Predicting the functional, molecular, and phenotypic consequences of amino acid substitutions using hidden Markov models.
Hashem A. Shihab,Julian Gough,David Neil Cooper,Peter D. Stenson,Gary L A Barker,Keith J. Edwards,Ian N. M. Day,Tom R. Gaunt +7 more
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TLDR
The Functional Analysis Through Hidden Markov Models (FATHMM) software and server is described: a species‐independent method with optional species‐specific weightings for the prediction of the functional effects of protein missense variants, demonstrating that FATHMM can be efficiently applied to high‐throughput/large‐scale human and nonhuman genome sequencing projects with the added benefit of phenotypic outcome associations.Abstract:
The rate at which nonsynonymous single nucleotide polymorphisms (nsSNPs) are being identified in the human genome is increasing dramatically owing to advances in whole-genome/whole-exome sequencing technologies. Automated methods capable of accurately and reliably distinguishing between pathogenic and functionally neutral nsSNPs are therefore assuming ever-increasing importance. Here, we describe the Functional Analysis Through Hidden Markov Models (FATHMM) software and server: a species-independent method with optional species-specific weightings for the prediction of the functional effects of protein missense variants. Using a model weighted for human mutations, we obtained performance accuracies that outperformed traditional prediction methods (i.e., SIFT, PolyPhen, and PANTHER) on two separate benchmarks. Furthermore, in one benchmark, we achieve performance accuracies that outperform current state-of-the-art prediction methods (i.e., SNPs&GO and MutPred). We demonstrate that FATHMM can be efficiently applied to high-throughput/large-scale human and nonhuman genome sequencing projects with the added benefit of phenotypic outcome associations. To illustrate this, we evaluated nsSNPs in wheat (Triticum spp.) to identify some of the important genetic variants responsible for the phenotypic differences introduced by intense selection during domestication. A Web-based implementation of FATHMM, including a high-throughput batch facility and a downloadable standalone package, is available at http://fathmm.biocompute.org.uk.read more
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Detection of variants in dystroglycanopathy-associated genes through the application of targeted whole-exome sequencing analysis to a large cohort of patients with unexplained limb-girdle muscle weakness.
Katherine Johnson,Marta Bertoli,Marta Bertoli,L. Phillips,Ana Töpf,Peter Van den Bergh,John Vissing,Nanna Witting,Shahriar Nafissi,Shirin Jamal-Omidi,Anna Łusakowska,Anna Kostera-Pruszczyk,Anna Potulska-Chromik,Nicolas Deconinck,Carina Wallgren-Pettersson,Sonja Strang-Karlsson,Jaume Colomer,Kristl G. Claeys,Kristl G. Claeys,Willem De Ridder,Jonathan Baets,Maja von der Hagen,Roberto Fernández-Torrón,Miren Zulaica Ijurco,Juan Bautista Espinal Valencia,Andreas Hahn,Hacer Durmus,Tracey Willis,L. Xu,L. Xu,Elise Valkanas,Elise Valkanas,Thomas E. Mullen,Thomas E. Mullen,Monkol Lek,Monkol Lek,Daniel G. MacArthur,Daniel G. MacArthur,Volker Straub,Volker Straub +39 more
TL;DR: Evidence is presented for the genetic and phenotypic diversity of the dystroglycanopathies as a disease group, while also highlighting the advantage of incorporating next-generation sequencing into the diagnostic pathway of rare diseases.
Journal ArticleDOI
IMPACT: a whole-exome sequencing analysis pipeline for integrating molecular profiles with actionable therapeutics in clinical samples.
Jennifer D. Hintzsche,Jihye Kim,Vinod Kumar Yadav,Carol M. Amato,Steven E. Robinson,Eric Seelenfreund,Yiqun G. Shellman,Joshua Wisell,Allison Applegate,Martin D. McCarter,Neil F. Box,John J. Tentler,Subhajyoti De,Subhajyoti De,William A. Robinson,Aik Choon Tan,Aik Choon Tan +16 more
TL;DR: IMPACT provides a new bioinformatics strategy to delineate candidate somatic variants and actionable therapies and can be applied to other patient tumor samples to discover effective drug targets for personalized medicine.
Journal ArticleDOI
Evaluation of computational techniques for predicting non-synonymous single nucleotide variants pathogenicity.
Marwa S. Hassan,A. A. Shaalan,Moawad I. Dessouky,Abdelaziz Elsaid Abdelnaiem,Mahmoud ElHefnawi +4 more
TL;DR: FATHMM gives the highest performance over the seven individual techniques, where it achieves 83.75% and 77.78% ACC on whole and random sample dataset, respectively, and the launched Meta classifier (CSTJ48) is outperforming over all the eight individual tools that compared here.
Journal ArticleDOI
Mismatch repair deficiency in high-grade meningioma: a rare but recurrent event associated with dramatic immune activation and clinical response to PD-1 blockade.
Ian F. Dunn,Ziming Du,Ziming Du,Mehdi Touat,Michael B. Sisti,Patrick Y. Wen,Patrick Y. Wen,Renato Umeton,Adrian M. Dubuc,Matthew D. Ducar,Peter Canoll,Eric Allan Severson,Julia A. Elvin,Shakti H. Ramkissoon,Shakti H. Ramkissoon,Jia-Ren Lin,Lais Cabrera,Brenda Acevedo,Peter K. Sorger,Keith L. Ligon,Keith L. Ligon,Sandro Santagata,David A. Reardon +22 more
TL;DR: A patient with an atypical meningioma that was not controlled by repeated surgery and radiation but which was highly response to nivolumab is reported here, initiating a phase II study of nivorumab, a humanized IgG4 PD-1 blocking monoclonal antibody, in patients with higher-grade mening iomas that recurred following surgery and radiotherapy.
Journal ArticleDOI
Role of E542 and E545 missense mutations of PIK3CA in breast cancer: a comparative computational approach.
TL;DR: A large number of mutations observed in PIK3CA have the ability to trigger the different activities of the cell, thereby bypassing the regular cellular cycle and the deleterious effect of these mutations is compared in silico prediction tools.
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