Recursive Partitioning Analysis of Complex Disease Pharmacogenetic Studies. I. Motivation and Overview

• Hallberg P , MelhusH: Candidate genes in the pharmacogenomics of antihypertensive treatment – a review and future aspects.Curr. Opin. Pharmacogenomics2, 83–112 (2004).
   Google Scholar
• Merikangas KR , RischN: Genomic priorities and public health.Science302(5645), 599–601 (2003).
   PubMed Web of Science ®Google Scholar
• Wright A , CharlesworthB, RudanI, CarothersA, CampbellH: A polygenic basis for late-onset disease.Trends Genet.19, 97–106 (2003).
   PubMed Web of Science ®Google Scholar
• Frank IE , FriedmanJH: A statistical view of some chemometrics regression tools.Technometrics35, 109–135 (1993).
   Web of Science ®Google Scholar
• Lander ES , KruglyakL: Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results.Nat. Genet.11, 241–247 (1995).
   PubMed Web of Science ®Google Scholar
• Rothman KJ : No adjustments are needed for multiple comparisons.Epidemiology1, 43–46 (1990).
   PubMedGoogle Scholar
• Rothman KJ , GreenhouseS: Modern Epidemiology. Lippincott Williams and Wilkins, New York (1998).
   Google Scholar
• Zaykin DV , YoungSS: Recursive partitioning analysis of complex disease pharmacogenetic studies. II. Statistical considerations.Pharmacogenomics6(1), 77–89 (2005).
   PubMed Web of Science ®Google Scholar
• Rao DC : CAT scans, PET scans and genomic scans.Genet. Epidemiol.15, 1–18 (1998).
   PubMed Web of Science ®Google Scholar
• Cox NJ , FriggeM, NicolaeDL et al.: Loci on chromosomes 2 (NIDDM1) and 15 interact to increase susceptibility to Type 2 diabetes.Nat. Genet.21, 213–215 (1999).
   PubMed Web of Science ®Google Scholar
• Cook NR , ZeeRYL, RidkerPM: Tree and spline based association analysis of gene–gene interaction models for ischemic stroke.Statist. Med.23, 1439–1453 (2004).
   PubMed Web of Science ®Google Scholar
• Wilcox MA , SmollerJW, LunettaKL, NeubergD: Using recursive partitioning for exploration and follow-up of linkage and association analysis.Genet. Epidemiol.17(Supp. 1), S391–S396 (1999).
   PubMed Web of Science ®Google Scholar
• Zhang H , BonneyG: Use of classification trees for association studies.Genet. Epidemiol.19, 323–332 (2000).
   PubMed Web of Science ®Google Scholar
• Province MA , ShannonWD, RaoDC: Classification methods for confronting heterogeneity.Adv Genet.42, 273–286 (2001).
   PubMed Web of Science ®Google Scholar
• Shannon WD , ProvinceMA, RaoDC: Tree-based recursive partitioning methods for subdividing sibpairs into relatively more homogeneous subgroups.Genet. Epidemiol.20, 293–306 (2001).
   PubMed Web of Science ®Google Scholar
• Foulkes AS , DeGruttolaV, HertogsK: Combining genotype groups and recursive partitioning: an application to huyman immunodeficiency virus type 1 genetics data.J. Royal Stat. Soc.53, 311–323 (2004).
   Google Scholar
• Ruczinski I , KooperbergC, LeBlancML: Exploring interactions in high-dimensional genomic data: an overview of logic regression with applications.J. Multivariate Analysis90, 178–195 (2004).
   Web of Science ®Google Scholar
• Bell J : Predicting disease using genomics.Nature429, 453–456 (2004).
   PubMed Web of Science ®Google Scholar
• Evans WE , RellingMV: Moving towards individualized medicine with pharmacogenomics.Nature429, 464–468 (2004).
   PubMed Web of Science ®Google Scholar
• Morris RW , KaplanNL: On the advantage of haplotype analysis in the presence of multiple disease susceptibility alleles.Genet. Epidemiol.23, 221–233 (2002).
   PubMed Web of Science ®Google Scholar
• Schaid DJ : Relative efficiency of ambiguous vs. directly measured haplotype frequencies.Genet. Epidemiol.23, 426–443 (2002).
   PubMed Web of Science ®Google Scholar
• Zaykin DV , WestfallPH, YoungSS, KarnoubMA, WagnerMJ, EhmMG: Testing association of statistically inferred haplotypes with discrete and continuous traits in samples of unrelated individuals.Hum. Hered.53, 79–91 (2002).
   PubMed Web of Science ®Google Scholar
• Stram DO , Leigh Pearce C, Bretsky P et al.: Modeling and E-M estimation of haplotype-specific relative risks from genotype data for a case-control study of unrelated individuals. Hum. Hered.55, 179–190 (2003).
   PubMed Web of Science ®Google Scholar
• Epstein MP , SattenGA: Inference on haplotype effects in case-control studies using unphased genotype data.Am. J. Hum. Genet.73(6), 1316–1329 (2003).
   PubMed Web of Science ®Google Scholar
• Lin DY : Haplotype-based association analysis in cohort studies of unrelated individuals.Genet. Epidemiol.26, 255–264 (2004).
   PubMed Web of Science ®Google Scholar
• Curran MD : Statistical Modeling for Genetics: Pharmacogenetics, Molecular Evolution and Complex Traits. University of North Carolina at Chapel Hill (2003) (Dissertation).
   Google Scholar
• Hawkins DM , KassGV: Automatic interaction detection. In: Topics in Applied Multivariate Analysis. Hawkins DM (Ed.), Cambridge University Press, Cambridge, UK, 269–302 (1982).
   Google Scholar
• Breiman L , FriedmanJH, OlshenRA, Stone CJ: Classification and Regression Trees. Wadsworth, Belmont, CA, USA (1984).
   Google Scholar
• Quilan JR : C4.5: Programs for Machine Learning. Morgan Kaufmann, San Mateo, CA, USA (1993).
   Google Scholar
• Rusinko A 3rd, Farmen MW, Lambert CG, Brown PL, Young SS: Analysis of a large structure/biological activity data set using recursive partitioning. J. Chem. Inf. Comput. Science39, 1017–1026 (1999).
   PubMedGoogle Scholar
• Zaykin DV , MengZ, GhoshSK: Interval estimation of genetic susceptibility for retrospective case-control studies.BMC Genet.5(1), 9 (2004).
   Google Scholar
• Hastie T , TibshiraniR, FriedmanJ: The Elements of Statistical Learning. Springer, New York, USA (2001).
   Google Scholar
• Devlin B , RoederK, WassermanL: Genomic control, a new approach to genetic-based association studies.Theor. Popul. Biol.60, 155–166 (2001).
   PubMed Web of Science ®Google Scholar
• Westfall PH , YoungSS: Resampling-Based Multiple Testing. Wiley, New York, USA (1993).
   Google Scholar
• Burman P : A comparative study of ordinary cross-validation, ν-fold cross-validation and repeated learning-testing methods.Biometrika76, 503–514 (1988).
   Web of Science ®Google Scholar

Patent

• Farmen MW, Lambert CG, Rusinko AR 3rd, Young SS: Statistical deconvoluting of mixtures: US6434542 (1997).
   Google Scholar

Websites

• http://www.ukbiobank.ac.uk/ The UK Biobank project.
   Google Scholar
• http://www.affymetrix.com/index.affx Affymetrix homepage.
   Google Scholar
• www.goldenhelix.com HelixTree (2004).
   Google Scholar