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10.1371/journal.pgen.1005496 http://scihub22266oqcxt.onion/10.1371/journal.pgen.1005496 C4598191!4598191!26448358     free     free     free Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\26448358.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       PLoS+Genet 2015 ; 11 (10): ä Nephropedia Template TP {{tp|p=26448358|t=2015. Sequence to Medical Phenotypes: A Framework for Interpretation of Human Whole Genome DNA Sequence Data |pdf=|usr=}}{{26448358}} gab.com Text Sequence to Medical Phenotypes: A Framework for Interpretation of Human Whole Genome DNA Sequence Data JO: PLoS Genet http://www.kidney.de/pget.php?&tw=1&pmid=26448358 #FOAvip High throughput sequencing has facilitated a precipitous drop in the cost of genomic sequencing, prompting predictions of a revolution in medicine via genetic personalization of diagnostic and therapeutic strategies. There are significant barriers to realizing this goal that are related to the difficult task of interpreting personal genetic variation. A comprehensive, widely accessible application for interpretation of whole genome sequence data is needed. Here, we present a series of methods for identification of genetic variants and genotypes with clinical associations, phasing genetic data and using Mendelian inheritance for quality control, and providing predictive genetic information about risk for rare disease phenotypes and response to pharmacological therapy in single individuals and father-mother-child trios. We demonstrate application of these methods for disease and drug response prognostication in whole genome sequence data from twelve unrelated adults, and for disease gene discovery in one father-mother-child trio with apparently simplex congenital ventricular arrhythmia. In doing so we identify clinically actionable inherited disease risk and drug response genotypes in pre-symptomatic individuals. We also nominate a new candidate gene in congenital arrhythmia, ATP2B4, and provide experimental evidence of a regulatory role for variants discovered using this framework. Twit Text FOAVip Sequence to Medical Phenotypes: A Framework for Interpretation of Human Whole Genome DNA Sequence Data ????PLoS Genet http://www.kidney.de/pget.php?&tw=1&pmid=26448358 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26448358 #FOAvip English Wikipedia <ref>{{Cite pmid|26448358}}</ref> Sequence to Medical Phenotypes: A Framework for Interpretation of Human Whole Genome DNA Sequence Data #MMPMID26448358 Dewey FE; Grove ME; Priest JR; Waggott D; Batra P; Miller CL; Wheeler M; Zia A; Pan C; Karzcewski KJ; Miyake C; Whirl-Carrillo M; Klein TE; Datta S; Altman RB; Snyder M; Quertermous T; Ashley EA PLoS Genet 2015[Oct]; 11 (10): ä PMID26448358show ga High throughput sequencing has facilitated a precipitous drop in the cost of genomic sequencing, prompting predictions of a revolution in medicine via genetic personalization of diagnostic and therapeutic strategies. There are significant barriers to realizing this goal that are related to the difficult task of interpreting personal genetic variation. A comprehensive, widely accessible application for interpretation of whole genome sequence data is needed. Here, we present a series of methods for identification of genetic variants and genotypes with clinical associations, phasing genetic data and using Mendelian inheritance for quality control, and providing predictive genetic information about risk for rare disease phenotypes and response to pharmacological therapy in single individuals and father-mother-child trios. We demonstrate application of these methods for disease and drug response prognostication in whole genome sequence data from twelve unrelated adults, and for disease gene discovery in one father-mother-child trio with apparently simplex congenital ventricular arrhythmia. In doing so we identify clinically actionable inherited disease risk and drug response genotypes in pre-symptomatic individuals. We also nominate a new candidate gene in congenital arrhythmia, ATP2B4, and provide experimental evidence of a regulatory role for variants discovered using this framework. äSequence to Medical Phenotypes: A Framework for Interpretation of Huma(epmc).pdf DeepDyve Pubget Overpricing