4.7 Article Proceedings Paper

Xenome-a tool for classifying reads from xenograft samples

Journal

BIOINFORMATICS
Volume 28, Issue 12, Pages I172-I178

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/bts236

Keywords

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Funding

  1. Australian Government's Department of Communications
  2. Information Technology and the Arts
  3. Australian Research Council through Backing Australia's Ability
  4. ICT Centre of Excellence programs
  5. Prostate Cancer Foundation of Australia (EDW)
  6. Victorian Government's Operational Infrastructure Support Program
  7. 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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