Xenome—a tool for classifying reads from xenograft samples

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 Contact: tom.conway@nicta.com.au