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 *

204 related articles for article (PubMed ID: 32912253)

  • 1. PTWAS: investigating tissue-relevant causal molecular mechanisms of complex traits using probabilistic TWAS analysis.
    Zhang Y; Quick C; Yu K; Barbeira A; ; Luca F; Pique-Regi R; Kyung Im H; Wen X
    Genome Biol; 2020 Sep; 21(1):232. PubMed ID: 32912253
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. 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]  

  • 4. Influence of tissue context on gene prioritization for predicted transcriptome-wide association studies.
    Li B; Veturi Y; Bradford Y; Verma SS; Verma A; Lucas AM; Haas DW; Ritchie MD
    Pac Symp Biocomput; 2019; 24():296-307. PubMed ID: 30864331
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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]  

  • 6. Some statistical consideration in transcriptome-wide association studies.
    Xue H; Pan W;
    Genet Epidemiol; 2020 Apr; 44(3):221-232. PubMed ID: 31821608
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Probabilistic integration of transcriptome-wide association studies and colocalization analysis identifies key molecular pathways of complex traits.
    Okamoto J; Wang L; Yin X; Luca F; Pique-Regi R; Helms A; Im HK; Morrison J; Wen X
    Am J Hum Genet; 2023 Jan; 110(1):44-57. PubMed ID: 36608684
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Integrating transcriptome-wide association study and copy number variation study identifies candidate genes and pathways for diffuse non-Hodgkin's lymphoma.
    Wu D; Zhao J; Ma H; Wang MC
    Cancer Genet; 2020 May; 243():7-10. PubMed ID: 32179489
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Transcriptome-wide association study reveals candidate causal genes for lung cancer.
    Bossé Y; Li Z; Xia J; Manem V; Carreras-Torres R; Gabriel A; Gaudreault N; Albanes D; Aldrich MC; Andrew A; Arnold S; Bickeböller H; Bojesen SE; Brennan P; Brunnstrom H; Caporaso N; Chen C; Christiani DC; Field JK; Goodman G; Grankvist K; Houlston R; Johansson M; Johansson M; Kiemeney LA; Lam S; Landi MT; Lazarus P; Le Marchand L; Liu G; Melander O; Rennert G; Risch A; Rosenberg SM; Schabath MB; Shete S; Song Z; Stevens VL; Tardon A; Wichmann HE; Woll P; Zienolddiny S; Obeidat M; Timens W; Hung RJ; Joubert P; Amos CI; McKay JD
    Int J Cancer; 2020 Apr; 146(7):1862-1878. PubMed ID: 31696517
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A powerful and versatile colocalization test.
    Deng Y; Pan W
    PLoS Comput Biol; 2020 Apr; 16(4):e1007778. PubMed ID: 32275709
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Integrative analysis of transcriptome-wide association study data and mRNA expression profiles identified candidate genes and pathways associated with atrial fibrillation.
    Zhang L; Liu L; Ma M; Cheng S; Cheng B; Li P; Wen Y; Du Y; Liang X; Zhao Y; Ding M; Xin Q; Liang C; Huang H; Zhang F
    Heart Vessels; 2019 Nov; 34(11):1882-1888. PubMed ID: 31065785
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Integrative analysis of transcriptome-wide association study and mRNA expression profiles identifies candidate genes associated with autism spectrum disorders.
    Huang H; Cheng S; Ding M; Wen Y; Ma M; Zhang L; Li P; Cheng B; Liang X; Liu L; Du Y; Zhao Y; Kafle OP; Han B; Zhang F
    Autism Res; 2019 Jan; 12(1):33-38. PubMed ID: 30561910
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. Meta-imputation of transcriptome from genotypes across multiple datasets by leveraging publicly available summary-level data.
    Liu AE; Kang HM
    PLoS Genet; 2022 Jan; 18(1):e1009571. PubMed ID: 35100255
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Transcriptome-wide association study and eQTL colocalization identify potentially causal genes responsible for human bone mineral density GWAS associations.
    Al-Barghouthi BM; Rosenow WT; Du KP; Heo J; Maynard R; Mesner L; Calabrese G; Nakasone A; Senwar B; Gerstenfeld L; Larner J; Ferguson V; Ackert-Bicknell C; Morgan E; Brautigan D; Farber CR
    Elife; 2022 Nov; 11():. PubMed ID: 36416764
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Integrative analysis of transcriptome-wide association study and mRNA expression profile identified risk genes for bipolar disorder.
    Yang R; Wang R; Zhao D; Lian K; Shang B; Dong L; Yang X; Dang X; Sun D; Cheng Y
    Neurosci Lett; 2024 Sep; 839():137935. PubMed ID: 39151574
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Identifying Candidate Genes Associated with Sporadic Amyotrophic Lateral Sclerosis via Integrative Analysis of Transcriptome-Wide Association Study and Messenger RNA Expression Profile.
    Li P; Cheng S; Wen Y; Cheng B; Liu L; Wu X; Ao X; Huang Z; Liao C; Li S; Zhang F; Zhang Z
    Cell Mol Neurobiol; 2023 Jan; 43(1):327-338. PubMed ID: 35038056
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Bayesian genome-wide TWAS with reference transcriptomic data of brain and blood tissues identified 93 risk genes for Alzheimer's disease dementia.
    Guo S; Yang J
    medRxiv; 2023 Jul; ():. PubMed ID: 37503151
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Integrating eQTL and GWAS data characterises established and identifies novel migraine risk loci.
    Ghaffar A; ; Nyholt DR
    Hum Genet; 2023 Aug; 142(8):1113-1137. PubMed ID: 37245199
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A robust two-sample transcriptome-wide Mendelian randomization method integrating GWAS with multi-tissue eQTL summary statistics.
    Gleason KJ; Yang F; Chen LS
    Genet Epidemiol; 2021 Jun; 45(4):353-371. PubMed ID: 33834509
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.