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Identification of cancer driver genes in focal genomic aberrations from whole-exome sequencing data

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Abstract
aSummary: Whole-exome sequencing (WES) data have been used for identifying copy number aberrations in cancer cells. Nonetheless, the use of WES is still challenging for identification of focal aberrant regions in multiple samples that may contain cancer driver genes. In this study, we developed a wavelet-based method for identifying focal genomic aberrant regions in the WES data from cancer cells (WIFA-X). When we applied WIFA-X to glioblastoma multiforme and lung adenocarcinoma datasets, WIFA-X outperformed other approaches on identifying cancer driver genes.
Author(s)
Jang, HoLee, Hyunju
Issued Date
2018-02
Type
Article
DOI
10.1093/bioinformatics/btx620
URI
https://scholar.gist.ac.kr/handle/local/13409
Publisher
Oxford University Press
Citation
Bioinformatics, v.34, no.3, pp.519 - 521
ISSN
1367-4803
Appears in Collections:
Department of AI Convergence > 1. Journal Articles
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