Journal
BIOINFORMATICS
Volume 28, Issue 12, Pages I172-I178Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/bts236
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Funding
- Australian Government's Department of Communications
- Information Technology and the Arts
- Australian Research Council through Backing Australia's Ability
- ICT Centre of Excellence programs
- Prostate Cancer Foundation of Australia (EDW)
- Victorian Government's Operational Infrastructure Support Program
- Australian NHMRC Career Development Award [519539]
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Motivation: Shotgun sequence read data derived from xenograft material contains a mixture of reads arising from the host and reads arising from the graft. Classifying the read mixture to separate the two allows for more precise analysis to be performed. Results: We present a technique, with an associated tool Xenome, which performs fast, accurate and specific classification of xenograft-derived sequence read data. We have evaluated it on RNA-Seq data from human, mouse and human-in-mouse xenograft datasets.
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