595 related articles for article (PubMed ID: 29411426)
1. Integrating eQTL data with GWAS summary statistics in pathway-based analysis with application to schizophrenia.
Wu C; Pan W
Genet Epidemiol; 2018 Apr; 42(3):303-316. PubMed ID: 29411426
[TBL] [Abstract][Full Text] [Related]
2. A fast and powerful eQTL weighted method to detect genes associated with complex trait using GWAS summary data.
Zhang J; Xie S; Gonzales S; Liu J; Wang X
Genet Epidemiol; 2020 Sep; 44(6):550-563. PubMed ID: 32350919
[TBL] [Abstract][Full Text] [Related]
3. How powerful are summary-based methods for identifying expression-trait associations under different genetic architectures?
Veturi Y; Ritchie MD
Pac Symp Biocomput; 2018; 23():228-239. PubMed ID: 29218884
[TBL] [Abstract][Full Text] [Related]
4. Integration of Enhancer-Promoter Interactions with GWAS Summary Results Identifies Novel Schizophrenia-Associated Genes and Pathways.
Wu C; Pan W
Genetics; 2018 Jul; 209(3):699-709. PubMed ID: 29728367
[TBL] [Abstract][Full Text] [Related]
5. Bayesian genome-wide TWAS with reference transcriptomic data of brain and blood tissues identified 141 risk genes for Alzheimer's disease dementia.
Guo S; Yang J
Alzheimers Res Ther; 2024 Jun; 16(1):120. PubMed ID: 38824563
[TBL] [Abstract][Full Text] [Related]
6. A Powerful Framework for Integrating eQTL and GWAS Summary Data.
Xu Z; Wu C; Wei P; Pan W
Genetics; 2017 Nov; 207(3):893-902. PubMed ID: 28893853
[TBL] [Abstract][Full Text] [Related]
7. Statistical power of transcriptome-wide association studies.
He R; Xue H; Pan W;
Genet Epidemiol; 2022 Dec; 46(8):572-588. PubMed ID: 35766062
[TBL] [Abstract][Full Text] [Related]
8. Leveraging expression from multiple tissues using sparse canonical correlation analysis and aggregate tests improves the power of transcriptome-wide association studies.
Feng H; Mancuso N; Gusev A; Majumdar A; Major M; Pasaniuc B; Kraft P
PLoS Genet; 2021 Apr; 17(4):e1008973. PubMed ID: 33831007
[TBL] [Abstract][Full Text] [Related]
9. Gene-based association tests using GWAS summary statistics and incorporating eQTL.
Cao X; Wang X; Zhang S; Sha Q
Sci Rep; 2022 Mar; 12(1):3553. PubMed ID: 35241742
[TBL] [Abstract][Full Text] [Related]
10. Bayesian Genome-wide TWAS Method to Leverage both cis- and trans-eQTL Information through Summary Statistics.
Luningham JM; Chen J; Tang S; De Jager PL; Bennett DA; Buchman AS; Yang J
Am J Hum Genet; 2020 Oct; 107(4):714-726. PubMed ID: 32961112
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. Subset-based method for cross-tissue transcriptome-wide association studies improves power and interpretability.
Guo X; Chatterjee N; Dutta D
HGG Adv; 2024 Apr; 5(2):100283. PubMed ID: 38491773
[TBL] [Abstract][Full Text] [Related]
13. Genome-wide association study followed by trans-ancestry meta-analysis identify 17 new risk loci for schizophrenia.
Liu J; Li S; Li X; Li W; Yang Y; Guo S; Lv L; Xiao X; Yao YG; Guan F; Li M; Luo XJ
BMC Med; 2021 Aug; 19(1):177. PubMed ID: 34380480
[TBL] [Abstract][Full Text] [Related]
14. iFunMed: Integrative functional mediation analysis of GWAS and eQTL studies.
Rojo C; Zhang Q; Keleş S
Genet Epidemiol; 2019 Oct; 43(7):742-760. PubMed ID: 31328826
[TBL] [Abstract][Full Text] [Related]
15. nMAGMA: a network-enhanced method for inferring risk genes from GWAS summary statistics and its application to schizophrenia.
Yang A; Chen J; Zhao XM
Brief Bioinform; 2021 Jul; 22(4):. PubMed ID: 33230537
[TBL] [Abstract][Full Text] [Related]
16. Novel Variance-Component TWAS method for studying complex human diseases with applications to Alzheimer's dementia.
Tang S; Buchman AS; De Jager PL; Bennett DA; Epstein MP; Yang J
PLoS Genet; 2021 Apr; 17(4):e1009482. PubMed ID: 33798195
[TBL] [Abstract][Full Text] [Related]
17. SUMMIT-FA: a new resource for improved transcriptome imputation using functional annotations.
Melton HJ; Zhang Z; Wu C
Hum Mol Genet; 2024 Mar; 33(7):624-635. PubMed ID: 38129112
[TBL] [Abstract][Full Text] [Related]
18. Endometrial vezatin and its association with endometriosis risk.
Holdsworth-Carson SJ; Fung JN; Luong HT; Sapkota Y; Bowdler LM; Wallace L; Teh WT; Powell JE; Girling JE; Healey M; Montgomery GW; Rogers PA
Hum Reprod; 2016 May; 31(5):999-1013. PubMed ID: 27005890
[TBL] [Abstract][Full Text] [Related]
19. 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]
20. Leveraging existing GWAS summary data of genetically correlated and uncorrelated traits to improve power for a new GWAS.
Xue H; Wu C; Pan W
Genet Epidemiol; 2020 Oct; 44(7):717-732. PubMed ID: 32677173
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]