Xenome—a tool for classifying reads from xenograft samples
Open Access
- 9 June 2012
- journal article
- conference paper
- Published by Oxford University Press (OUP) in Bioinformatics
- Vol. 28 (12) , i172-i178
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 Contact:tom.conway@nicta.com.auKeywords
This publication has 18 references indexed in Scilit:
- AREM: Aligning Short Reads from ChIP-Sequencing by Expectation MaximizationJournal of Computational Biology, 2011
- Identification of novel transcripts in annotated genomes using RNA-SeqBioinformatics, 2011
- Comparative studies of de novo assembly tools for next-generation sequencing technologiesBioinformatics, 2011
- Next-generation VariationHunter: combinatorial algorithms for transposon insertion discoveryBioinformatics, 2010
- Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiationNature Biotechnology, 2010
- Validation of a mouse xenograft model system for gene expression analysis of human acute lymphoblastic leukaemiaBMC Genomics, 2010
- Genome remodelling in a basal-like breast cancer metastasis and xenograftNature, 2010
- De novo assembly of human genomes with massively parallel short read sequencingGenome Research, 2009
- TopHat: discovering splice junctions with RNA-SeqBioinformatics, 2009
- BLAT—The BLAST-Like Alignment ToolGenome Research, 2002