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A poor man’s BLASTX—high-throughput metagenomic protein database search using PAUDA
Author(s) -
Daniel H. Huson,
Chao Xie
Publication year - 2013
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btt254
Subject(s) - metagenomics , context (archaeology) , kegg , cluster analysis , computer science , software , data mining , computational biology , biology , gene , genetics , artificial intelligence , operating system , gene ontology , paleontology , gene expression
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.

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