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Items: 1 to 20 of 109

1.

PheWAS: demonstrating the feasibility of a phenome-wide scan to discover gene-disease associations.

Denny JC, Ritchie MD, Basford MA, Pulley JM, Bastarache L, Brown-Gentry K, Wang D, Masys DR, Roden DM, Crawford DC.

Bioinformatics. 2010 May 1;26(9):1205-10. doi: 10.1093/bioinformatics/btq126. Epub 2010 Mar 24.

2.

Robust replication of genotype-phenotype associations across multiple diseases in an electronic medical record.

Ritchie MD, Denny JC, Crawford DC, Ramirez AH, Weiner JB, Pulley JM, Basford MA, Brown-Gentry K, Balser JR, Masys DR, Haines JL, Roden DM.

Am J Hum Genet. 2010 Apr 9;86(4):560-72. doi: 10.1016/j.ajhg.2010.03.003. Epub 2010 Apr 1. Erratum in: Am J Hum Genet. 2010 Aug 13;87(2):310.

3.

Phenome-wide association study (PheWAS) in EMR-linked pediatric cohorts, genetically links PLCL1 to speech language development and IL5-IL13 to Eosinophilic Esophagitis.

Namjou B, Marsolo K, Caroll RJ, Denny JC, Ritchie MD, Verma SS, Lingren T, Porollo A, Cobb BL, Perry C, Kottyan LC, Rothenberg ME, Thompson SD, Holm IA, Kohane IS, Harley JB.

Front Genet. 2014 Nov 18;5:401. doi: 10.3389/fgene.2014.00401. eCollection 2014.

4.

Phenome-wide association study (PheWAS) for detection of pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network.

Pendergrass SA, Brown-Gentry K, Dudek S, Frase A, Torstenson ES, Goodloe R, Ambite JL, Avery CL, Buyske S, Bůžková P, Deelman E, Fesinmeyer MD, Haiman CA, Heiss G, Hindorff LA, Hsu CN, Jackson RD, Kooperberg C, Le Marchand L, Lin Y, Matise TC, Monroe KR, Moreland L, Park SL, Reiner A, Wallace R, Wilkens LR, Crawford DC, Ritchie MD.

PLoS Genet. 2013;9(1):e1003087. doi: 10.1371/journal.pgen.1003087. Epub 2013 Jan 31.

5.

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 15;31(12):1981-7. doi: 10.1093/bioinformatics/btv076. Epub 2015 Feb 4.

6.

INTEGRATING CLINICAL LABORATORY MEASURES AND ICD-9 CODE DIAGNOSES IN PHENOME-WIDE ASSOCIATION STUDIES.

Verma A, Leader JB, Verma SS, Frase A, Wallace J, Dudek S, Lavage DR, Van Hout CV, Dewey FE, Penn J, Lopez A, Overton JD, Carey DJ, Ledbetter DH, Kirchner HL, Ritchie MD, Pendergrass SA.

Pac Symp Biocomput. 2016;21:168-79.

7.

Variants near FOXE1 are associated with hypothyroidism and other thyroid conditions: using electronic medical records for genome- and phenome-wide studies.

Denny JC, Crawford DC, Ritchie MD, Bielinski SJ, Basford MA, Bradford Y, Chai HS, Bastarache L, Zuvich R, Peissig P, Carrell D, Ramirez AH, Pathak J, Wilke RA, Rasmussen L, Wang X, Pacheco JA, Kho AN, Hayes MG, Weston N, Matsumoto M, Kopp PA, Newton KM, Jarvik GP, Li R, Manolio TA, Kullo IJ, Chute CG, Chisholm RL, Larson EB, McCarty CA, Masys DR, Roden DM, de Andrade M.

Am J Hum Genet. 2011 Oct 7;89(4):529-42. doi: 10.1016/j.ajhg.2011.09.008.

8.

Visual integration of results from a large DNA biobank (BioVU) using synthesis-view.

Pendergrass S, Dudek SM, Roden DM, Crawford DC, Ritchie MD.

Pac Symp Biocomput. 2011:265-75.

9.

Evaluating phecodes, clinical classification software, and ICD-9-CM codes for phenome-wide association studies in the electronic health record.

Wei WQ, Bastarache LA, Carroll RJ, Marlo JE, Osterman TJ, Gamazon ER, Cox NJ, Roden DM, Denny JC.

PLoS One. 2017 Jul 7;12(7):e0175508. doi: 10.1371/journal.pone.0175508. eCollection 2017.

10.

Phenome-Wide Association Study of Autoantibodies to Citrullinated and Noncitrullinated Epitopes in Rheumatoid Arthritis.

