Xenome--a tool for classifying reads from xenograft samples.
BACKGROUND
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.


BACKGROUND
Xenome is available for non-commercial use from http://www.nicta.com.au/bioinformatics.
NICTA Victoria Research Laboratory, Department of Computer Science and Software Engineering, The University of Melbourne, Parkville and Monash Institute of Medical Research, Monash University, Clayton, Australia. tom.conway@nicta.com.au
Thomas
T
Conway
Jeremy
J
Wazny
Andrew
A
Bromage
Martin
M
Tymms
Dhanya
D
Sooraj
Elizabeth D
ED
Williams
Bryan
B
Beresford-Smith
D000465:Algorithms; D000818:Animals; D018076:DNA, Complementary / Q000235:genetics; D016678:Genome / Q000235:genetics; D006801:Humans; D051379:Mice; D017423:Sequence Analysis, RNA / Q000379:methods*; D012984:Software; D014183:Transplantation, Heterologous / Q000145:classification*
D018076:DNA, Complementary