Improving cancer gene identification
29 Nov 2011
Actively causing mutations to disrupt cellular processes and thus, perhaps, cause cancer in mouse models is a widely used approach to find cancer genes and study affected regions in the genome. This process, called insertional mutagenesis, employs retroviruses and transposons that are integrated into the host DNA. Identifying which genes are affected by these insertions and are responsible for cancer development is not yet a straightforward task. To improve the analysis of large-scale insertional mutagenesis screens, Johann de Jong (Netherlands Cancer Institute) and colleagues developed Kernel Convolved Rule Based Mapping (KC-RBM), a computational method to map integration sites to target genes. When compared to existing methods, KC-RBM showed superior performance in identifying true positives. KC-RBM is available as R-package.
J de Jong, J de Ridder, L van der Weyden, N Sun, M van Uitert, A Berns, M van Lohuizen, J Jonkers, DJ Adams, LFA Wessels
Computational identification of insertional mutagenesis targets for cancer gene discovery
Nucleic Acids Research 2011, (39), 15 published online 7 June 2011
By: Esther Thole