This week in techniques



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Computational models

An algorithm for more accurate identification of cancer-associated mutations in genome sequencing studies

An improved algorithm to assess the significance of mutations identified through genome sequencing could be used to more accurately predict cancer-associated genes. A set of 3,083 matched, tumor-normal pairs was used to develop an algorithm to identify cancer-associated genes that includes correcting for heterogeneous rates of mutation across the genome. The algorithm identified cancer-associated genes with higher accuracy than an earlier iteration of the algorithm that did not correct for heterogeneous rates of mutation. Next steps include improving model accuracy using additional sequencing data (see Cancer genome
statistics lesson, page 7).

SciBX 6(27); doi:10.1038/scibx.2013.699
Published online July 18, 2013

Patent application filed; freely available for not-for-profit use; available for licensing for commercial use

Lawrence, M.S. et al. Nature; published online June 16, 2013;
Contact: Gad Getz, Broad Institute of MIT and Harvard, Cambridge, Mass.
Contact: Eric S. Lander, same affiliation as above