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dc.contributor.authorFreytag, S
dc.contributor.authorBurgess, R
dc.contributor.authorOliver, KL
dc.contributor.authorBahlo, M
dc.date.accessioned2021-02-04T02:03:08Z
dc.date.available2021-02-04T02:03:08Z
dc.date.issued2017-06-08
dc.identifierpii: 10.1186/s13073-017-0444-y
dc.identifier.citationFreytag, S., Burgess, R., Oliver, K. L. & Bahlo, M. (2017). brain-coX: investigating and visualising gene co-expression in seven human brain transcriptomic datasets. GENOME MEDICINE, 9 (1), https://doi.org/10.1186/s13073-017-0444-y.
dc.identifier.issn1756-994X
dc.identifier.urihttp://hdl.handle.net/11343/259554
dc.description.abstractBACKGROUND: The pathogenesis of neurological and mental health disorders often involves multiple genes, complex interactions, as well as brain- and development-specific biological mechanisms. These characteristics make identification of disease genes for such disorders challenging, as conventional prioritisation tools are not specifically tailored to deal with the complexity of the human brain. Thus, we developed a novel web-application-brain-coX-that offers gene prioritisation with accompanying visualisations based on seven gene expression datasets in the post-mortem human brain, the largest such resource ever assembled. RESULTS: We tested whether our tool can correctly prioritise known genes from 37 brain-specific KEGG pathways and 17 psychiatric conditions. We achieved average sensitivity of nearly 50%, at the same time reaching a specificity of approximately 75%. We also compared brain-coX's performance to that of its main competitors, Endeavour and ToppGene, focusing on the ability to discover novel associations. Using a subset of the curated SFARI autism gene collection we show that brain-coX's prioritisations are most similar to SFARI's own curated gene classifications. CONCLUSIONS: brain-coX is the first prioritisation and visualisation web-tool targeted to the human brain and can be freely accessed via http://shiny.bioinf.wehi.edu.au/freytag.s/ .
dc.languageEnglish
dc.publisherBMC
dc.titlebrain-coX: investigating and visualising gene co-expression in seven human brain transcriptomic datasets
dc.typeJournal Article
dc.identifier.doi10.1186/s13073-017-0444-y
melbourne.affiliation.departmentMedicine and Radiology
melbourne.affiliation.departmentSchool of Mathematics and Statistics
melbourne.affiliation.departmentMedical Biology (W.E.H.I.)
melbourne.affiliation.facultyMedicine, Dentistry & Health Sciences
melbourne.affiliation.facultyScience
melbourne.source.titleGenome Medicine: medicine in the post-genomic era
melbourne.source.volume9
melbourne.source.issue1
dc.rights.licenseCC BY
melbourne.elementsid1214957
melbourne.contributor.authorFreytag, Saskia
melbourne.contributor.authorBahlo, Melanie
melbourne.contributor.authorBroderick, Karen
melbourne.contributor.authorBurgess, Rosemary
dc.identifier.eissn1756-994X
melbourne.accessrightsOpen Access


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