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Disambiguate: An open-source application for disambiguating two species in next generation sequencing data from grafted samples
Grafting of cell lines and primary tumours is a crucial step in the drug development process between cell line studies and clinical trials. Disambiguate is a program for computationally separating the sequencing reads of two species derived from grafted samples. Disambiguate operates on DNA or RNA-s...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
F1000Research
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5130069/ https://www.ncbi.nlm.nih.gov/pubmed/27990269 http://dx.doi.org/10.12688/f1000research.10082.2 |
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author | Ahdesmäki, Miika J. Gray, Simon R. Johnson, Justin H. Lai, Zhongwu |
author_facet | Ahdesmäki, Miika J. Gray, Simon R. Johnson, Justin H. Lai, Zhongwu |
author_sort | Ahdesmäki, Miika J. |
collection | PubMed |
description | Grafting of cell lines and primary tumours is a crucial step in the drug development process between cell line studies and clinical trials. Disambiguate is a program for computationally separating the sequencing reads of two species derived from grafted samples. Disambiguate operates on DNA or RNA-seq alignments to the two species and separates the components at very high sensitivity and specificity as illustrated in artificially mixed human-mouse samples. This allows for maximum recovery of data from target tumours for more accurate variant calling and gene expression quantification. Given that no general use open source algorithm accessible to the bioinformatics community exists for the purposes of separating the two species data, the proposed Disambiguate tool presents a novel approach and improvement to performing sequence analysis of grafted samples. Both Python and C++ implementations are available and they are integrated into several open and closed source pipelines. Disambiguate is open source and is freely available at https://github.com/AstraZeneca-NGS/disambiguate. |
format | Online Article Text |
id | pubmed-5130069 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | F1000Research |
record_format | MEDLINE/PubMed |
spelling | pubmed-51300692016-12-16 Disambiguate: An open-source application for disambiguating two species in next generation sequencing data from grafted samples Ahdesmäki, Miika J. Gray, Simon R. Johnson, Justin H. Lai, Zhongwu F1000Res Software Tool Article Grafting of cell lines and primary tumours is a crucial step in the drug development process between cell line studies and clinical trials. Disambiguate is a program for computationally separating the sequencing reads of two species derived from grafted samples. Disambiguate operates on DNA or RNA-seq alignments to the two species and separates the components at very high sensitivity and specificity as illustrated in artificially mixed human-mouse samples. This allows for maximum recovery of data from target tumours for more accurate variant calling and gene expression quantification. Given that no general use open source algorithm accessible to the bioinformatics community exists for the purposes of separating the two species data, the proposed Disambiguate tool presents a novel approach and improvement to performing sequence analysis of grafted samples. Both Python and C++ implementations are available and they are integrated into several open and closed source pipelines. Disambiguate is open source and is freely available at https://github.com/AstraZeneca-NGS/disambiguate. F1000Research 2017-01-24 /pmc/articles/PMC5130069/ /pubmed/27990269 http://dx.doi.org/10.12688/f1000research.10082.2 Text en Copyright: © 2017 Ahdesmäki MJ et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Software Tool Article Ahdesmäki, Miika J. Gray, Simon R. Johnson, Justin H. Lai, Zhongwu Disambiguate: An open-source application for disambiguating two species in next generation sequencing data from grafted samples |
title | Disambiguate: An open-source application for disambiguating two species in next generation sequencing data from grafted samples |
title_full | Disambiguate: An open-source application for disambiguating two species in next generation sequencing data from grafted samples |
title_fullStr | Disambiguate: An open-source application for disambiguating two species in next generation sequencing data from grafted samples |
title_full_unstemmed | Disambiguate: An open-source application for disambiguating two species in next generation sequencing data from grafted samples |
title_short | Disambiguate: An open-source application for disambiguating two species in next generation sequencing data from grafted samples |
title_sort | disambiguate: an open-source application for disambiguating two species in next generation sequencing data from grafted samples |
topic | Software Tool Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5130069/ https://www.ncbi.nlm.nih.gov/pubmed/27990269 http://dx.doi.org/10.12688/f1000research.10082.2 |
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