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BMC Proceedings|December 19, 2009
Non-redundant summary scores applied to the North American Rheumatoid Arthritis Consortium datasetNathan D PankratzBMC Proceedings|December 19, 2009
The effect of minor allele frequency on the likelihood of obtaining false positivesMeredith E Tabangin, Jessica G Woo, Lisa J MartinBMC Proceedings|December 19, 2009
Multivariate association analysis of the components of metabolic syndrome from the Framingham Heart StudyAllison R Baker, Robert J Goodloe, Emma K Larkin, et al.BMC Proceedings|December 19, 2009
A combinatorial approach for detecting gene-gene interaction using multiple traits of Genetic Analysis Workshop 16 rheumatoid arthritis dataXiaoqi Cui, Qiuying Sha, Shuanglin Zhang, et al.BMC Proceedings|December 19, 2009
ACPA: automated cluster plot analysis of genotype dataArne Schillert, Daniel F Schwarz, Maren Vens, et al.BMC Proceedings|December 19, 2009
Predictive modeling in case-control single-nucleotide polymorphism studies in the presence of population stratification: a case study using Genetic Analysis Workshop 16 Problem 1 datasetNiloofar Arshadi, Billy Chang, Rafal KustraBMC Proceedings|December 19, 2009
Detecting single-nucleotide polymorphism by single-nucleotide polymorphism interactions in rheumatoid arthritis using a two-step approach with machine learning and a Bayesian threshold least absolute shrinkage and selection operator (LASSO) modelOscar González-Recio, Evangelina López de Maturana, Andrés T Vega, et al.BMC Proceedings|December 19, 2009
Evaluation of random forests performance for genome-wide association studies in the presence of interaction effectsYoonhee Kim, Robert Wojciechowski, Heejong Sung, et al.BMC Proceedings|December 19, 2009
Epistatic interactions of CDKN2B-TCF7L2 for risk of type 2 diabetes and of CDKN2B-JAZF1 for triglyceride/high-density lipoprotein ratio longitudinal change: evidence from the Framingham Heart StudyPing An, Mary Feitosa, Shamika Ketkar, et al.BMC Proceedings|December 19, 2009
Power and false-positive rates for the restricted partition method (RPM) in a large candidate gene data setRobert Culverhouse, Wu Jin, Carol H Jin, et al.Pageof 101