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Xenome-a tool for classifying reads from xenograft samples

  • Thomas Conway
  • , Jeremy Wazny
  • , Andrew Bromage
  • , Martin James Tymms
  • , Dhanya Sooraj
  • , Elizabeth Williams
  • , Bryan Beresford-Smith

Research output: Contribution to journalArticleResearchpeer-review

Abstract

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. AVAILABILITY: Xenome is available for non-commercial use from http://www.nicta.com.au/bioinformatics
Original languageEnglish
Pages (from-to)172 - 178
Number of pages7
JournalBioinformatics
Volume28
Issue number12
DOIs
Publication statusPublished - 2012

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