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Lambda: the local aligner for massive biological data
Motivation: Next-generation sequencing technologies produce unprecedented amounts of data, leading to completely new research fields. One of these is metagenomics, the study of large-size DNA samples containing a multitude of diverse organisms. A key problem in metagenomics is to functionally and ta...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4147892/ https://www.ncbi.nlm.nih.gov/pubmed/25161219 http://dx.doi.org/10.1093/bioinformatics/btu439 |
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author | Hauswedell, Hannes Singer, Jochen Reinert, Knut |
author_facet | Hauswedell, Hannes Singer, Jochen Reinert, Knut |
author_sort | Hauswedell, Hannes |
collection | PubMed |
description | Motivation: Next-generation sequencing technologies produce unprecedented amounts of data, leading to completely new research fields. One of these is metagenomics, the study of large-size DNA samples containing a multitude of diverse organisms. A key problem in metagenomics is to functionally and taxonomically classify the sequenced DNA, to which end the well-known BLAST program is usually used. But BLAST has dramatic resource requirements at metagenomic scales of data, imposing a high financial or technical burden on the researcher. Multiple attempts have been made to overcome these limitations and present a viable alternative to BLAST. Results: In this work we present Lambda, our own alternative for BLAST in the context of sequence classification. In our tests, Lambda often outperforms the best tools at reproducing BLAST’s results and is the fastest compared with the current state of the art at comparable levels of sensitivity. Availability and implementation: Lambda was implemented in the SeqAn open-source C++ library for sequence analysis and is publicly available for download at http://www.seqan.de/projects/lambda. Contact: hannes.hauswedell@fu-berlin.de Supplementary information: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-4147892 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-41478922014-09-02 Lambda: the local aligner for massive biological data Hauswedell, Hannes Singer, Jochen Reinert, Knut Bioinformatics Eccb 2014 Proceedings Papers Committee Motivation: Next-generation sequencing technologies produce unprecedented amounts of data, leading to completely new research fields. One of these is metagenomics, the study of large-size DNA samples containing a multitude of diverse organisms. A key problem in metagenomics is to functionally and taxonomically classify the sequenced DNA, to which end the well-known BLAST program is usually used. But BLAST has dramatic resource requirements at metagenomic scales of data, imposing a high financial or technical burden on the researcher. Multiple attempts have been made to overcome these limitations and present a viable alternative to BLAST. Results: In this work we present Lambda, our own alternative for BLAST in the context of sequence classification. In our tests, Lambda often outperforms the best tools at reproducing BLAST’s results and is the fastest compared with the current state of the art at comparable levels of sensitivity. Availability and implementation: Lambda was implemented in the SeqAn open-source C++ library for sequence analysis and is publicly available for download at http://www.seqan.de/projects/lambda. Contact: hannes.hauswedell@fu-berlin.de Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2014-09-01 2014-08-22 /pmc/articles/PMC4147892/ /pubmed/25161219 http://dx.doi.org/10.1093/bioinformatics/btu439 Text en © The Author 2014. 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 non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Eccb 2014 Proceedings Papers Committee Hauswedell, Hannes Singer, Jochen Reinert, Knut Lambda: the local aligner for massive biological data |
title | Lambda: the local aligner for massive biological data |
title_full | Lambda: the local aligner for massive biological data |
title_fullStr | Lambda: the local aligner for massive biological data |
title_full_unstemmed | Lambda: the local aligner for massive biological data |
title_short | Lambda: the local aligner for massive biological data |
title_sort | lambda: the local aligner for massive biological data |
topic | Eccb 2014 Proceedings Papers Committee |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4147892/ https://www.ncbi.nlm.nih.gov/pubmed/25161219 http://dx.doi.org/10.1093/bioinformatics/btu439 |
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