440 related articles for article (PubMed ID: 19654115)
1. Multiple testing in genome-wide association studies via hidden Markov models.
Wei Z; Sun W; Wang K; Hakonarson H
Bioinformatics; 2009 Nov; 25(21):2802-8. PubMed ID: 19654115
[TBL] [Abstract][Full Text] [Related]
2. Hidden Markov models for controlling false discovery rate in genome-wide association analysis.
Wei Z
Methods Mol Biol; 2012; 802():337-44. PubMed ID: 22130891
[TBL] [Abstract][Full Text] [Related]
3. Large-scale multiple testing in genome-wide association studies via region-specific hidden Markov models.
Xiao J; Zhu W; Guo J
BMC Bioinformatics; 2013 Sep; 14():282. PubMed ID: 24067069
[TBL] [Abstract][Full Text] [Related]
4. Replicability analysis in genome-wide association studies via Cartesian hidden Markov models.
Wang P; Zhu W
BMC Bioinformatics; 2019 Mar; 20(1):146. PubMed ID: 30885122
[TBL] [Abstract][Full Text] [Related]
5. INTERSNP: genome-wide interaction analysis guided by a priori information.
Herold C; Steffens M; Brockschmidt FF; Baur MP; Becker T
Bioinformatics; 2009 Dec; 25(24):3275-81. PubMed ID: 19837719
[TBL] [Abstract][Full Text] [Related]
6. SNPHarvester: a filtering-based approach for detecting epistatic interactions in genome-wide association studies.
Yang C; He Z; Wan X; Yang Q; Xue H; Yu W
Bioinformatics; 2009 Feb; 25(4):504-11. PubMed ID: 19098029
[TBL] [Abstract][Full Text] [Related]
7. A powerful statistical framework for generalization testing in GWAS, with application to the HCHS/SOL.
Sofer T; Heller R; Bogomolov M; Avery CL; Graff M; North KE; Reiner AP; Thornton TA; Rice K; Benjamini Y; Laurie CC; Kerr KF
Genet Epidemiol; 2017 Apr; 41(3):251-258. PubMed ID: 28090672
[TBL] [Abstract][Full Text] [Related]
8. Uncovering networks from genome-wide association studies via circular genomic permutation.
Cabrera CP; Navarro P; Huffman JE; Wright AF; Hayward C; Campbell H; Wilson JF; Rudan I; Hastie ND; Vitart V; Haley CS
G3 (Bethesda); 2012 Sep; 2(9):1067-75. PubMed ID: 22973544
[TBL] [Abstract][Full Text] [Related]
9. SNP-based pathway enrichment analysis for genome-wide association studies.
Weng L; Macciardi F; Subramanian A; Guffanti G; Potkin SG; Yu Z; Xie X
BMC Bioinformatics; 2011 Apr; 12():99. PubMed ID: 21496265
[TBL] [Abstract][Full Text] [Related]
10. A hidden Markov random field model for genome-wide association studies.
Li H; Wei Z; Maris J
Biostatistics; 2010 Jan; 11(1):139-50. PubMed ID: 19822692
[TBL] [Abstract][Full Text] [Related]
11. Disease association tests by inferring ancestral haplotypes using a hidden markov model.
Su SY; Balding DJ; Coin LJ
Bioinformatics; 2008 Apr; 24(7):972-8. PubMed ID: 18296746
[TBL] [Abstract][Full Text] [Related]
12. Integrate multiple traits to detect novel trait-gene association using GWAS summary data with an adaptive test approach.
Guo B; Wu B
Bioinformatics; 2019 Jul; 35(13):2251-2257. PubMed ID: 30476000
[TBL] [Abstract][Full Text] [Related]
13. Shared genetic factors for age at natural menopause in Iranian and European women.
Rahmani M; Earp MA; Ramezani Tehrani F; Ataee M; Wu J; Treml M; Nudischer R; P-Behnami S; ; Perry JR; Murabito JM; Azizi F; Brooks-Wilson A
Hum Reprod; 2013 Jul; 28(7):1987-94. PubMed ID: 23592221
[TBL] [Abstract][Full Text] [Related]
14. A multi-SNP association test for complex diseases incorporating an optimal P-value threshold algorithm in nuclear families.
Wang YT; Sung PY; Lin PL; Yu YW; Chung RH
BMC Genomics; 2015 May; 16(1):381. PubMed ID: 25975968
[TBL] [Abstract][Full Text] [Related]
15. A hidden Markov approach for ascertaining cSNP genotypes from RNA sequence data in the presence of allelic imbalance by exploiting linkage disequilibrium.
Steibel JP; Wang H; Zhong PS
BMC Bioinformatics; 2015 Feb; 16():61. PubMed ID: 25887316
[TBL] [Abstract][Full Text] [Related]
16. Translating genome wide association study results to associations among common diseases: in silico study with an electronic medical record.
Anand V; Rosenman MB; Downs SM
Int J Med Inform; 2013 Sep; 82(9):864-74. PubMed ID: 23743324
[TBL] [Abstract][Full Text] [Related]
17. An optimum projection and noise reduction approach for detecting rare and common variants associated with complex diseases.
Turkmen A; Lin S
Hum Hered; 2012; 74(1):51-60. PubMed ID: 23154579
[TBL] [Abstract][Full Text] [Related]
18. A powerful approach to identify replicable variants in genome-wide association studies.
Li Y; Lei H; Wen X; Cao H
Am J Hum Genet; 2024 May; 111(5):966-978. PubMed ID: 38701746
[TBL] [Abstract][Full Text] [Related]
19. fcfdr: an R package to leverage continuous and binary functional genomic data in GWAS.
Hutchinson A; Liley J; Wallace C
BMC Bioinformatics; 2022 Jul; 23(1):310. PubMed ID: 35907789
[TBL] [Abstract][Full Text] [Related]
20. Assessing gene length biases in gene set analysis of Genome-Wide Association Studies.
Jia P; Tian J; Zhao Z
Int J Comput Biol Drug Des; 2010; 3(4):297-310. PubMed ID: 21297229
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]