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Items: 1 to 20 of 114

1.

PUMA: a unified framework for penalized multiple regression analysis of GWAS data.

Hoffman GE, Logsdon BA, Mezey JG.

PLoS Comput Biol. 2013;9(6):e1003101. doi: 10.1371/journal.pcbi.1003101. Epub 2013 Jun 27.

2.
3.

A novel variational Bayes multiple locus Z-statistic for genome-wide association studies with Bayesian model averaging.

Logsdon BA, Carty CL, Reiner AP, Dai JY, Kooperberg C.

Bioinformatics. 2012 Jul 1;28(13):1738-44. doi: 10.1093/bioinformatics/bts261. Epub 2012 May 4.

4.

Integrative pathway-based approach for genome-wide association studies: identification of new pathways for rheumatoid arthritis and type 1 diabetes.

B├╝chel F, Mittag F, Wrzodek C, Zell A, Gasser T, Sharma M.

PLoS One. 2013 Oct 25;8(10):e78577. doi: 10.1371/journal.pone.0078577. eCollection 2013.

5.

iLOCi: a SNP interaction prioritization technique for detecting epistasis in genome-wide association studies.

Piriyapongsa J, Ngamphiw C, Intarapanich A, Kulawonganunchai S, Assawamakin A, Bootchai C, Shaw PJ, Tongsima S.

BMC Genomics. 2012;13 Suppl 7:S2. doi: 10.1186/1471-2164-13-S7-S2. Epub 2012 Dec 13.

6.

Causal graph-based analysis of genome-wide association data in rheumatoid arthritis.

Alekseyenko AV, Lytkin NI, Ai J, Ding B, Padyukov L, Aliferis CF, Statnikov A.

Biol Direct. 2011 May 18;6:25. doi: 10.1186/1745-6150-6-25.

7.

Penalized multimarker vs. single-marker regression methods for genome-wide association studies of quantitative traits.

Yi H, Breheny P, Imam N, Liu Y, Hoeschele I.

Genetics. 2015 Jan;199(1):205-22. doi: 10.1534/genetics.114.167817. Epub 2014 Oct 28.

8.

SNP-SNP interactions discovered by logic regression explain Crohn's disease genetics.

Dinu I, Mahasirimongkol S, Liu Q, Yanai H, Sharaf Eldin N, Kreiter E, Wu X, Jabbari S, Tokunaga K, Yasui Y.

PLoS One. 2012;7(10):e43035. doi: 10.1371/journal.pone.0043035. Epub 2012 Oct 12.

9.

Penalized Regression and Risk Prediction in Genome-Wide Association Studies.

Austin E, Pan W, Shen X.

Stat Anal Data Min. 2013 Aug 1;6(4). doi: 10.1002/sam.11183.

10.

GWIS--model-free, fast and exhaustive search for epistatic interactions in case-control GWAS.

Goudey B, Rawlinson D, Wang Q, Shi F, Ferra H, Campbell RM, Stern L, Inouye MT, Ong CS, Kowalczyk A.

BMC Genomics. 2013;14 Suppl 3:S10. doi: 10.1186/1471-2164-14-S3-S10. Epub 2013 May 28.

11.

SNP selection in genome-wide and candidate gene studies via penalized logistic regression.

Ayers KL, Cordell HJ.

Genet Epidemiol. 2010 Dec;34(8):879-91. doi: 10.1002/gepi.20543.

12.

Genome-wide association analysis by lasso penalized logistic regression.

Wu TT, Chen YF, Hastie T, Sobel E, Lange K.

Bioinformatics. 2009 Mar 15;25(6):714-21. doi: 10.1093/bioinformatics/btp041. Epub 2009 Jan 28.

14.

Novel rheumatoid arthritis susceptibility locus at 22q12 identified in an extended UK genome-wide association study.

Orozco G, Viatte S, Bowes J, Martin P, Wilson AG, Morgan AW, Steer S, Wordsworth P, Hocking LJ; UK Rheumatoid Arthritis Genetics Consortium; Wellcome Trust Case Control Consortium; Biologics in Rheumatoid Arthritis Genetics and Genomics Study Syndicate Consortium, Barton A, Worthington J, Eyre S.

Arthritis Rheumatol. 2014 Jan;66(1):24-30. doi: 10.1002/art.38196.

15.

Penalized regression approaches to testing for quantitative trait-rare variant association.

Kim S, Pan W, Shen X.

Front Genet. 2014 May 13;5:121. doi: 10.3389/fgene.2014.00121. eCollection 2014.

16.

Penalized regression for genome-wide association screening of sequence data.

Zhou H, Alexander DH, Sehl ME, Sinsheimer JS, Sobel EM, Lange K.

Pac Symp Biocomput. 2011:106-17.

17.

Integrating pathway analysis and genetics of gene expression for genome-wide association studies.

Zhong H, Yang X, Kaplan LM, Molony C, Schadt EE.

Am J Hum Genet. 2010 Apr 9;86(4):581-91. doi: 10.1016/j.ajhg.2010.02.020. Epub 2010 Mar 25.

18.

Integrative genomic deconvolution of rheumatoid arthritis GWAS loci into gene and cell type associations.

Walsh AM, Whitaker JW, Huang CC, Cherkas Y, Lamberth SL, Brodmerkel C, Curran ME, Dobrin R.

Genome Biol. 2016 Apr 30;17:79. doi: 10.1186/s13059-016-0948-6.

19.

An efficient hierarchical generalized linear mixed model for pathway analysis of genome-wide association studies.

Wang L, Jia P, Wolfinger RD, Chen X, Grayson BL, Aune TM, Zhao Z.

Bioinformatics. 2011 Mar 1;27(5):686-92. doi: 10.1093/bioinformatics/btq728. Epub 2011 Jan 25.

20.

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.

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