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 assoc...

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Detalles Bibliográficos
Autores principales: Conway, Thomas, Wazny, Jeremy, Bromage, Andrew, Tymms, Martin, Sooraj, Dhanya, Williams, Elizabeth D., Beresford-Smith, Bryan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2012
Materias:
Ismb 2012 Proceedings Papers Committee July 15 to July 19, 2012, Long Beach, Ca, Usa
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3371868/
https://www.ncbi.nlm.nih.gov/pubmed/22689758
http://dx.doi.org/10.1093/bioinformatics/bts236
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author Conway, Thomas
Wazny, Jeremy
Bromage, Andrew
Tymms, Martin
Sooraj, Dhanya
Williams, Elizabeth D.
Beresford-Smith, Bryan
author_facet Conway, Thomas
Wazny, Jeremy
Bromage, Andrew
Tymms, Martin
Sooraj, Dhanya
Williams, Elizabeth D.
Beresford-Smith, Bryan
author_sort Conway, Thomas
collection PubMed
description 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
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spelling pubmed-33718682012-06-11 Xenome—a tool for classifying reads from xenograft samples Conway, Thomas Wazny, Jeremy Bromage, Andrew Tymms, Martin Sooraj, Dhanya Williams, Elizabeth D. Beresford-Smith, Bryan Bioinformatics Ismb 2012 Proceedings Papers Committee July 15 to July 19, 2012, Long Beach, Ca, Usa 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 Oxford University Press 2012-06-15 2012-06-09 /pmc/articles/PMC3371868/ /pubmed/22689758 http://dx.doi.org/10.1093/bioinformatics/bts236 Text en © The Author(s) 2012. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Ismb 2012 Proceedings Papers Committee July 15 to July 19, 2012, Long Beach, Ca, Usa
Conway, Thomas
Wazny, Jeremy
Bromage, Andrew
Tymms, Martin
Sooraj, Dhanya
Williams, Elizabeth D.
Beresford-Smith, Bryan
Xenome—a tool for classifying reads from xenograft samples
title Xenome—a tool for classifying reads from xenograft samples
title_full Xenome—a tool for classifying reads from xenograft samples
title_fullStr Xenome—a tool for classifying reads from xenograft samples
title_full_unstemmed Xenome—a tool for classifying reads from xenograft samples
title_short Xenome—a tool for classifying reads from xenograft samples
title_sort xenome—a tool for classifying reads from xenograft samples
topic Ismb 2012 Proceedings Papers Committee July 15 to July 19, 2012, Long Beach, Ca, Usa
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3371868/
https://www.ncbi.nlm.nih.gov/pubmed/22689758
http://dx.doi.org/10.1093/bioinformatics/bts236
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