375 related articles for article (PubMed ID: 34465180)
21. The phenotype-genotype reference map: Improving biobank data science through replication.
Bastarache L; Delozier S; Pandit A; He J; Lewis A; Annis AC; LeFaive J; Denny JC; Carroll RJ; Altman RB; Hughey JJ; Zawistowski M; Peterson JF
Am J Hum Genet; 2023 Sep; 110(9):1522-1533. PubMed ID: 37607538
[TBL] [Abstract][Full Text] [Related]
22. PheWAS and Beyond: The Landscape of Associations with Medical Diagnoses and Clinical Measures across 38,662 Individuals from Geisinger.
Verma A; Lucas A; Verma SS; Zhang Y; Josyula N; Khan A; Hartzel DN; Lavage DR; Leader J; Ritchie MD; Pendergrass SA
Am J Hum Genet; 2018 Apr; 102(4):592-608. PubMed ID: 29606303
[TBL] [Abstract][Full Text] [Related]
23. High-throughput multimodal automated phenotyping (MAP) with application to PheWAS.
Liao KP; Sun J; Cai TA; Link N; Hong C; Huang J; Huffman JE; Gronsbell J; Zhang Y; Ho YL; Castro V; Gainer V; Murphy SN; O'Donnell CJ; Gaziano JM; Cho K; Szolovits P; Kohane IS; Yu S; Cai T
J Am Med Inform Assoc; 2019 Nov; 26(11):1255-1262. PubMed ID: 31613361
[TBL] [Abstract][Full Text] [Related]
24. Abdominal CT metrics in 17,646 patients reveal associations between myopenia, myosteatosis, and medical phenotypes: a phenome-wide association study.
Zambrano Chaves JM; Lenchik L; Gallegos IO; Blankemeier L; Liang T; Rubin DL; Willis MH; Chaudhari AS; Boutin RD
EBioMedicine; 2024 May; 103():105116. PubMed ID: 38636199
[TBL] [Abstract][Full Text] [Related]
25. Multi-ancestry genome- and phenome-wide association studies of diverticular disease in electronic health records with natural language processing enriched phenotyping algorithm.
Joo YY; Pacheco JA; Thompson WK; Rasmussen-Torvik LJ; Rasmussen LV; Lin FTJ; Andrade M; Borthwick KM; Bottinger E; Cagan A; Carrell DS; Denny JC; Ellis SB; Gottesman O; Linneman JG; Pathak J; Peissig PL; Shang N; Tromp G; Veerappan A; Smith ME; Chisholm RL; Gawron AJ; Hayes MG; Kho AN
PLoS One; 2023; 18(5):e0283553. PubMed ID: 37196047
[TBL] [Abstract][Full Text] [Related]
26. The challenges, advantages and future of phenome-wide association studies.
Hebbring SJ
Immunology; 2014 Feb; 141(2):157-65. PubMed ID: 24147732
[TBL] [Abstract][Full Text] [Related]
27. The use of electronic health records for psychiatric phenotyping and genomics.
Smoller JW
Am J Med Genet B Neuropsychiatr Genet; 2018 Oct; 177(7):601-612. PubMed ID: 28557243
[TBL] [Abstract][Full Text] [Related]
28. Leveraging genomic diversity for discovery in an electronic health record linked biobank: the UCLA ATLAS Community Health Initiative.
Johnson R; Ding Y; Venkateswaran V; Bhattacharya A; Boulier K; Chiu A; Knyazev S; Schwarz T; Freund M; Zhan L; Burch KS; Caggiano C; Hill B; Rakocz N; Balliu B; Denny CT; Sul JH; Zaitlen N; Arboleda VA; Halperin E; Sankararaman S; Butte MJ; ; Lajonchere C; Geschwind DH; Pasaniuc B
Genome Med; 2022 Sep; 14(1):104. PubMed ID: 36085083
[TBL] [Abstract][Full Text] [Related]
29. IDENTIFYING GENETIC ASSOCIATIONS WITH VARIABILITY IN METABOLIC HEALTH AND BLOOD COUNT LABORATORY VALUES: DIVING INTO THE QUANTITATIVE TRAITS BY LEVERAGING LONGITUDINAL DATA FROM AN EHR.
Verma SS; Lucas AM; Lavage DR; Leader JB; Metpally R; Krishnamurthy S; Dewey F; Borecki I; Lopez A; Overton J; Penn J; Reid J; Pendergrass SA; Breitwieser G; Ritchie MD
Pac Symp Biocomput; 2017; 22():533-544. PubMed ID: 27897004
[TBL] [Abstract][Full Text] [Related]
30. Genetically determined serum urate levels and cardiovascular and other diseases in UK Biobank cohort: A phenome-wide mendelian randomization study.
