Format

Send to

Choose Destination
Bioinformatics. 2012 Jun 15;28(12):i172-8. doi: 10.1093/bioinformatics/bts236.

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

Author information

1
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

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.

PMID:
22689758
PMCID:
PMC3371868
DOI:
10.1093/bioinformatics/bts236
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Silverchair Information Systems Icon for PubMed Central
Loading ...
Support Center