Please use this identifier to cite or link to this item: https://ahro.austin.org.au/austinjspui/handle/1/16803
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dc.contributor.authorGussow, Ayal B-
dc.contributor.authorCopeland, Brett R-
dc.contributor.authorDhindsa, Ryan S-
dc.contributor.authorWang, Quanli-
dc.contributor.authorPetrovski, Slavé-
dc.contributor.authorMajoros, William H-
dc.contributor.authorAllen, Andrew S-
dc.contributor.authorGoldstein, David B-
dc.date2017-08-10-
dc.date.accessioned2017-08-18T00:40:50Z-
dc.date.available2017-08-18T00:40:50Z-
dc.date.issued2017-08-10-
dc.identifier.citationPLoS One 2017; 12(8): e0181604en_US
dc.identifier.urihttps://ahro.austin.org.au/austinjspui/handle/1/16803-
dc.description.abstractThere is broad agreement that genetic mutations occurring outside of the protein-coding regions play a key role in human disease. Despite this consensus, we are not yet capable of discerning which portions of non-coding sequence are important in the context of human disease. Here, we present Orion, an approach that detects regions of the non-coding genome that are depleted of variation, suggesting that the regions are intolerant of mutations and subject to purifying selection in the human lineage. We show that Orion is highly correlated with known intolerant regions as well as regions that harbor putatively pathogenic variation. This approach provides a mechanism to identify pathogenic variation in the human non-coding genome and will have immediate utility in the diagnostic interpretation of patient genomes and in large case control studies using whole-genome sequences.en_US
dc.titleOrion: Detecting regions of the human non-coding genome that are intolerant to variation using population geneticsen_US
dc.typeJournal Articleen_US
dc.identifier.journaltitlePLoS Oneen_US
dc.identifier.affiliationProgram in Computational Biology and Bioinformatics, Duke University, Durham, NC, United States of Americaen_US
dc.identifier.affiliationInstitute for Genomic Medicine, Columbia University, New York, NY, United States of Americaen_US
dc.identifier.affiliationDepartment of Medicine, The University of Melbourne, Austin Health and Royal Melbourne Hospital, Melbourne, Victoria, Australiaen_US
dc.identifier.affiliationCenter for Genomic and Computational Biology, Duke University, Durham, NC, United States of Americaen_US
dc.identifier.affiliationDepartment of Biostatistics and Bioinformatics, Duke University, Durham NC, United States of America. Abstracten_US
dc.identifier.pubmedurihttps://pubmed.ncbi.nlm.nih.gov/28797091en_US
dc.identifier.doi10.1371/journal.pone.0181604en_US
dc.type.contentTexten_US
dc.type.austinJournal Articleen_US
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.openairetypeJournal Article-
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