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      MetaDome: Pathogenicity analysis of genetic variants through aggregation of homologous human protein domains

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          Abstract

          The growing availability of human genetic variation has given rise to novel methods of measuring genetic tolerance that better interpret variants of unknown significance. We recently developed a concept based on protein domain homology in the human genome to improve variant interpretation. For this purpose, we mapped population variation from the Exome Aggregation Consortium (ExAC) and pathogenic mutations from the Human Gene Mutation Database (HGMD) onto Pfam protein domains. The aggregation of these variation data across homologous domains into meta‐domains allowed us to generate amino acid resolution of genetic intolerance profiles for human protein domains. Here, we developed MetaDome, a fast and easy‐to‐use web server that visualizes meta‐domain information and gene‐wide profiles of genetic tolerance. We updated the underlying data of MetaDome to contain information from 56,319 human transcripts, 71,419 protein domains, 12,164,292 genetic variants from gnomAD, and 34,076 pathogenic mutations from ClinVar. MetaDome allows researchers to easily investigate their variants of interest for the presence or absence of variation at corresponding positions within homologous domains. We illustrate the added value of MetaDome by an example that highlights how it may help in the interpretation of variants of unknown significance. The MetaDome web server is freely accessible at https://stuart.radboudumc.nl/metadome.

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          D³: Data-Driven Documents.

          Data-Driven Documents (D3) is a novel representation-transparent approach to visualization for the web. Rather than hide the underlying scenegraph within a toolkit-specific abstraction, D3 enables direct inspection and manipulation of a native representation: the standard document object model (DOM). With D3, designers selectively bind input data to arbitrary document elements, applying dynamic transforms to both generate and modify content. We show how representational transparency improves expressiveness and better integrates with developer tools than prior approaches, while offering comparable notational efficiency and retaining powerful declarative components. Immediate evaluation of operators further simplifies debugging and allows iterative development. Additionally, we demonstrate how D3 transforms naturally enable animation and interaction with dramatic performance improvements over intermediate representations. © 2010 IEEE
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            HMMER web server: 2015 update

            The HMMER website, available at http://www.ebi.ac.uk/Tools/hmmer/, provides access to the protein homology search algorithms found in the HMMER software suite. Since the first release of the website in 2011, the search repertoire has been expanded to include the iterative search algorithm, jackhmmer. The continued growth of the target sequence databases means that traditional tabular representations of significant sequence hits can be overwhelming to the user. Consequently, additional ways of presenting homology search results have been developed, allowing them to be summarised according to taxonomic distribution or domain architecture. The taxonomy and domain architecture representations can be used in combination to filter the results according to the needs of a user. Searches can also be restricted prior to submission using a new taxonomic filter, which not only ensures that the results are specific to the requested taxonomic group, but also improves search performance. The repertoire of profile hidden Markov model libraries, which are used for annotation of query sequences with protein families and domains, has been expanded to include the libraries from CATH-Gene3D, PIRSF, Superfamily and TIGRFAMs. Finally, we discuss the relocation of the HMMER webserver to the European Bioinformatics Institute and the potential impact that this will have.
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              The Human Gene Mutation Database: towards a comprehensive repository of inherited mutation data for medical research, genetic diagnosis and next-generation sequencing studies

              The Human Gene Mutation Database (HGMD®) constitutes a comprehensive collection of published germline mutations in nuclear genes that underlie, or are closely associated with human inherited disease. At the time of writing (March 2017), the database contained in excess of 203,000 different gene lesions identified in over 8000 genes manually curated from over 2600 journals. With new mutation entries currently accumulating at a rate exceeding 17,000 per annum, HGMD represents de facto the central unified gene/disease-oriented repository of heritable mutations causing human genetic disease used worldwide by researchers, clinicians, diagnostic laboratories and genetic counsellors, and is an essential tool for the annotation of next-generation sequencing data. The public version of HGMD (http://www.hgmd.org) is freely available to registered users from academic institutions and non-profit organisations whilst the subscription version (HGMD Professional) is available to academic, clinical and commercial users under license via QIAGEN Inc.
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                Author and article information

                Contributors
                Christian.Gilissen@radboudumc.nl
                Journal
                Hum Mutat
                Hum. Mutat
                10.1002/(ISSN)1098-1004
                HUMU
                Human Mutation
                John Wiley and Sons Inc. (Hoboken )
                1059-7794
                1098-1004
                18 June 2019
                August 2019
                : 40
                : 8 ( doiID: 10.1002/humu.2019.40.issue-8 )
                : 1030-1038
                Affiliations
                [ 1 ] Department of Human Genetics, Radboud Institute for Molecular Life Sciences Radboud University Medical Center Nijmegen The Netherlands
                [ 2 ] Centre for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences Radboud University Medical Center Nijmegen The Netherlands
                [ 3 ] Bio‐informatica HAN University of Applied Sciences Nijmegen The Netherlands
                [ 4 ] Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour Radboud University Medical Center Nijmegen The Netherlands
                [ 5 ] Institute of Genetic Medicine, International Centre for Life Newcastle University Newcastle upon Tyne United Kingdom
                Author notes
                [*] [* ] Correspondence Christian Gilissen, Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands. Email: Christian.Gilissen@ 123456radboudumc.nl

                Author information
                http://orcid.org/0000-0003-3410-760X
                Article
                HUMU23798
                10.1002/humu.23798
                6772141
                31116477
                719b7ffd-613a-4c02-80c8-2b9df9538834
                © 2019 The Authors. Human Mutation Published by Wiley Periodicals, Inc.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                History
                : 11 January 2019
                : 21 April 2019
                : 15 May 2019
                Page count
                Figures: 2, Tables: 2, Pages: 9, Words: 6192
                Funding
                Funded by: Radboud Universitair Medisch Centrum
                Award ID: R0002793
                Funded by: Nederlandse Organisatie voor Wetenschappelijk Onderzoek
                Award ID: 918‐15‐667
                Award ID: 916‐14‐043
                Categories
                Informatics
                Informatics
                Custom metadata
                2.0
                humu23798
                August 2019
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.6.9 mode:remove_FC converted:01.10.2019

                Human biology
                clinvar,genetic tolerance,genetic variation,gnomad,meta‐domains,pathogenicity,pfam,protein domain homology,web server

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