BSSV: Bayesian based somatic structural variation identification with whole genome DNA-seq data

Xi Chen, Xu Shi, Ayesha N. Shajahan, Leena Hilakivi-Clarke, Robert Clarke, Jianhua Xuan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

High coverage whole genome DNA-sequencing enables identification of somatic structural variation (SSV) more evident in paired tumor and normal samples. Recent studies show that simultaneous analysis of paired samples provides a better resolution of SSV detection than subtracting shared SVs. However, available tools can neither identify all types of SSVs nor provide any rank information regarding their somatic features. In this paper, we have developed a Bayesian framework, by integrating read alignment information from both tumor and normal samples, called BSSV, to calculate the significance of each SSV. Tested by simulated data, the precision of BSSV is comparable to that of available tools and the false negative rate is significantly lowered. We have also applied this approach to The Cancer Genome Atlas breast cancer data for SSV detection. Many known breast cancer specific mutated genes like RAD51, BRIP1, ER, PGR and PTPRD have been successfully identified.

Original languageEnglish (US)
Title of host publication2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3937-3940
Number of pages4
ISBN (Electronic)9781424479290
DOIs
StatePublished - Nov 2 2014
Externally publishedYes
Event2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 - Chicago, United States
Duration: Aug 26 2014Aug 30 2014

Publication series

Name2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014

Other

Other2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
CountryUnited States
CityChicago
Period8/26/148/30/14

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  • Cite this

    Chen, X., Shi, X., Shajahan, A. N., Hilakivi-Clarke, L., Clarke, R., & Xuan, J. (2014). BSSV: Bayesian based somatic structural variation identification with whole genome DNA-seq data. In 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 (pp. 3937-3940). [6944485] (2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2014.6944485