Currently, oncology testing includes molecular studies and cytogenetic analysis to detect genetic aberrations of clinical significance. Next-generation sequencing (NGS) allows rapid analysis of multiple genes for clinically actionable somatic variants. The WUCaMP assay uses targeted capture for NGS analysis of 25 cancerassociated genes to detect mutations at actionable loci. We present clinical validation of the assay and a detailed framework for design and validation of similar clinical assays. Deep sequencing of 78 tumor specimens (!1000Â average unique coverage across the capture region) achieved high sensitivity for detecting somatic variants at low allele fraction (AF). Validation revealed sensitivities and specificities of 100% for detection of single-nucleotide variants (SNVs) within coding regions, compared with SNP array sequence data (95% CI Z 83.4e100.0 for sensitivity and 94.2e100.0 for specificity) or whole-genome sequencing (95% CI Z 89.1e100.0 for sensitivity and 99.9e100.0 for specificity) of HapMap samples. Sensitivity for detecting variants at an observed 10% AF was 100% (95% CI Z 93.2e100.0) in HapMap mixes. Analysis of 15 masked specimens harboring clinically reported variants yielded concordant calls for 13/13 variants at AF of !15%. The WUCaMP assay is a robust and sensitive method to detect somatic variants of clinical significance in molecular oncology laboratories, with reduced time and cost of genetic analysis allowing for strategic patient management. (J Mol Diagn 2014, 16: 89e105; http://dx.doi.org/10.1016/j.jmoldx.2013 Traditional approaches to the genetic characterization of clinical oncology specimens include cytogenetic analysis, fluorescence in situ hybridization (FISH), and molecular studies of single genes. These methodologies are complementary to each other and generate information of diagnostic and prognostic relevance. However, as new insight is gained into the complexities of cancer at the molecular level, the need emerges to obtain a more detailed cancer genetic profile for improved patient management. As illustrated by recent studies, identifying DNA mutations in cancer may aid in understanding clonal evolution, 1 risk stratification, 2 and therapeutic strategies. 3,4 With the advent of next-generation sequencing (NGS), a more complete biological characterization of a tumor can be attained at the molecular level. 5