Xenome-a tool for classifying reads from xenograft samples

被引：193

作者：

Conway, Thomas ^{[1
]}

Wazny, Jeremy ^{[1
]}

Bromage, Andrew ^{[1
]}

Tymms, Martin ^{[2
]}

Sooraj, Dhanya ^{[2
]}

Williams, Elizabeth D. ^{[2
]}

Beresford-Smith, Bryan ^{[1
]}

机构：

[1] Univ Melbourne, NICTA Victoria Res Lab, Dept Comp Sci & Software Engn, Parkville, Vic 3052, Australia

[2] Monash Univ, Monash Inst Med Res, Clayton, Vic, Australia

来源：

BIOINFORMATICS | 2012年 / 28卷 / 12期

基金：

澳大利亚国家健康与医学研究理事会; 澳大利亚研究理事会;

关键词：

RNA-SEQ; TRANSCRIPTS; METASTASIS; GENOMES;

D O I：

10.1093/bioinformatics/bts236

中图分类号：

Q5 [生物化学];

学科分类号：

070307 [化学生物学];

摘要：

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.

引用

页码：I172 / I178

页数：7

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