Li X; Meng X; He Y; Spiliopoulou A; Timofeeva M; Wei WQ; Gifford A; Yang T; Varley T; Tzoulaki I; Joshi P; Denny JC; Mckeigue P; Campbell H; Theodoratou E
PLoS Med; 2019 Oct; 16(10):e1002937. PubMed ID: 31626644
[TBL] [Abstract][Full Text] [Related]
31. Phenome-Wide Association Studies as a Tool to Advance Precision Medicine.
Denny JC; Bastarache L; Roden DM
Annu Rev Genomics Hum Genet; 2016 Aug; 17():353-73. PubMed ID: 27147087
[TBL] [Abstract][Full Text] [Related]
32. Comorbidities in Childhood Celiac Disease: A Phenome Wide Association Study Using the Electronic Health Record.
Prinzbach A; Moosavinasab S; Rust S; Boyle B; Barnard JA; Huang Y; Lin S
J Pediatr Gastroenterol Nutr; 2018 Oct; 67(4):488-493. PubMed ID: 29746339
[TBL] [Abstract][Full Text] [Related]
33. Association of Polygenic Risk Scores for Multiple Cancers in a Phenome-wide Study: Results from The Michigan Genomics Initiative.
Fritsche LG; Gruber SB; Wu Z; Schmidt EM; Zawistowski M; Moser SE; Blanc VM; Brummett CM; Kheterpal S; Abecasis GR; Mukherjee B
Am J Hum Genet; 2018 Jun; 102(6):1048-1061. PubMed ID: 29779563
[TBL] [Abstract][Full Text] [Related]
34. Distinguishing vulnerability and resilience to posttraumatic stress disorder evaluating traumatic experiences, genetic risk and electronic health records.
Løkhammer S; Koller D; Wendt FR; Choi KW; He J; Friligkou E; Overstreet C; Gelernter J; Hellard SL; Polimanti R
Psychiatry Res; 2024 Jul; 337():115950. PubMed ID: 38744179
[TBL] [Abstract][Full Text] [Related]
35. PheProb: probabilistic phenotyping using diagnosis codes to improve power for genetic association studies.
Sinnott JA; Cai F; Yu S; Hejblum BP; Hong C; Kohane IS; Liao KP
J Am Med Inform Assoc; 2018 Oct; 25(10):1359-1365. PubMed ID: 29788308
[TBL] [Abstract][Full Text] [Related]
36. Relational machine learning for electronic health record-driven phenotyping.
Peissig PL; Santos Costa V; Caldwell MD; Rottscheit C; Berg RL; Mendonca EA; Page D
J Biomed Inform; 2014 Dec; 52():260-70. PubMed ID: 25048351
[TBL] [Abstract][Full Text] [Related]
37. UK phenomics platform for developing and validating electronic health record phenotypes: CALIBER.
Denaxas S; Gonzalez-Izquierdo A; Direk K; Fitzpatrick NK; Fatemifar G; Banerjee A; Dobson RJB; Howe LJ; Kuan V; Lumbers RT; Pasea L; Patel RS; Shah AD; Hingorani AD; Sudlow C; Hemingway H
J Am Med Inform Assoc; 2019 Dec; 26(12):1545-1559. PubMed ID: 31329239
[TBL] [Abstract][Full Text] [Related]
38. Overcome the Limitation of Phenome-Wide Association Studies (PheWAS): Extension of PheWAS to Efficient and Robust Large-Scale ICD Codes Analysis.
Lin YC; Zhang S; Vessels T; Bastarache L; Bejan CA; Hsie RS; Philips EJ; Ruderfer DM; Pulley JM; Edwards TL; Wells QS; Warner JL; Denny JC; Roden DM; Kang H; Xu Y
medRxiv; 2024 Apr; ():. PubMed ID: 38699370
[TBL] [Abstract][Full Text] [Related]
39. Defining Phenotypes from Clinical Data to Drive Genomic Research.
Robinson JR; Wei WQ; Roden DM; Denny JC
Annu Rev Biomed Data Sci; 2018 Jul; 1():69-92. PubMed ID: 34109303
[TBL] [Abstract][Full Text] [Related]
40. Application of clinical text data for phenome-wide association studies (PheWASs).
Hebbring SJ; Rastegar-Mojarad M; Ye Z; Mayer J; Jacobson C; Lin S
Bioinformatics; 2015 Jun; 31(12):1981-7. PubMed ID: 25657332
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
