These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
341 related articles for article (PubMed ID: 21104886)
1. Analysis of untyped SNPs: maximum likelihood and imputation methods. Hu YJ; Lin DY Genet Epidemiol; 2010 Dec; 34(8):803-15. PubMed ID: 21104886 [TBL] [Abstract][Full Text] [Related]
2. ATRIUM: testing untyped SNPs in case-control association studies with related individuals. Wang Z; McPeek MS Am J Hum Genet; 2009 Nov; 85(5):667-78. PubMed ID: 19913122 [TBL] [Abstract][Full Text] [Related]
3. Fast and robust association tests for untyped SNPs in case-control studies. Allen AS; Satten GA; Bray SL; Dudbridge F; Epstein MP Hum Hered; 2010; 70(3):167-76. PubMed ID: 20689309 [TBL] [Abstract][Full Text] [Related]
4. Accuracy of genome-wide imputation of untyped markers and impacts on statistical power for association studies. Hao K; Chudin E; McElwee J; Schadt EE BMC Genet; 2009 Jun; 10():27. PubMed ID: 19531258 [TBL] [Abstract][Full Text] [Related]
5. Using imputed genotype data in the joint score tests for genetic association and gene-environment interactions in case-control studies. Song M; Wheeler W; Caporaso NE; Landi MT; Chatterjee N Genet Epidemiol; 2018 Mar; 42(2):146-155. PubMed ID: 29178451 [TBL] [Abstract][Full Text] [Related]
6. Jackknife-based gene-gene interactiontests for untyped SNPs. Song M BMC Genet; 2015 Jul; 16():85. PubMed ID: 26187382 [TBL] [Abstract][Full Text] [Related]
7. Genome-wide association of breast cancer: composite likelihood with imputed genotypes. Politopoulos I; Gibson J; Tapper W; Ennis S; Eccles D; Collins A Eur J Hum Genet; 2011 Feb; 19(2):194-9. PubMed ID: 20959865 [TBL] [Abstract][Full Text] [Related]
8. 1000 Genomes-based imputation identifies novel and refined associations for the Wellcome Trust Case Control Consortium phase 1 Data. Huang J; Ellinghaus D; Franke A; Howie B; Li Y Eur J Hum Genet; 2012 Jul; 20(7):801-5. PubMed ID: 22293688 [TBL] [Abstract][Full Text] [Related]
9. Simultaneous analysis of all SNPs in genome-wide and re-sequencing association studies. Hoggart CJ; Whittaker JC; De Iorio M; Balding DJ PLoS Genet; 2008 Jul; 4(7):e1000130. PubMed ID: 18654633 [TBL] [Abstract][Full Text] [Related]
10. Increasing power of genome-wide association studies by collecting additional single-nucleotide polymorphisms. Kostem E; Lozano JA; Eskin E Genetics; 2011 Jun; 188(2):449-60. PubMed ID: 21467568 [TBL] [Abstract][Full Text] [Related]
11. Genotype imputation in case-only studies of gene-environment interaction: validity and power. AleknonytÄ—-Resch M; Szymczak S; Freitag-Wolf S; Dempfle A; Krawczak M Hum Genet; 2021 Aug; 140(8):1217-1228. PubMed ID: 34041609 [TBL] [Abstract][Full Text] [Related]
12. Evaluating the effects of imputation on the power, coverage, and cost efficiency of genome-wide SNP platforms. Anderson CA; Pettersson FH; Barrett JC; Zhuang JJ; Ragoussis J; Cardon LR; Morris AP Am J Hum Genet; 2008 Jul; 83(1):112-9. PubMed ID: 18589396 [TBL] [Abstract][Full Text] [Related]
13. Multi-SNP Haplotype Analysis Methods for Association Analysis. Stram DO Methods Mol Biol; 2017; 1666():485-504. PubMed ID: 28980261 [TBL] [Abstract][Full Text] [Related]
14. Fast and accurate imputation of summary statistics enhances evidence of functional enrichment. Pasaniuc B; Zaitlen N; Shi H; Bhatia G; Gusev A; Pickrell J; Hirschhorn J; Strachan DP; Patterson N; Price AL Bioinformatics; 2014 Oct; 30(20):2906-14. PubMed ID: 24990607 [TBL] [Abstract][Full Text] [Related]
15. Enhanced statistical tests for GWAS in admixed populations: assessment using African Americans from CARe and a Breast Cancer Consortium. Pasaniuc B; Zaitlen N; Lettre G; Chen GK; Tandon A; Kao WH; Ruczinski I; Fornage M; Siscovick DS; Zhu X; Larkin E; Lange LA; Cupples LA; Yang Q; Akylbekova EL; Musani SK; Divers J; Mychaleckyj J; Li M; Papanicolaou GJ; Millikan RC; Ambrosone CB; John EM; Bernstein L; Zheng W; Hu JJ; Ziegler RG; Nyante SJ; Bandera EV; Ingles SA; Press MF; Chanock SJ; Deming SL; Rodriguez-Gil JL; Palmer CD; Buxbaum S; Ekunwe L; Hirschhorn JN; Henderson BE; Myers S; Haiman CA; Reich D; Patterson N; Wilson JG; Price AL PLoS Genet; 2011 Apr; 7(4):e1001371. PubMed ID: 21541012 [TBL] [Abstract][Full Text] [Related]
16. Quick, "imputation-free" meta-analysis with proxy-SNPs. Meesters C; Leber M; Herold C; Angisch M; Mattheisen M; Drichel D; Lacour A; Becker T BMC Bioinformatics; 2012 Sep; 13():231. PubMed ID: 22971100 [TBL] [Abstract][Full Text] [Related]
17. Validation of genotype imputation in Southeast Asian populations and the effect of single nucleotide polymorphism annotation on imputation outcome. Lert-Itthiporn W; Suktitipat B; Grove H; Sakuntabhai A; Malasit P; Tangthawornchaikul N; Matsuda F; Suriyaphol P BMC Med Genet; 2018 Feb; 19(1):23. PubMed ID: 29439659 [TBL] [Abstract][Full Text] [Related]
18. A flexible genome-wide bootstrap method that accounts for ranking and threshold-selection bias in GWAS interpretation and replication study design. Faye LL; Sun L; Dimitromanolakis A; Bull SB Stat Med; 2011 Jul; 30(15):1898-912. PubMed ID: 21538984 [TBL] [Abstract][Full Text] [Related]
19. Simple and efficient analysis of disease association with missing genotype data. Lin DY; Hu Y; Huang BE Am J Hum Genet; 2008 Feb; 82(2):444-52. PubMed ID: 18252224 [TBL] [Abstract][Full Text] [Related]
20. MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes. Li Y; Willer CJ; Ding J; Scheet P; Abecasis GR Genet Epidemiol; 2010 Dec; 34(8):816-34. PubMed ID: 21058334 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]