Cargando…
ABRA: improved coding indel detection via assembly-based realignment
Motivation: Variant detection from next-generation sequencing (NGS) data is an increasingly vital aspect of disease diagnosis, treatment and research. Commonly used NGS-variant analysis tools generally rely on accurately mapped short reads to identify somatic variants and germ-line genotypes. Existi...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4173014/ https://www.ncbi.nlm.nih.gov/pubmed/24907369 http://dx.doi.org/10.1093/bioinformatics/btu376 |
_version_ | 1782336121524453376 |
---|---|
author | Mose, Lisle E. Wilkerson, Matthew D. Hayes, D. Neil Perou, Charles M. Parker, Joel S. |
author_facet | Mose, Lisle E. Wilkerson, Matthew D. Hayes, D. Neil Perou, Charles M. Parker, Joel S. |
author_sort | Mose, Lisle E. |
collection | PubMed |
description | Motivation: Variant detection from next-generation sequencing (NGS) data is an increasingly vital aspect of disease diagnosis, treatment and research. Commonly used NGS-variant analysis tools generally rely on accurately mapped short reads to identify somatic variants and germ-line genotypes. Existing NGS read mappers have difficulty accurately mapping short reads containing complex variation (i.e. more than a single base change), thus making identification of such variants difficult or impossible. Insertions and deletions (indels) in particular have been an area of great difficulty. Indels are frequent and can have substantial impact on function, which makes their detection all the more imperative. Results: We present ABRA, an assembly-based realigner, which uses an efficient and flexible localized de novo assembly followed by global realignment to more accurately remap reads. This results in enhanced performance for indel detection as well as improved accuracy in variant allele frequency estimation. Availability and implementation: ABRA is implemented in a combination of Java and C/C++ and is freely available for download at https://github.com/mozack/abra. Contact: lmose@unc.edu; parkerjs@email.unc.edu Supplementary information: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-4173014 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-41730142014-09-25 ABRA: improved coding indel detection via assembly-based realignment Mose, Lisle E. Wilkerson, Matthew D. Hayes, D. Neil Perou, Charles M. Parker, Joel S. Bioinformatics Applications Notes Motivation: Variant detection from next-generation sequencing (NGS) data is an increasingly vital aspect of disease diagnosis, treatment and research. Commonly used NGS-variant analysis tools generally rely on accurately mapped short reads to identify somatic variants and germ-line genotypes. Existing NGS read mappers have difficulty accurately mapping short reads containing complex variation (i.e. more than a single base change), thus making identification of such variants difficult or impossible. Insertions and deletions (indels) in particular have been an area of great difficulty. Indels are frequent and can have substantial impact on function, which makes their detection all the more imperative. Results: We present ABRA, an assembly-based realigner, which uses an efficient and flexible localized de novo assembly followed by global realignment to more accurately remap reads. This results in enhanced performance for indel detection as well as improved accuracy in variant allele frequency estimation. Availability and implementation: ABRA is implemented in a combination of Java and C/C++ and is freely available for download at https://github.com/mozack/abra. Contact: lmose@unc.edu; parkerjs@email.unc.edu Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2014-10 2014-06-06 /pmc/articles/PMC4173014/ /pubmed/24907369 http://dx.doi.org/10.1093/bioinformatics/btu376 Text en © The Author 2014. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Mose, Lisle E. Wilkerson, Matthew D. Hayes, D. Neil Perou, Charles M. Parker, Joel S. ABRA: improved coding indel detection via assembly-based realignment |
title | ABRA: improved coding indel detection via assembly-based realignment |
title_full | ABRA: improved coding indel detection via assembly-based realignment |
title_fullStr | ABRA: improved coding indel detection via assembly-based realignment |
title_full_unstemmed | ABRA: improved coding indel detection via assembly-based realignment |
title_short | ABRA: improved coding indel detection via assembly-based realignment |
title_sort | abra: improved coding indel detection via assembly-based realignment |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4173014/ https://www.ncbi.nlm.nih.gov/pubmed/24907369 http://dx.doi.org/10.1093/bioinformatics/btu376 |
work_keys_str_mv | AT moselislee abraimprovedcodingindeldetectionviaassemblybasedrealignment AT wilkersonmatthewd abraimprovedcodingindeldetectionviaassemblybasedrealignment AT hayesdneil abraimprovedcodingindeldetectionviaassemblybasedrealignment AT peroucharlesm abraimprovedcodingindeldetectionviaassemblybasedrealignment AT parkerjoels abraimprovedcodingindeldetectionviaassemblybasedrealignment |