VirusSeq: software to identify viruses and their integration sites using next-generation sequencing of human cancer tissue

Yunxin Chen, Hui Yao, Erika J. Thompson, Nizar M. Tannir, John N. Weinstein, Xiaoping Su
<span title="2012-11-17">2012</span> <i title="Oxford University Press (OUP)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4r72gbmtcrde5no3fwwogjs3cu" style="color: black;">Computer applications in the biosciences : CABIOS</a> </i> &nbsp;
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.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1093/bioinformatics/bts665">doi:10.1093/bioinformatics/bts665</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/23162058">pmid:23162058</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC3546792/">pmcid:PMC3546792</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/v2m53c73fra5hlz36ubgve4hea">fatcat:v2m53c73fra5hlz36ubgve4hea</a> </span>
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