335 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.
Aleknonytė-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. 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]
19. 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]
20. 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]
[Next] [New Search]
