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

Content Provider	IEEE Xplore Digital Library
Author	Xi Chen Xu Shi Shajahan, A.N. Hilakivi-Clarke, L. Clarke, R. Jianhua Xuan
Copyright Year	2014
Description	Author affiliation: Dept. of Oncology, Georgetown Univ., Washington, DC, USA (Shajahan, A.N.; Hilakivi-Clarke, L.; Clarke, R.) \|\| Bradley Dept. of Electr. & Comput. Eng., Virginia Polytech. Inst. & State Univ., Arlington, VA, USA (Xi Chen; Xu Shi; Jianhua Xuan)
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.
Sponsorship	IEEE Eng. Med. Biol. Soc.
Starting Page	3937
Ending Page	3940
File Size	691079
Page Count	4
File Format	PDF
ISBN	9781424479290
ISSN	1557170X
DOI	10.1109/EMBC.2014.6944485
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bioinformatics Genomics Tumors Bayes methods Breast cancer Sensitivity
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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BSSV: Bayesian based somatic structural variation identification with whole genome DNA-seq data