Oncocis: Annotation of cis-regulatory mutations in cancer

Perera, D; Chacon, D; Thoms, JA; Poulos, RC; Shlien, A; Beck, D; Campbell, PJ; Pimanda, JE; Wong, JW

Oncocis: Annotation of cis-regulatory mutations in cancer

Perera, D Chacon, D

Thoms, JA Poulos, RC Shlien, A Beck, D Campbell, PJ Pimanda, JE Wong, JW

Permalink

Publication Type:: Journal Article
Citation:: Genome Biology, 2014, 15 (10)
Issue Date:: 2014-01-01

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download Published VersionAdobe PDF (3.16 MB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Perera, D	en_US
dc.contributor.author	Chacon, D https://orcid.org/0000-0003-3729-1385	en_US
dc.contributor.author	Thoms, JA	en_US
dc.contributor.author	Poulos, RC	en_US
dc.contributor.author	Shlien, A	en_US
dc.contributor.author	Beck, D	en_US
dc.contributor.author	Campbell, PJ	en_US
dc.contributor.author	Pimanda, JE	en_US
dc.contributor.author	Wong, JW	en_US
dc.date.issued	2014-01-01	en_US
dc.identifier.citation	Genome Biology, 2014, 15 (10)	en_US
dc.identifier.issn	1474-7596	en_US
dc.identifier.uri	http://hdl.handle.net/10453/116253
dc.description.abstract	Whole genome sequencing has enabled the identification of thousands of somatic mutations within non-coding genomic regions of individual cancer samples. However, identification of mutations that potentially alter gene regulation remains a major challenge. Here we present OncoCis, a new method that enables identification of potential cis-regulatory mutations using cell type-specific genome and epigenome-wide datasets along with matching gene expression data. We demonstrate that the use of cell type-specific information and gene expression can significantly reduce the number of candidate cis-regulatory mutations compared with existing tools designed for the annotation of cis-regulatory SNPs.	en_US
dc.relation.ispartof	Genome Biology	en_US
dc.relation.isbasedon	10.1186/s13059-014-0485-0	en_US
dc.subject.classification	Bioinformatics	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Neoplasms	en_US
dc.subject.mesh	Telomerase	en_US
dc.subject.mesh	DNA Mutational Analysis	en_US
dc.subject.mesh	Computational Biology	en_US
dc.subject.mesh	Gene Expression Regulation, Neoplastic	en_US
dc.subject.mesh	Mutation	en_US
dc.subject.mesh	Software	en_US
dc.subject.mesh	Databases, Genetic	en_US
dc.subject.mesh	Promoter Regions, Genetic	en_US
dc.subject.mesh	Epigenomics	en_US
dc.subject.mesh	Molecular Sequence Annotation	en_US
dc.title	Oncocis: Annotation of cis-regulatory mutations in cancer	en_US
dc.type	Journal Article
utslib.citation.volume	10	en_US
utslib.citation.volume	15	en_US
utslib.for	080301 Bioinformatics Software	en_US
utslib.for	05 Environmental Sciences	en_US
utslib.for	06 Biological Sciences	en_US
utslib.for	08 Information and Computing Sciences	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Biomedical Engineering
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Software
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	open_access
pubs.issue	10	en_US
pubs.publication-status	Published	en_US
pubs.volume	15	en_US

Abstract:

Whole genome sequencing has enabled the identification of thousands of somatic mutations within non-coding genomic regions of individual cancer samples. However, identification of mutations that potentially alter gene regulation remains a major challenge. Here we present OncoCis, a new method that enables identification of potential cis-regulatory mutations using cell type-specific genome and epigenome-wide datasets along with matching gene expression data. We demonstrate that the use of cell type-specific information and gene expression can significantly reduce the number of candidate cis-regulatory mutations compared with existing tools designed for the annotation of cis-regulatory SNPs.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/116253