A poor man’s BLASTX—high-throughput metagenomic protein database search using PAUDA

Summary: In the context of metagenomics, we introduce a new approach to protein database search called PAUDA, which runs ∼10 000 times faster than BLASTX, while achieving about one-third of the assignment rate of reads to KEGG orthology groups, and producing gene and taxon abundance profiles that ar...

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Bibliographic Details
Published in:Bioinformatics
Main Authors: Huson, Daniel H., Xie, Chao
Format: Text
Language:English
Published: Oxford University Press 2014
Subjects:
Online Access:http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3866550
http://www.ncbi.nlm.nih.gov/pubmed/23658416
https://doi.org/10.1093/bioinformatics/btt254
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Summary:Summary: In the context of metagenomics, we introduce a new approach to protein database search called PAUDA, which runs ∼10 000 times faster than BLASTX, while achieving about one-third of the assignment rate of reads to KEGG orthology groups, and producing gene and taxon abundance profiles that are highly correlated to those obtained with BLASTX. PAUDA requires <80 CPU hours to analyze a dataset of 246 million Illumina DNA reads from permafrost soil for which a previous BLASTX analysis (on a subset of 176 million reads) reportedly required 800 000 CPU hours, leading to the same clustering of samples by functional profiles.