Somatic mutation calling from next-generation sequencing data remains a challenge due to the difficulties of distinguishing true somatic events from artifacts arising from PCR, sequencing errors or mis-mapping. Tumor cellularity or purity, sub-clonality and copy number changes also confound the identification of true somatic events against a background of germline variants. We have developed a heuristic strategy and software (http://www.qcmg.org/bioinformatics/qsnp/) for somatic mutation calling in samples with low tumor content and we show the superior sensitivity and precision of our approach using a previously sequenced cell line, a series of tumor/normal admixtures, and 3,253 putative somatic SNVs verified on an orthogonal platform. ; Karin S. Kassahn, Oliver Holmes, Katia Nones, Ann-Marie Patch, David K. Miller, Angelika N. Christ, Ivon Harliwong, Timothy J. Bruxner, Qinying Xu, Matthew Anderson, Scott Wood, Conrad Leonard, Darrin Taylor, Felicity Newell, Sarah Song, Senel Idrisoglu, Craig Nourse, Ehsan Nourbakhsh, Suzanne Manning, Shivangi Wani, Anita Steptoe, Marina Pajic, Mark J. Cowley, Mark Pinese, David K. Chang, Anthony J. Gill, Amber L. Johns, Jianmin Wu, Peter J. Wilson, Lynn Fink, Andrew V. Biankin, Nicola Waddell, Sean M. Grimmond, John V. Pearson