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10.1016/j.ajhg.2016.08.016 http://scihub22266oqcxt.onion/10.1016/j.ajhg.2016.08.016 C5065685!5065685!27666373     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Am+J+Hum+Genet 2016 ; 99 (4): 877-85 Nephropedia Template TP {{tp|p=27666373|t=2016. REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants |pdf=|usr=}}{{27666373}} gab.com Text REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants JO: Am J Hum Genet http://www.kidney.de/pget.php?&tw=1&pmid=27666373 #FOAvip The vast majority of coding variants are rare, and assessment of the contribution of rare variants to complex traits is hampered by low statistical power and limited functional data. Improved methods for predicting the pathogenicity of rare coding variants are needed to facilitate the discovery of disease variants from exome sequencing studies. We developed REVEL (rare exome variant ensemble learner), an ensemble method for predicting the pathogenicity of missense variants on the basis of individual tools: MutPred, FATHMM, VEST, PolyPhen, SIFT, PROVEAN, MutationAssessor, MutationTaster, LRT, GERP, SiPhy, phyloP, and phastCons. REVEL was trained with recently discovered pathogenic and rare neutral missense variants, excluding those previously used to train its constituent tools. When applied to two independent test sets, REVEL had the best overall performance (p < 10?12) as compared to any individual tool and seven ensemble methods: MetaSVM, MetaLR, KGGSeq, Condel, CADD, DANN, and Eigen. Importantly, REVEL also had the best performance for distinguishing pathogenic from rare neutral variants with allele frequencies <0.5%. The area under the receiver operating characteristic curve (AUC) for REVEL was 0.046?0.182 higher in an independent test set of 935 recent SwissVar disease variants and 123,935 putatively neutral exome sequencing variants and 0.027?0.143 higher in an independent test set of 1,953 pathogenic and 2,406 benign variants recently reported in ClinVar than the AUCs for other ensemble methods. We provide pre-computed REVEL scores for all possible human missense variants to facilitate the identification of pathogenic variants in the sea of rare variants discovered as sequencing studies expand in scale. Twit Text FOAVip REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants ????Am J Hum Genet http://www.kidney.de/pget.php?&tw=1&pmid=27666373 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27666373 #FOAvip English Wikipedia <ref>{{Cite pmid|27666373}}</ref> REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants #MMPMID27666373 Ioannidis N; Rothstein J; Pejaver V; Middha S; McDonnell S; Baheti S; Musolf A; Li Q; Holzinger E; Karyadi D; Cannon-Albright L; Teerlink C; Stanford J; Isaacs W; Xu J; Cooney K; Lange E; Schleutker J; Carpten J; Powell I; Cussenot O; Cancel-Tassin G; Giles G; MacInnis R; Maier C; Hsieh CL; Wiklund F; Catalona W; Foulkes W; Mandal D; Eeles R; Kote-Jarai Z; Bustamante C; Schaid D; Hastie T; Ostrander E; Bailey-Wilson J; Radivojac P; Thibodeau S; Whittemore A; Sieh W Am J Hum Genet 2016[Oct]; 99 (4): 877-85 PMID27666373show ga The vast majority of coding variants are rare, and assessment of the contribution of rare variants to complex traits is hampered by low statistical power and limited functional data. Improved methods for predicting the pathogenicity of rare coding variants are needed to facilitate the discovery of disease variants from exome sequencing studies. We developed REVEL (rare exome variant ensemble learner), an ensemble method for predicting the pathogenicity of missense variants on the basis of individual tools: MutPred, FATHMM, VEST, PolyPhen, SIFT, PROVEAN, MutationAssessor, MutationTaster, LRT, GERP, SiPhy, phyloP, and phastCons. REVEL was trained with recently discovered pathogenic and rare neutral missense variants, excluding those previously used to train its constituent tools. When applied to two independent test sets, REVEL had the best overall performance (p < 10?12) as compared to any individual tool and seven ensemble methods: MetaSVM, MetaLR, KGGSeq, Condel, CADD, DANN, and Eigen. Importantly, REVEL also had the best performance for distinguishing pathogenic from rare neutral variants with allele frequencies <0.5%. The area under the receiver operating characteristic curve (AUC) for REVEL was 0.046?0.182 higher in an independent test set of 935 recent SwissVar disease variants and 123,935 putatively neutral exome sequencing variants and 0.027?0.143 higher in an independent test set of 1,953 pathogenic and 2,406 benign variants recently reported in ClinVar than the AUCs for other ensemble methods. We provide pre-computed REVEL scores for all possible human missense variants to facilitate the identification of pathogenic variants in the sea of rare variants discovered as sequencing studies expand in scale. äREVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Mis(epmc).pdf DeepDyve Pubget Overpricing