435 related articles for article (PubMed ID: 33604756)
41. The open targets post-GWAS analysis pipeline.
Peat G; Jones W; Nuhn M; Marugán JC; Newell W; Dunham I; Zerbino D
Bioinformatics; 2020 May; 36(9):2936-2937. PubMed ID: 31930349
[TBL] [Abstract][Full Text] [Related]
42. ColocQuiaL: a QTL-GWAS colocalization pipeline.
Chen BY; Bone WP; Lorenz K; Levin M; Ritchie MD; Voight BF
Bioinformatics; 2022 Sep; 38(18):4409-4411. PubMed ID: 35894642
[TBL] [Abstract][Full Text] [Related]
43. Investigation of multi-trait associations using pathway-based analysis of GWAS summary statistics.
Pei G; Sun H; Dai Y; Liu X; Zhao Z; Jia P
BMC Genomics; 2019 Feb; 20(Suppl 1):79. PubMed ID: 30712509
[TBL] [Abstract][Full Text] [Related]
44. An open access database of genome-wide association results.
Johnson AD; O'Donnell CJ
BMC Med Genet; 2009 Jan; 10():6. PubMed ID: 19161620
[TBL] [Abstract][Full Text] [Related]
45. Local Genetic Correlation Gives Insights into the Shared Genetic Architecture of Complex Traits.
Shi H; Mancuso N; Spendlove S; Pasaniuc B
Am J Hum Genet; 2017 Nov; 101(5):737-751. PubMed ID: 29100087
[TBL] [Abstract][Full Text] [Related]
46. Comparative analysis of the GBLUP, emBayesB, and GWAS algorithms to predict genetic values in large yellow croaker (Larimichthys crocea).
Dong L; Xiao S; Wang Q; Wang Z
BMC Genomics; 2016 Jun; 17():460. PubMed ID: 27301965
[TBL] [Abstract][Full Text] [Related]
47. An atlas of genetic correlations across human diseases and traits.
Bulik-Sullivan B; Finucane HK; Anttila V; Gusev A; Day FR; Loh PR; ; ; ; Duncan L; Perry JR; Patterson N; Robinson EB; Daly MJ; Price AL; Neale BM
Nat Genet; 2015 Nov; 47(11):1236-41. PubMed ID: 26414676
[TBL] [Abstract][Full Text] [Related]
48. PRIMe: a method for characterization and evaluation of pleiotropic regions from multiple genome-wide association studies.
Huang J; Johnson AD; O'Donnell CJ
Bioinformatics; 2011 May; 27(9):1201-6. PubMed ID: 21398673
[TBL] [Abstract][Full Text] [Related]
49. Genome-Wide Association Study for Major Biofuel Traits in Sorghum Using Minicore Collection.
Rayaprolu L; Selvanayagam S; Rao DM; Gupta R; Das RR; Rathore A; Gandham P; Kiranmayee KNSU; Deshpande SP; Are AK
Protein Pept Lett; 2021; 28(8):909-928. PubMed ID: 33588716
[TBL] [Abstract][Full Text] [Related]
50. Trans-eQTLs identified in whole blood have limited influence on complex disease biology.
Yap CX; Lloyd-Jones L; Holloway A; Smartt P; Wray NR; Gratten J; Powell JE
Eur J Hum Genet; 2018 Sep; 26(9):1361-1368. PubMed ID: 29891877
[TBL] [Abstract][Full Text] [Related]
51. EPIQ-efficient detection of SNP-SNP epistatic interactions for quantitative traits.
Arkin Y; Rahmani E; Kleber ME; Laaksonen R; März W; Halperin E
Bioinformatics; 2014 Jun; 30(12):i19-25. PubMed ID: 24931983
[TBL] [Abstract][Full Text] [Related]
52. Fast Genome-Wide QTL Association Mapping on Pedigree and Population Data.
Zhou H; Blangero J; Dyer TD; Chan KK; Lange K; Sobel EM
Genet Epidemiol; 2017 Apr; 41(3):174-186. PubMed ID: 27943406
[TBL] [Abstract][Full Text] [Related]
53. Alcohol Dependence Genetics: Lessons Learned From Genome-Wide Association Studies (GWAS) and Post-GWAS Analyses.
Hart AB; Kranzler HR
Alcohol Clin Exp Res; 2015 Aug; 39(8):1312-27. PubMed ID: 26110981
[TBL] [Abstract][Full Text] [Related]
54. JEPEG: a summary statistics based tool for gene-level joint testing of functional variants.
Lee D; Williamson VS; Bigdeli TB; Riley BP; Fanous AH; Vladimirov VI; Bacanu SA
Bioinformatics; 2015 Apr; 31(8):1176-82. PubMed ID: 25505091
[TBL] [Abstract][Full Text] [Related]
55. Structural equation modeling for hypertension and type 2 diabetes based on multiple SNPs and multiple phenotypes.
Jeon S; Shin JY; Yee J; Park T; Park M
PLoS One; 2019; 14(9):e0217189. PubMed ID: 31513605
[TBL] [Abstract][Full Text] [Related]
56. Powerful and efficient SNP-set association tests across multiple phenotypes using GWAS summary data.
Guo B; Wu B
Bioinformatics; 2019 Apr; 35(8):1366-1372. PubMed ID: 30239606
[TBL] [Abstract][Full Text] [Related]
57. Genome wide association studies using a new nonparametric model reveal the genetic architecture of 17 agronomic traits in an enlarged maize association panel.
Yang N; Lu Y; Yang X; Huang J; Zhou Y; Ali F; Wen W; Liu J; Li J; Yan J
PLoS Genet; 2014 Sep; 10(9):e1004573. PubMed ID: 25211220
[TBL] [Abstract][Full Text] [Related]
58. An efficient genome-wide association test for multivariate phenotypes based on the Fisher combination function.
Yang JJ; Li J; Williams LK; Buu A
BMC Bioinformatics; 2016 Jan; 17():19. PubMed ID: 26729364
[TBL] [Abstract][Full Text] [Related]
59. An association study using imputed whole-genome sequence data identifies novel significant loci for growth-related traits in a Duroc × Erhualian F
Ji J; Yan G; Chen D; Xiao S; Gao J; Zhang Z
J Anim Breed Genet; 2019 May; 136(3):217-228. PubMed ID: 30869175
[TBL] [Abstract][Full Text] [Related]
60. Partitioning gene-based variance of complex traits by gene score regression.
Zhang W; Li SY; Liu T; Li Y
PLoS One; 2020; 15(8):e0237657. PubMed ID: 32817676
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
