Summary of contributions to GAW15 Group 13: candidate gene association studies.

@article{citeulike:3025933, abstract = {Here we summarize the contributions to Group 13 of the Genetic Analysis Workshop 15 held in St. Pete Beach, Florida, on November 12-14, 2006. The focus of this group was to identify candidate genes associated with rheumatoid arthritis or surrogate outcomes. The association methods proposed in this group were diverse, from better known approaches, such as logistic regression for single nucleotide polymorphism (SNP) analysis and haplotype sharing tests to methods less familiar to genetic epidemiologists, such as machine learning and visualization methods. The majority of papers analyzed Genetic Analysis Workshop 15 Problems 2 (rheumatoid arthritis data) and 3 (simulated data). The highlighted points of this group analyses were: (1) haplotype-based statistics can be more powerful than single SNP analysis for risk-locus localization; (2) considering linkage disequilibrium block structure in haplotype analysis may reduce the likelihood of false-positive results; and (3) visual representation of genetic models for continuous covariates may help identify SNPs associated with the underlying quantitative trait loci.}, address = {Division of Biostatistics, Department of Health Science Research, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA. mandrade@mayo.edu}, author = {de Andrade, M. and Allen, A. S. and Brinza, D. and Cheng, R. and Da, Y. and de Vries, A. R. and Ewhida, A. and Feng, Z. and Jung, H. and Hsieh, H. J. and K\"{o}hler, K. and Liu, Y. and Liu-Mares, W. and Luan, J. and Marquard, V. and Nolte, I. M. and Oh, S. and Platt, A. and Qin, X. and Yoo, Y. J. and Yuan, A. and Tian, X. and Won, S. }, citeulike-article-id = {3025933}, doi = {http://dx.doi.org/10.1002/gepi.20287}, issn = {0741-0395}, journal = {Genetic epidemiology}, keywords = {association, dataset}, posted-at = {2008-07-22 02:02:49}, priority = {2}, title = {Summary of contributions to GAW15 Group 13: candidate gene association studies.}, url = {http://dx.doi.org/10.1002/gepi.20287}, volume = {31 Suppl 1}, year = {2007} }

TY - JOUR ID - citeulike:3025933 L3 - citeulike-article-id:3025933 TI - Summary of contributions to GAW15 Group 13: candidate gene association studies. JF - Genetic epidemiology VL - 31 Suppl 1 AD - Division of Biostatistics, Department of Health Science Research, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA. mandrade@mayo.edu SN - 0741-0395 N2 - Here we summarize the contributions to Group 13 of the Genetic Analysis Workshop 15 held in St. Pete Beach, Florida, on November 12-14, 2006. The focus of this group was to identify candidate genes associated with rheumatoid arthritis or surrogate outcomes. The association methods proposed in this group were diverse, from better known approaches, such as logistic regression for single nucleotide polymorphism (SNP) analysis and haplotype sharing tests to methods less familiar to genetic epidemiologists, such as machine learning and visualization methods. The majority of papers analyzed Genetic Analysis Workshop 15 Problems 2 (rheumatoid arthritis data) and 3 (simulated data). The highlighted points of this group analyses were: (1) haplotype-based statistics can be more powerful than single SNP analysis for risk-locus localization; (2) considering linkage disequilibrium block structure in haplotype analysis may reduce the likelihood of false-positive results; and (3) visual representation of genetic models for continuous covariates may help identify SNPs associated with the underlying quantitative trait loci. KW - association KW - dataset AU - de Andrade, M AU - Allen, AS AU - Brinza, D AU - Cheng, R AU - Da, Y AU - de Vries, AR AU - Ewhida, A AU - Feng, Z AU - Jung, H AU - Hsieh, HJ AU - Köhler, K AU - Liu, Y AU - Liu-Mares, W AU - Luan, J AU - Marquard, V AU - Nolte, IM AU - Oh, S AU - Platt, A AU - Qin, X AU - Yoo, YJ AU - Yuan, A AU - Tian, X AU - Won, S PY - 2007/// UR - http://dx.doi.org/10.1002/gepi.20287 ER -