MG-Digger: An Automated Pipeline to Search for Giant Virus-Related Sequences in Metagenomes.

ABSTRACT: The number of metagenomic studies conducted each year is growing dramatically. Storage and analysis of such big data is difficult and time-consuming. Interestingly, analysis shows that environmental and human metagenomes include a significant amount of non-annotated sequences, representing a 'dark matter.' We established a bioinformatics pipeline that automatically detects metagenome reads matching query sequences from a given set and applied this tool to the detection of sequences matching large and giant DNA viral members of the proposed order Megavirales or virophages. A total of 1,045 environmental and human metagenomes (≈ 1 Terabase) were collected, processed, and stored on our bioinformatics server. In addition, nucleotide and protein sequences from 93 Megavirales representatives, in

SUBMITTER: Verneau J 

PROVIDER: S-EPMC4814491 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature