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dc.contributor.authorAmarasinghe, KC
dc.contributor.authorLi, J
dc.contributor.authorHalgamuge, SK
dc.date.accessioned2020-05-21T03:50:33Z
dc.date.available2020-05-21T03:50:33Z
dc.date.issued2013
dc.identifierpii: 1471-2105-14-S2-S2
dc.identifier.citationAmarasinghe, K. C., Li, J. & Halgamuge, S. K. (2013). CoNVEX: copy number variation estimation in exome sequencing data using HMM. BMC Bioinformatics, 14 (S2), https://doi.org/10.1186/1471-2105-14-S2-S2.
dc.identifier.issn1471-2105
dc.identifier.urihttp://hdl.handle.net/11343/239163
dc.description.abstractBACKGROUND: One of the main types of genetic variations in cancer is Copy Number Variations (CNV). Whole exome sequencing (WES) is a popular alternative to whole genome sequencing (WGS) to study disease specific genomic variations. However, finding CNV in Cancer samples using WES data has not been fully explored. RESULTS: We present a new method, called CoNVEX, to estimate copy number variation in whole exome sequencing data. It uses ratio of tumour and matched normal average read depths at each exonic region, to predict the copy gain or loss. The useful signal produced by WES data will be hindered by the intrinsic noise present in the data itself. This limits its capacity to be used as a highly reliable CNV detection source. Here, we propose a method that consists of discrete wavelet transform (DWT) to reduce noise. The identification of copy number gains/losses of each targeted region is performed by a Hidden Markov Model (HMM). CONCLUSION: HMM is frequently used to identify CNV in data produced by various technologies including Array Comparative Genomic Hybridization (aCGH) and WGS. Here, we propose an HMM to detect CNV in cancer exome data. We used modified data from 1000 Genomes project to evaluate the performance of the proposed method. Using these data we have shown that CoNVEX outperforms the existing methods significantly in terms of precision. Overall, CoNVEX achieved a sensitivity of more than 92% and a precision of more than 50%.
dc.languageEnglish
dc.publisherBioMed Central
dc.titleCoNVEX: copy number variation estimation in exome sequencing data using HMM
dc.typeJournal Article
dc.identifier.doi10.1186/1471-2105-14-S2-S2
melbourne.affiliation.departmentSir Peter MacCallum Department of Oncology
melbourne.affiliation.departmentMechanical Engineering
melbourne.source.titleBMC Bioinformatics
melbourne.source.volume14
melbourne.source.issueS2
melbourne.identifier.arcDP1096296
dc.rights.licenseCC BY
melbourne.elementsid499423
melbourne.openaccess.pmchttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC3549847
melbourne.contributor.authorHalgamuge, Saman
melbourne.contributor.authorAmarasinghe, Kaushalya
melbourne.contributor.authorLi, Jason
dc.identifier.eissn1471-2105
melbourne.conference.locationVancouver, CANADA
melbourne.identifier.fundernameidAUST RESEARCH COUNCIL, DP1096296
melbourne.accessrightsOpen Access


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