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.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

146 related articles for article (PubMed ID: 25810429)

  • 1. DISSCO: direct imputation of summary statistics allowing covariates.
    Xu Z; Duan Q; Yan S; Chen W; Li M; Lange E; Li Y
    Bioinformatics; 2015 Aug; 31(15):2434-42. PubMed ID: 25810429
    [TBL] [Abstract][Full Text] [Related]  

  • 2. DIST: direct imputation of summary statistics for unmeasured SNPs.
    Lee D; Bigdeli TB; Riley BP; Fanous AH; Bacanu SA
    Bioinformatics; 2013 Nov; 29(22):2925-7. PubMed ID: 23990413
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Evaluation and application of summary statistic imputation to discover new height-associated loci.
    Rüeger S; McDaid A; Kutalik Z
    PLoS Genet; 2018 May; 14(5):e1007371. PubMed ID: 29782485
    [TBL] [Abstract][Full Text] [Related]  

  • 4. DISTMIX: direct imputation of summary statistics for unmeasured SNPs from mixed ethnicity cohorts.
    Lee D; Bigdeli TB; Williamson VS; Vladimirov VI; Riley BP; Fanous AH; Bacanu SA
    Bioinformatics; 2015 Oct; 31(19):3099-104. PubMed ID: 26059716
    [TBL] [Abstract][Full Text] [Related]  

  • 5. FAPI: Fast and accurate P-value Imputation for genome-wide association study.
    Kwan JS; Li MX; Deng JE; Sham PC
    Eur J Hum Genet; 2016 May; 24(5):761-6. PubMed ID: 26306642
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Adapt-Mix: learning local genetic correlation structure improves summary statistics-based analyses.
    Park DS; Brown B; Eng C; Huntsman S; Hu D; Torgerson DG; Burchard EG; Zaitlen N
    Bioinformatics; 2015 Jun; 31(12):i181-9. PubMed ID: 26072481
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Association studies with imputed variants using expectation-maximization likelihood-ratio tests.
    Huang KC; Sun W; Wu Y; Chen M; Mohlke KL; Lange LA; Li Y
    PLoS One; 2014; 9(11):e110679. PubMed ID: 25383782
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Imputation of genotypes from low density (50,000 markers) to high density (700,000 markers) of cows from research herds in Europe, North America, and Australasia using 2 reference populations.
    Pryce JE; Johnston J; Hayes BJ; Sahana G; Weigel KA; McParland S; Spurlock D; Krattenmacher N; Spelman RJ; Wall E; Calus MP
    J Dairy Sci; 2014 Mar; 97(3):1799-811. PubMed ID: 24472132
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Accurate and adaptive imputation of summary statistics in mixed-ethnicity cohorts.
    Togninalli M; Roqueiro D; ; Borgwardt KM
    Bioinformatics; 2018 Sep; 34(17):i687-i696. PubMed ID: 30423082
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Comparison among three variant callers and assessment of the accuracy of imputation from SNP array data to whole-genome sequence level in chicken.
    Ni G; Strom TM; Pausch H; Reimer C; Preisinger R; Simianer H; Erbe M
    BMC Genomics; 2015 Oct; 16():824. PubMed ID: 26486989
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Extending rare-variant testing strategies: analysis of noncoding sequence and imputed genotypes.
    Zawistowski M; Gopalakrishnan S; Ding J; Li Y; Grimm S; Zöllner S
    Am J Hum Genet; 2010 Nov; 87(5):604-17. PubMed ID: 21070896
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Proper conditional analysis in the presence of missing data: Application to large scale meta-analysis of tobacco use phenotypes.
    Jiang Y; Chen S; McGuire D; Chen F; Liu M; Iacono WG; Hewitt JK; Hokanson JE; Krauter K; Laakso M; Li KW; Lutz SM; McGue M; Pandit A; Zajac GJM; Boehnke M; Abecasis GR; Vrieze SI; Zhan X; Jiang B; Liu DJ
    PLoS Genet; 2018 Jul; 14(7):e1007452. PubMed ID: 30016313
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Effects of reduced panel, reference origin, and genetic relationship on imputation of genotypes in Hereford cattle.
    Huang Y; Maltecca C; Cassady JP; Alexander LJ; Snelling WM; MacNeil MD
    J Anim Sci; 2012 Dec; 90(12):4203-8. PubMed ID: 22859753
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A Unifying Framework for Imputing Summary Statistics in Genome-Wide Association Studies.
    Wu Y; Eskin E; Sankararaman S
    J Comput Biol; 2020 Mar; 27(3):418-428. PubMed ID: 32053016
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Comparison of different methods for imputing genome-wide marker genotypes in Swedish and Finnish Red Cattle.
    Ma P; Brøndum RF; Zhang Q; Lund MS; Su G
    J Dairy Sci; 2013 Jul; 96(7):4666-77. PubMed ID: 23684022
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Evaluation of the accuracy of imputed sequence variant genotypes and their utility for causal variant detection in cattle.
    Pausch H; MacLeod IM; Fries R; Emmerling R; Bowman PJ; Daetwyler HD; Goddard ME
    Genet Sel Evol; 2017 Feb; 49(1):24. PubMed ID: 28222685
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Imputation of missing genotypes from low- to high-density SNP panel in different population designs.
    He S; Wang S; Fu W; Ding X; Zhang Q
    Anim Genet; 2015 Feb; 46(1):1-7. PubMed ID: 25431355
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Accuracy of genotype imputation in sheep breeds.
    Hayes BJ; Bowman PJ; Daetwyler HD; Kijas JW; van der Werf JH
    Anim Genet; 2012 Feb; 43(1):72-80. PubMed ID: 22221027
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Imputation of missing single nucleotide polymorphism genotypes using a multivariate mixed model framework.
    Calus MP; Veerkamp RF; Mulder HA
    J Anim Sci; 2011 Jul; 89(7):2042-9. PubMed ID: 21357451
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Fast imputation using medium or low-coverage sequence data.
    VanRaden PM; Sun C; O'Connell JR
    BMC Genet; 2015 Jul; 16():82. PubMed ID: 26168789
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.