMID:
18618760
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