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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...

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Detalles Bibliográficos
Autores principales: Hauswedell, Hannes, Singer, Jochen, Reinert, Knut
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
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
Descripción
Sumario: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.