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10.1146/annurev-genom-090314-024956 http://scihub22266oqcxt.onion/10.1146/annurev-genom-090314-024956 C5480096!5480096!27147087     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Annu+Rev+Genomics+Hum+Genet 2016 ; 17 (ä): 353-73 Nephropedia Template TP {{tp|p=27147087|t=2016. Phenome-Wide Association Studies as a Tool to Advance Precision Medicine |pdf=|usr=}}{{27147087}} gab.com Text Phenome-Wide Association Studies as a Tool to Advance Precision Medicine JO: Annu Rev Genomics Hum Genet http://www.kidney.de/pget.php?&tw=1&pmid=27147087 #FOAvip Beginning in the early 2000s, the accumulation of biospecimens linked to electronic health records (EHRs) made possible genome-phenome studies (i.e., comparative analyses of genetic variants and phenotypes) using only data collected as a by-product of typical health care. In addition to disease and trait genetics, EHRs proved a valuable resource for analyzing pharmacogenetic traits and developing reverse genetics approaches such as phenome-wide association studies (PheWASs). PheWASs are designed to survey which of many phenotypes may be associated with a given genetic variant. PheWAS methods have been validated through replication of hundreds of known genotype-phenotype associations, and their use has differentiated between true pleiotropy and clinical comorbidity, added context to genetic discoveries, and helped define disease subtypes, and may also help repurpose medications. PheWAS methods have also proven to be useful with research-collected data. Future efforts that integrate broad, robust collection of phenotype data (e.g., EHR data) with purpose-collected research data in combination with a greater understanding of EHR data will create a rich resource for increasingly more efficient and detailed genome-phenome analysis to usher in new discoveries in precision medicine. Twit Text FOAVip Phenome-Wide Association Studies as a Tool to Advance Precision Medicine ????Annu Rev Genomics Hum Genet http://www.kidney.de/pget.php?&tw=1&pmid=27147087 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27147087 #FOAvip English Wikipedia <ref>{{Cite pmid|27147087}}</ref> Phenome-Wide Association Studies as a Tool to Advance Precision Medicine #MMPMID27147087 Denny JC; Bastarache L; Roden DM Annu Rev Genomics Hum Genet 2016[Aug]; 17 (ä): 353-73 PMID27147087show ga Beginning in the early 2000s, the accumulation of biospecimens linked to electronic health records (EHRs) made possible genome-phenome studies (i.e., comparative analyses of genetic variants and phenotypes) using only data collected as a by-product of typical health care. In addition to disease and trait genetics, EHRs proved a valuable resource for analyzing pharmacogenetic traits and developing reverse genetics approaches such as phenome-wide association studies (PheWASs). PheWASs are designed to survey which of many phenotypes may be associated with a given genetic variant. PheWAS methods have been validated through replication of hundreds of known genotype-phenotype associations, and their use has differentiated between true pleiotropy and clinical comorbidity, added context to genetic discoveries, and helped define disease subtypes, and may also help repurpose medications. PheWAS methods have also proven to be useful with research-collected data. Future efforts that integrate broad, robust collection of phenotype data (e.g., EHR data) with purpose-collected research data in combination with a greater understanding of EHR data will create a rich resource for increasingly more efficient and detailed genome-phenome analysis to usher in new discoveries in precision medicine. äPhenome-Wide Association Studies as a Tool to Advance Precision Medici(epmc).pdf DeepDyve Pubget Overpricing