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PALADIN: protein alignment for functional profiling whole metagenome shotgun data
MOTIVATION: Whole metagenome shotgun sequencing is a powerful approach for assaying the functional potential of microbial communities. We currently lack tools that efficiently and accurately align DNA reads against protein references, the technique necessary for constructing a functional profile. He...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5423455/ https://www.ncbi.nlm.nih.gov/pubmed/28158639 http://dx.doi.org/10.1093/bioinformatics/btx021 |
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author | Westbrook, Anthony Ramsdell, Jordan Schuelke, Taruna Normington, Louisa Bergeron, R Daniel Thomas, W Kelley MacManes, Matthew D |
author_facet | Westbrook, Anthony Ramsdell, Jordan Schuelke, Taruna Normington, Louisa Bergeron, R Daniel Thomas, W Kelley MacManes, Matthew D |
author_sort | Westbrook, Anthony |
collection | PubMed |
description | MOTIVATION: Whole metagenome shotgun sequencing is a powerful approach for assaying the functional potential of microbial communities. We currently lack tools that efficiently and accurately align DNA reads against protein references, the technique necessary for constructing a functional profile. Here, we present PALADIN—a novel modification of the Burrows-Wheeler Aligner that provides accurate alignment, robust reporting capabilities and orders-of-magnitude improved efficiency by directly mapping in protein space. RESULTS: We compared the accuracy and efficiency of PALADIN against existing tools that employ nucleotide or protein alignment algorithms. Using simulated reads, PALADIN consistently outperformed the popular DNA read mappers BWA and NovoAlign in detected proteins, percentage of reads mapped and ontological similarity. We also compared PALADIN against four existing protein alignment tools: BLASTX, RAPSearch2, DIAMOND and Lambda, using empirically obtained reads. PALADIN yielded results seven times faster than the best performing alternative, DIAMOND and nearly 8000 times faster than BLASTX. PALADIN's accuracy was comparable to all tested solutions. AVAILABILITY AND IMPLEMENTATION: PALADIN was implemented in C, and its source code and documentation are available at https://github.com/twestbrookunh/paladin SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-5423455 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-54234552017-05-11 PALADIN: protein alignment for functional profiling whole metagenome shotgun data Westbrook, Anthony Ramsdell, Jordan Schuelke, Taruna Normington, Louisa Bergeron, R Daniel Thomas, W Kelley MacManes, Matthew D Bioinformatics Original Papers MOTIVATION: Whole metagenome shotgun sequencing is a powerful approach for assaying the functional potential of microbial communities. We currently lack tools that efficiently and accurately align DNA reads against protein references, the technique necessary for constructing a functional profile. Here, we present PALADIN—a novel modification of the Burrows-Wheeler Aligner that provides accurate alignment, robust reporting capabilities and orders-of-magnitude improved efficiency by directly mapping in protein space. RESULTS: We compared the accuracy and efficiency of PALADIN against existing tools that employ nucleotide or protein alignment algorithms. Using simulated reads, PALADIN consistently outperformed the popular DNA read mappers BWA and NovoAlign in detected proteins, percentage of reads mapped and ontological similarity. We also compared PALADIN against four existing protein alignment tools: BLASTX, RAPSearch2, DIAMOND and Lambda, using empirically obtained reads. PALADIN yielded results seven times faster than the best performing alternative, DIAMOND and nearly 8000 times faster than BLASTX. PALADIN's accuracy was comparable to all tested solutions. AVAILABILITY AND IMPLEMENTATION: PALADIN was implemented in C, and its source code and documentation are available at https://github.com/twestbrookunh/paladin SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2017-05-15 2017-01-31 /pmc/articles/PMC5423455/ /pubmed/28158639 http://dx.doi.org/10.1093/bioinformatics/btx021 Text en © The Author 2017. 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 | Original Papers Westbrook, Anthony Ramsdell, Jordan Schuelke, Taruna Normington, Louisa Bergeron, R Daniel Thomas, W Kelley MacManes, Matthew D PALADIN: protein alignment for functional profiling whole metagenome shotgun data |
title | PALADIN: protein alignment for functional profiling whole metagenome shotgun data |
title_full | PALADIN: protein alignment for functional profiling whole metagenome shotgun data |
title_fullStr | PALADIN: protein alignment for functional profiling whole metagenome shotgun data |
title_full_unstemmed | PALADIN: protein alignment for functional profiling whole metagenome shotgun data |
title_short | PALADIN: protein alignment for functional profiling whole metagenome shotgun data |
title_sort | paladin: protein alignment for functional profiling whole metagenome shotgun data |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5423455/ https://www.ncbi.nlm.nih.gov/pubmed/28158639 http://dx.doi.org/10.1093/bioinformatics/btx021 |
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