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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Exome-Wide Association Study on Alanine Aminotransferase Identifies Sequence Variants in the GPAM and APOE Associated With Fatty Liver Disease
Oveis Jamialahmadi,Rosellina Margherita Mancina,Ester Ciociola,Federica Tavaglione,Federica Tavaglione,Panu K. Luukkonen,Panu K. Luukkonen,Panu K. Luukkonen,Guido Baselli,Francesco Malvestiti,Dorothée Thuillier,Violeta Raverdy,Ville Männistö,Rosaria Maria Pipitone,Grazia Pennisi,Daniele Prati,Rocco Spagnuolo,Salvatore Petta,Jussi Pihlajamäki,François Pattou,Hannele Yki-Järvinen,Hannele Yki-Järvinen,Luca Valenti,Stefano Romeo,Stefano Romeo,Stefano Romeo +25 more
TL;DR: Two novel genetic variants in GPAM and APOE that are robustly associated with steatosis and liver damage are identified that may help to better elucidate the genetic susceptibility to FLD onset and progression.
Journal ArticleDOI
De novo mutations in hereditary diffuse leukoencephalopathy with axonal spheroids (HDLS)
Kathrin N. Karle,Saskia Biskup,Rebecca Schüle,Katherine Schweitzer,Rejko Krüger,Peter Bauer,Benjamin Bender,Thomas Nägele,Ludger Schöls +8 more
TL;DR: Typical clinical phenotype and early brain MRI alterations can help to guide the diagnosis of HDLS, and de novo mutations in one-third of patients with CSF1R mutations should be considered even in the absence of a family history.
Journal ArticleDOI
Functional analysis reveals that RBM10 mutations contribute to lung adenocarcinoma pathogenesis by deregulating splicing
Jiawei Zhao,Yue Sun,Yin Huang,Fan Song,Zengshu Huang,Yufang Bao,Ji Zuo,David Saffen,Zhen Shao,Wen Liu,Yongbo Wang +10 more
TL;DR: Integrative analysis of RBM10 mutation and RNA expression data revealed that LUAD-associated R BM10 mutations exhibit a mutational spectrum similar to that of tumor suppressor genes, implying that RBM 10 mutations contribute to LUAD pathogenesis, at least in large part, by deregulating splicing.
Journal ArticleDOI
Germline mutations in MAP3K6 are associated with familial gastric cancer
Daniel Gaston,Samantha Hansford,Carla Oliveira,Mathew Nightingale,Hugo Pinheiro,Christine Macgillivray,Pardeep Kaurah,Andrea L. Rideout,Patricia Steele,Gabriela Soares,Weei-Yuarn Huang,Scott Whitehouse,Sarah Blowers,Marissa A. LeBlanc,Haiyan Jiang,Wenda L. Greer,Mark E. Samuels,Andrew C. Orr,Conrad V. Fernandez,Jacek Majewski,Mark Ludman,Sarah Dyack,Lynette S. Penney,Christopher R. McMaster,David G. Huntsman,Karen Bedard +25 more
TL;DR: Findings from a large family from Maritime Canada with FGC without CDH1 mutations, and studies showing the presence of somatic mutations in MAP3K6 in non-hereditary gastric cancers and gastric cancer cell lines, point towards MAP3k6 variants as a predisposing factor for FGC.
Journal ArticleDOI
OncoVar: an integrated database and analysis platform for oncogenic driver variants in cancers.
Tao Wang,Tao Wang,Shasha Ruan,Xiaolu Zhao,Xiaohui Shi,Huajing Teng,Jianing Zhong,Mingcong You,Kun Xia,Kun Xia,Zhong Sheng Sun,Fengbiao Mao +11 more
TL;DR: A useful platform, OncoVar, which employed published bioinformatics algorithms and incorporated known driver events to identify driver mutations and cancer genes and helps to rank mutations or genes for better decision-making among clinical oncologists, cancer researchers and the broad scientific community interested in cancer precision medicine.
References
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