Please use this identifier to cite or link to this item: https://ahro.austin.org.au/austinjspui/handle/1/20975
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dc.contributor.authorSilk, Michael-
dc.contributor.authorPetrovski, Slavé-
dc.contributor.authorAscher, David B-
dc.date2019-07-02-
dc.date.accessioned2019-06-19T06:29:49Z-
dc.date.available2019-06-19T06:29:49Z-
dc.date.issued2019-06-06-
dc.identifier.citationNucleic acids research 2019; 47(W1): W121-W126-
dc.identifier.urihttps://ahro.austin.org.au/austinjspui/handle/1/20975-
dc.description.abstractAdvances in genomic sequencing have enormous potential to revolutionize personalized medicine, however distinguishing disease-causing from benign variants remains a challenge. The increasing number of human genome and exome sequences available has revealed areas where unfavourable variation is removed through purifying selection. Here, we present the MTR-Viewer, a web-server enabling easy visualization at the gene or variant level of the Missense Tolerance Ratio (MTR), a measure of regional intolerance to missense variation calculated using variation from 240 000 exome and genome sequences. The MTR-Viewer enables exploration of MTR calculations, using different sliding windows, for over 18 000 human protein-coding genes and 85 000 alternative transcripts. Users can also view MTR scores calculated for specific ethnicities, to enable easy exploration of regions that may be under different selective pressure. The spatial distribution of population and known disease variants is also displayed on the protein's domain structure. Intolerant regions were found to be highly enriched for ClinVar pathogenic and COSMIC somatic missense variants (Mann-Whitney U test P < 2.2 × 10-16). As the MTR is not biased by known domains and protein features, it can highlight functionally important regions within genes overlooked or inaccessible by traditional methods. MTR-Viewer is freely available via a user friendly web-server at http://biosig.unimelb.edu.au/mtr-viewer/.-
dc.language.isoeng-
dc.titleMTR-Viewer: identifying regions within genes under purifying selection.-
dc.typeJournal Article-
dc.identifier.journaltitleNucleic acids research-
dc.identifier.affiliationDepartment of Biochemistry, University of Cambridge; Cambridge CB2 1GA, UKen
dc.identifier.affiliationCentre for Genomics Research, Precision Medicine and Genomics, IMED Biotech Unit, AstraZeneca, Cambridge, UKen
dc.identifier.affiliationDepartment of Medicine, The University of Melbourne, Royal Melbourne Hospital, Melbourne, VIC 3050, Australiaen
dc.identifier.affiliationDepartment of Biochemistry and Molecular Biology, University of Melbourne, Melbourne, VIC 3052, Australiaen
dc.identifier.affiliationACRF Facility for Innovative Cancer Drug Discovery, Bio21 Institute, University of Melbourne, Melbourne, VIC 3052, Australiaen
dc.identifier.affiliationStructural Biology and Bioinformatics, Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australiaen
dc.identifier.affiliationDepartment of Medicine, Austin Health, The University of Melbourne, Heidelberg, Victoria, Australia-
dc.identifier.doi10.1093/nar/gkz457-
dc.identifier.orcid0000-0002-1527-961X-
dc.identifier.pubmedid31170280-
dc.type.austinJournal Article-
item.openairetypeJournal Article-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
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