Liao KP, Sparks JA, Hejblum BP, Kuo IH, Cui J, Lahey LJ, Cagan A, Gainer VS, Liu W, Cai TT, Sokolove J, Cai T.

Arthritis Rheumatol. 2017 Apr;69(4):742-749. doi: 10.1002/art.39974.

11.

R PheWAS: data analysis and plotting tools for phenome-wide association studies in the R environment.

Carroll RJ, Bastarache L, Denny JC.

Bioinformatics. 2014 Aug 15;30(16):2375-6. doi: 10.1093/bioinformatics/btu197. Epub 2014 Apr 14.

12.

Detection of pleiotropy through a Phenome-wide association study (PheWAS) of epidemiologic data as part of the Environmental Architecture for Genes Linked to Environment (EAGLE) study.

Hall MA, Verma A, Brown-Gentry KD, Goodloe R, Boston J, Wilson S, McClellan B, Sutcliffe C, Dilks HH, Gillani NB, Jin H, Mayo P, Allen M, Schnetz-Boutaud N, Crawford DC, Ritchie MD, Pendergrass SA.

PLoS Genet. 2014 Dec 4;10(12):e1004678. doi: 10.1371/journal.pgen.1004678. eCollection 2014 Dec.

13.

Associations of autoantibodies, autoimmune risk alleles, and clinical diagnoses from the electronic medical records in rheumatoid arthritis cases and non-rheumatoid arthritis controls.

Liao KP, Kurreeman F, Li G, Duclos G, Murphy S, Guzman R, Cai T, Gupta N, Gainer V, Schur P, Cui J, Denny JC, Szolovits P, Churchill S, Kohane I, Karlson EW, Plenge RM.

Arthritis Rheum. 2013 Mar;65(3):571-81. doi: 10.1002/art.37801.

14.

Investigating the relationship between mitochondrial genetic variation and cardiovascular-related traits to develop a framework for mitochondrial phenome-wide association studies.

Mitchell SL, Hall JB, Goodloe RJ, Boston J, Farber-Eger E, Pendergrass SA, Bush WS, Crawford DC.

BioData Min. 2014 Apr 15;7:6. doi: 10.1186/1756-0381-7-6. eCollection 2014.

15.

Visually integrating and exploring high throughput Phenome-Wide Association Study (PheWAS) results using PheWAS-View.

Pendergrass SA, Dudek SM, Crawford DC, Ritchie MD.

BioData Min. 2012 Jun 8;5(1):5. doi: 10.1186/1756-0381-5-5.

16.

Phenome-Wide Association Study to Explore Relationships between Immune System Related Genetic Loci and Complex Traits and Diseases.

Verma A, Basile AO, Bradford Y, Kuivaniemi H, Tromp G, Carey D, Gerhard GS, Crowe JE Jr, Ritchie MD, Pendergrass SA.

PLoS One. 2016 Aug 10;11(8):e0160573. doi: 10.1371/journal.pone.0160573. eCollection 2016.

17.

The use of phenome-wide association studies (PheWAS) for exploration of novel genotype-phenotype relationships and pleiotropy discovery.

Pendergrass SA, Brown-Gentry K, Dudek SM, Torstenson ES, Ambite JL, Avery CL, Buyske S, Cai C, Fesinmeyer MD, Haiman C, Heiss G, Hindorff LA, Hsu CN, Jackson RD, Kooperberg C, Le Marchand L, Lin Y, Matise TC, Moreland L, Monroe K, Reiner AP, Wallace R, Wilkens LR, Crawford DC, Ritchie MD.

Genet Epidemiol. 2011 Jul;35(5):410-22. doi: 10.1002/gepi.20589. Epub 2011 May 18.

18.

The challenges, advantages and future of phenome-wide association studies.

Hebbring SJ.

Immunology. 2014 Feb;141(2):157-65. doi: 10.1111/imm.12195. Review.

19.

eMERGE Phenome-Wide Association Study (PheWAS) identifies clinical associations and pleiotropy for stop-gain variants.

Verma A, Verma SS, Pendergrass SA, Crawford DC, Crosslin DR, Kuivaniemi H, Bush WS, Bradford Y, Kullo I, Bielinski SJ, Li R, Denny JC, Peissig P, Hebbring S, De Andrade M, Ritchie MD, Tromp G.

BMC Med Genomics. 2016 Aug 12;9 Suppl 1:32. doi: 10.1186/s12920-016-0191-8.

20.

Phenome-wide association studies (PheWASs) for functional variants.

Ye Z, Mayer J, Ivacic L, Zhou Z, He M, Schrodi SJ, Page D, Brilliant MH, Hebbring SJ.

Eur J Hum Genet. 2015 Apr;23(4):523-9. doi: 10.1038/ejhg.2014.123. Epub 2014 Jul 30.

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