Abstract
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. R source code is available at http://gcancer.org/wifax. hyunjulee@gist.ac.kr. Supplementary data are available at Bioinformatics online.
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