UNLABELLED: The determination of protein sequences from a metagenomic dataset enables the study of metabolism and functional roles of the organisms that are present in the sampled microbial community. We had previously introduced algorithm and software for the accurate reconstruction of protein sequences from short peptides identified on nucleotide reads in a metagenomic dataset. Here, we present significant computational improvements to the short peptide assembly algorithm that make it practical to reconstruct proteins from large metagenomic datasets containing several hundred million reads, while maintaining accuracy. The improved computational efficiency is achieved using a suffix array data structure that allows for fast querying during the assembly process, and a significant redesign of assembly steps that enables multi-threaded execution. AVAILABILITY AND IMPLEMENTATION: The program is available under the GPLv3 license from sourceforge.net/projects/spa-assembler.
UNLABELLED: The determination of protein sequences from a metagenomic dataset enables the study of metabolism and functional roles of the organisms that are present in the sampled microbial community. We had previously introduced algorithm and software for the accurate reconstruction of protein sequences from short peptides identified on nucleotide reads in a metagenomic dataset. Here, we present significant computational improvements to the short peptide assembly algorithm that make it practical to reconstruct proteins from large metagenomic datasets containing several hundred million reads, while maintaining accuracy. The improved computational efficiency is achieved using a suffix array data structure that allows for fast querying during the assembly process, and a significant redesign of assembly steps that enables multi-threaded execution. AVAILABILITY AND IMPLEMENTATION: The program is available under the GPLv3 license from sourceforge.net/projects/spa-assembler.
Authors: Jiarong Guo; John F Quensen; Yanni Sun; Qiong Wang; C Titus Brown; James R Cole; James M Tiedje Journal: Front Genet Date: 2019-10-15 Impact factor: 4.599