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Title: Improved assemblies using a source-agnostic pipeline for MetaGenomic Assembly by Merging (MeGAMerge) of contigs

Assembly of metagenomic samples is a very complex process, with algorithms designed to address sequencing platform-specific issues, (read length, data volume, and/or community complexity), while also faced with genomes that differ greatly in nucleotide compositional biases and in abundance. To address these issues, we have developed a post-assembly process: MetaGenomic Assembly by Merging (MeGAMerge). We compare this process to the performance of several assemblers, using both real, and in-silico generated samples of different community composition and complexity. MeGAMerge consistently outperforms individual assembly methods, producing larger contigs with an increased number of predicted genes, without replication of data. MeGAMerge contigs are supported by read mapping and contig alignment data, when using synthetically-derived and real metagenomic data, as well as by gene prediction analyses and similarity searches. Ultimately, MeGAMerge is a flexible method that generates improved metagenome assemblies, with the ability to accommodate upcoming sequencing platforms, as well as present and future assembly algorithms.
 [1] ;  [1] ;  [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States); USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States)
Publication Date:
OSTI Identifier:
Grant/Contract Number:
AC02-05CH11231; HSHQDC08X00790; B104153I; B084531I
Accepted Manuscript
Journal Name:
Scientific Reports
Additional Journal Information:
Journal Volume: 4; Journal ID: ISSN 2045-2322
Nature Publishing Group
Research Org:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Org:
USDOE Office of Science (SC); U.S. Department of Homeland Security
Country of Publication:
United States
59 BASIC BIOLOGICAL SCIENCES; 97 MATHEMATICS AND COMPUTING genome assembly algorithms; genomics; metagenomics; next-generation sequencing