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10.1002/humu.23158 http://scihub22266oqcxt.onion/10.1002/humu.23158 C5299048!5299048!27995669     free     free     free Deprecated: Implicit conversion from float 217.6 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\27995669.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Hum+Mutat 2017 ; 38 (3): 243-51 Nephropedia Template TP {{tp|p=27995669|t=2017. PERCH: a unified framework for disease gene prioritization |pdf=|usr=}}{{27995669}} gab.com Text PERCH: a unified framework for disease gene prioritization JO: Hum Mutat http://www.kidney.de/pget.php?&tw=1&pmid=27995669 #FOAvip To interpret genetic variants discovered from next-generation sequencing (NGS), integration of heterogeneous information is vital for success. This paper describes a framework named PERCH (Polymorphism Evaluation, Ranking, and Classification for a Heritable trait), available at http://BJFengLab.org/. It can prioritize disease genes by quantitatively unifying a new deleteriousness measure called BayesDel, an improved assessment of the biological relevance of genes to the disease, a modified linkage analysis, a novel rare-variant association test, and a converted variant call quality score. It supports data that contain a various combination of extended pedigrees, trios, and case-controls, and allows for a reduced penetrance, an elevated phenocopy rate, liability classes and covariates. BayesDel is more accurate than PolyPhen2, SIFT, FATHMM, LRT, Mutation Taster, Mutation Assessor, PhyloP, GERP++, SiPhy, CADD, MetaLR, and MetaSVM. The overall approach is faster and more powerful than the existing quantitative method pVAAST, as shown by the simulations of challenging situations in finding the missing heritability of a complex disease. This framework can also classify variants of unknown significance (VUS, or variants of uncertain significance) by quantitatively integrating allele frequencies, deleteriousness, association, and co-segregation. PERCH is a versatile tool for gene prioritization in gene discovery research and variant classification in clinical genetic testing. Twit Text FOAVip PERCH: a unified framework for disease gene prioritization ????Hum Mutat http://www.kidney.de/pget.php?&tw=1&pmid=27995669 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27995669 #FOAvip English Wikipedia <ref>{{Cite pmid|27995669}}</ref> PERCH: a unified framework for disease gene prioritization #MMPMID27995669 Feng BJ Hum Mutat 2017[Mar]; 38 (3): 243-51 PMID27995669show ga To interpret genetic variants discovered from next-generation sequencing (NGS), integration of heterogeneous information is vital for success. This paper describes a framework named PERCH (Polymorphism Evaluation, Ranking, and Classification for a Heritable trait), available at http://BJFengLab.org/. It can prioritize disease genes by quantitatively unifying a new deleteriousness measure called BayesDel, an improved assessment of the biological relevance of genes to the disease, a modified linkage analysis, a novel rare-variant association test, and a converted variant call quality score. It supports data that contain a various combination of extended pedigrees, trios, and case-controls, and allows for a reduced penetrance, an elevated phenocopy rate, liability classes and covariates. BayesDel is more accurate than PolyPhen2, SIFT, FATHMM, LRT, Mutation Taster, Mutation Assessor, PhyloP, GERP++, SiPhy, CADD, MetaLR, and MetaSVM. The overall approach is faster and more powerful than the existing quantitative method pVAAST, as shown by the simulations of challenging situations in finding the missing heritability of a complex disease. This framework can also classify variants of unknown significance (VUS, or variants of uncertain significance) by quantitatively integrating allele frequencies, deleteriousness, association, and co-segregation. PERCH is a versatile tool for gene prioritization in gene discovery research and variant classification in clinical genetic testing. äPERCH: a unified framework for disease gene prioritization (epmc).pdf DeepDyve Pubget Overpricing