Precision cancer medicine aims to classify tumors by site, histology, and molecular testing to determine an individualized profile of cancer alterations. Viruses are a major contributor to oncogenesis, causing 12% to 20% of all human cancers. Several viruses are causal of specific types of cancer, promoting dysregulation of signaling pathways and resulting in carcinogenesis. In addition, integration of viral DNA into the host (human) genome is a hallmark of some viral species. Tests for the presence of viral infection used in the clinical setting most often use quantitative PCR or immunohistochemical staining. Both approaches have limitations and need to be interpreted/scored appropriately. In some cases, results are not binary (virus present/absent), and it is unclear what to do with a weakly or partially positive result. In addition, viral testing of cancers is performed separately from tests to detect human genomic alterations and can thus be time-consuming and use limited valuable specimen. We present a hybrid-capture and massively parallel sequencing approach to detect viral infection that is integrated with targeted genomic analysis to provide a more complete tumor profile from a single sample.