SUMMARY: We developed a new algorithmic method, VirusSeq, for detecting known viruses and their integration sites in the human genome using next-generation sequencing data. We evaluated VirusSeq on whole-transcriptome sequencing (RNA-Seq) data of 256 human cancer samples from The Cancer Genome Atlas. Using these data, we showed that VirusSeq accurately detects the known viruses and their integration sites with high sensitivity and specificity. VirusSeq can also perform this function using whole-genome sequencing data of human tissue. AVAILABILITY: VirusSeq has been implemented in PERL and is available at http://odin.mdacc.tmc.edu/∼xsu1/VirusSeq.html. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

UNLABELLED: We developed a novel algorithm, PurityEst, to infer the tumor purity level from the allelic differential representation of heterozygous loci with somatic mutations in a human tumor sample with a matched normal tissue using next-generation sequencing data. We applied our tool to a whole cancer genome sequencing datasets and demonstrated the accuracy of PurityEst compared with DNA copy number-based estimation. AVAILABILITY: PurityEst has been implemented in PERL and is available at http://odin.mdacc.tmc.edu/~xsu1/PurityEst.html.