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Rapid and powerful detection of subtle allelic imbalance from exome sequencing data with hapLOHseq
Motivation: The detection of subtle genomic allelic imbalance events has many potential applications. For example, identifying cancer-associated allelic imbalanced regions in low tumor-cellularity samples or in low-proportion tumor subclones can be used for early cancer detection, prognostic assessm...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5039922/ https://www.ncbi.nlm.nih.gov/pubmed/27288500 http://dx.doi.org/10.1093/bioinformatics/btw340 |
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author | San Lucas, F. Anthony Sivakumar, Smruthy Vattathil, Selina Fowler, Jerry Vilar, Eduardo Scheet, Paul |
author_facet | San Lucas, F. Anthony Sivakumar, Smruthy Vattathil, Selina Fowler, Jerry Vilar, Eduardo Scheet, Paul |
author_sort | San Lucas, F. Anthony |
collection | PubMed |
description | Motivation: The detection of subtle genomic allelic imbalance events has many potential applications. For example, identifying cancer-associated allelic imbalanced regions in low tumor-cellularity samples or in low-proportion tumor subclones can be used for early cancer detection, prognostic assessment and therapeutic selection in cancer patients. We developed hapLOHseq for the detection of subtle allelic imbalance events from next-generation sequencing data. Results: Our method identified events of 10 megabases or greater occurring in as little as 16% of the sample in exome sequencing data (at 80×) and 4% in whole genome sequencing data (at 30×), far exceeding the capabilities of existing software. We also found hapLOHseq to be superior at detecting large chromosomal changes across a series of pancreatic samples from TCGA. Availability and Implementation: hapLOHseq is available at scheet.org/software, distributed under an open source MIT license. Contact: pscheet@alum.wustl.edu Supplementary information: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-5039922 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-50399222016-09-29 Rapid and powerful detection of subtle allelic imbalance from exome sequencing data with hapLOHseq San Lucas, F. Anthony Sivakumar, Smruthy Vattathil, Selina Fowler, Jerry Vilar, Eduardo Scheet, Paul Bioinformatics Applications Notes Motivation: The detection of subtle genomic allelic imbalance events has many potential applications. For example, identifying cancer-associated allelic imbalanced regions in low tumor-cellularity samples or in low-proportion tumor subclones can be used for early cancer detection, prognostic assessment and therapeutic selection in cancer patients. We developed hapLOHseq for the detection of subtle allelic imbalance events from next-generation sequencing data. Results: Our method identified events of 10 megabases or greater occurring in as little as 16% of the sample in exome sequencing data (at 80×) and 4% in whole genome sequencing data (at 30×), far exceeding the capabilities of existing software. We also found hapLOHseq to be superior at detecting large chromosomal changes across a series of pancreatic samples from TCGA. Availability and Implementation: hapLOHseq is available at scheet.org/software, distributed under an open source MIT license. Contact: pscheet@alum.wustl.edu Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2016-10-01 2016-06-10 /pmc/articles/PMC5039922/ /pubmed/27288500 http://dx.doi.org/10.1093/bioinformatics/btw340 Text en © The Author 2016. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes San Lucas, F. Anthony Sivakumar, Smruthy Vattathil, Selina Fowler, Jerry Vilar, Eduardo Scheet, Paul Rapid and powerful detection of subtle allelic imbalance from exome sequencing data with hapLOHseq |
title | Rapid and powerful detection of subtle allelic imbalance from exome sequencing data with hapLOHseq |
title_full | Rapid and powerful detection of subtle allelic imbalance from exome sequencing data with hapLOHseq |
title_fullStr | Rapid and powerful detection of subtle allelic imbalance from exome sequencing data with hapLOHseq |
title_full_unstemmed | Rapid and powerful detection of subtle allelic imbalance from exome sequencing data with hapLOHseq |
title_short | Rapid and powerful detection of subtle allelic imbalance from exome sequencing data with hapLOHseq |
title_sort | rapid and powerful detection of subtle allelic imbalance from exome sequencing data with haplohseq |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5039922/ https://www.ncbi.nlm.nih.gov/pubmed/27288500 http://dx.doi.org/10.1093/bioinformatics/btw340 |
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