Dataset Information

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

ABSTRACT:

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

xsu1@mdanderson.org

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Chen Y

PROVIDER: S-EPMC3546792 | biostudies-literature | 2013 Jan

REPOSITORIES: biostudies-literature

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Publications

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

Chen Yunxin Y Yao Hui H Thompson Erika J EJ Tannir Nizar M NM Weinstein John N JN Su Xiaoping X

Bioinformatics (Oxford, England) 20121117 2

<h4>Summary</h4>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 ...[more]

PMID: 23162058

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Project description:Motivation. Alternative splicing events (ASEs) are prevalent in the transcriptome of eukaryotic species and are known to influence many biological phenomena. The identification and quantification of these events are crucial for a better understanding of biological processes. Next-generation DNA sequencing technologies have allowed deep characterization of transcriptomes and made it possible to address these issues. ASEs analysis, however, represents a challenging task especially when many different samples need to be compared. Some popular tools for the analysis of ASEs are known to report thousands of events without annotations and/or graphical representations. A new tool for the identification and visualization of ASEs is here described, which can be used by biologists without a solid bioinformatics background. Results. A software suite named Splicing Express was created to perform ASEs analysis from transcriptome sequencing data derived from next-generation DNA sequencing platforms. Its major goal is to serve the needs of biomedical researchers who do not have bioinformatics skills. Splicing Express performs automatic annotation of transcriptome data (GTF files) using gene coordinates available from the UCSC genome browser and allows the analysis of data from all available species. The identification of ASEs is done by a known algorithm previously implemented in another tool named Splooce. As a final result, Splicing Express creates a set of HTML files composed of graphics and tables designed to describe the expression profile of ASEs among all analyzed samples. By using RNA-Seq data from the Illumina Human Body Map and the Rat Body Map, we show that Splicing Express is able to perform all tasks in a straightforward way, identifying well-known specific events. Availability and Implementation. Splicing Express is written in Perl and is suitable to run only in UNIX-like systems. More details can be found at: http://www.bioinformatics-brazil.org/splicingexpress.

Dataset Information

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

Summary

Availability

Contact

Supplementary information

Publications

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

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