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BreakDancer: An algorithm for high resolution mapping of genomic structural variation

Detection and characterization of genomic structural variation are important for understanding the landscape of genetic variation in human populations and in complex diseases such as cancer. Recent studies demonstrate the feasibility of detecting structural variation using next-generation, short-ins...

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Autores principales: Chen, Ken, Wallis, John W., McLellan, Michael D., Larson, David E., Kalicki, Joelle M., Pohl, Craig S., McGrath, Sean D., Wendl, Michael C., Zhang, Qunyuan, Locke, Devin P., Shi, Xiaoqi, Fulton, Robert S., Ley, Timothy J., Wilson, Richard K., Ding, Li, Mardis, Elaine R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3661775/
https://www.ncbi.nlm.nih.gov/pubmed/19668202
http://dx.doi.org/10.1038/nmeth.1363
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author Chen, Ken
Wallis, John W.
McLellan, Michael D.
Larson, David E.
Kalicki, Joelle M.
Pohl, Craig S.
McGrath, Sean D.
Wendl, Michael C.
Zhang, Qunyuan
Locke, Devin P.
Shi, Xiaoqi
Fulton, Robert S.
Ley, Timothy J.
Wilson, Richard K.
Ding, Li
Mardis, Elaine R.
author_facet Chen, Ken
Wallis, John W.
McLellan, Michael D.
Larson, David E.
Kalicki, Joelle M.
Pohl, Craig S.
McGrath, Sean D.
Wendl, Michael C.
Zhang, Qunyuan
Locke, Devin P.
Shi, Xiaoqi
Fulton, Robert S.
Ley, Timothy J.
Wilson, Richard K.
Ding, Li
Mardis, Elaine R.
author_sort Chen, Ken
collection PubMed
description Detection and characterization of genomic structural variation are important for understanding the landscape of genetic variation in human populations and in complex diseases such as cancer. Recent studies demonstrate the feasibility of detecting structural variation using next-generation, short-insert, paired-end sequencing reads. However, the utility of these reads is not entirely clear, nor are the analysis methods under which accurate detection can be achieved. The algorithm BreakDancer predicts a wide variety of structural variants including indels, inversions, and translocations. We examined BreakDancer's performance in simulation, comparison with other methods, analysis of an acute myeloid leukemia sample, and the 1,000 Genomes trio individuals. We found that it substantially improved the detection of small and intermediate size indels from 10 bp to 1 Mbp that are difficult to detect via a single conventional approach.
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spelling pubmed-36617752013-05-22 BreakDancer: An algorithm for high resolution mapping of genomic structural variation Chen, Ken Wallis, John W. McLellan, Michael D. Larson, David E. Kalicki, Joelle M. Pohl, Craig S. McGrath, Sean D. Wendl, Michael C. Zhang, Qunyuan Locke, Devin P. Shi, Xiaoqi Fulton, Robert S. Ley, Timothy J. Wilson, Richard K. Ding, Li Mardis, Elaine R. Nat Methods Article Detection and characterization of genomic structural variation are important for understanding the landscape of genetic variation in human populations and in complex diseases such as cancer. Recent studies demonstrate the feasibility of detecting structural variation using next-generation, short-insert, paired-end sequencing reads. However, the utility of these reads is not entirely clear, nor are the analysis methods under which accurate detection can be achieved. The algorithm BreakDancer predicts a wide variety of structural variants including indels, inversions, and translocations. We examined BreakDancer's performance in simulation, comparison with other methods, analysis of an acute myeloid leukemia sample, and the 1,000 Genomes trio individuals. We found that it substantially improved the detection of small and intermediate size indels from 10 bp to 1 Mbp that are difficult to detect via a single conventional approach. 2009-08-09 2009-09 /pmc/articles/PMC3661775/ /pubmed/19668202 http://dx.doi.org/10.1038/nmeth.1363 Text en http://www.nature.com/authors/editorial_policies/license.html#terms Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms
spellingShingle Article
Chen, Ken
Wallis, John W.
McLellan, Michael D.
Larson, David E.
Kalicki, Joelle M.
Pohl, Craig S.
McGrath, Sean D.
Wendl, Michael C.
Zhang, Qunyuan
Locke, Devin P.
Shi, Xiaoqi
Fulton, Robert S.
Ley, Timothy J.
Wilson, Richard K.
Ding, Li
Mardis, Elaine R.
BreakDancer: An algorithm for high resolution mapping of genomic structural variation
title BreakDancer: An algorithm for high resolution mapping of genomic structural variation
title_full BreakDancer: An algorithm for high resolution mapping of genomic structural variation
title_fullStr BreakDancer: An algorithm for high resolution mapping of genomic structural variation
title_full_unstemmed BreakDancer: An algorithm for high resolution mapping of genomic structural variation
title_short BreakDancer: An algorithm for high resolution mapping of genomic structural variation
title_sort breakdancer: an algorithm for high resolution mapping of genomic structural variation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3661775/
https://www.ncbi.nlm.nih.gov/pubmed/19668202
http://dx.doi.org/10.1038/nmeth.1363
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