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

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109 Citations (Scopus)

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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