Supporting data for "drVM: a new tool for efficient genome assembly of known eukaryotic viruses from metagenomes"

Dataset type: Genomic, Software
Data released on January 16, 2017

Lin H; Liao Y (2017): Supporting data for "drVM: a new tool for efficient genome assembly of known eukaryotic viruses from metagenomes" GigaScience Database. http://dx.doi.org/10.5524/100272

DOI10.5524/100272

Virus discovery using high-throughput next-generation sequencing (NGS) has become more commonplace. However, although analysis of deep NGS data allows us to identity potential pathogens, the entire analytical procedure requires competency in the bioinformatics domain, which includes implementing proper software packages and preparing prerequisite databases. Simple and user-friendly bioinformatics pipelines are urgently required to obtain complete viral genome sequences from metagenomic data.
Here we present a pipeline, drVM (detect and reconstruct known viral genomes from metagenomes), for rapid viral read identification, genus-level read partition, read normalization, de novo assembly, sequence annotation and coverage profiling. The first two procedures and sequence annotation rely on known viral genomes as a reference database. We also present the validation results of the analysis of over 300 previously published sequencing runs, to provide complete viral genome assemblies for a variety of virus types including DNA viruses, RNA viruses and retroviruses.
drVM is available for free download here and is also assembled as a Docker container, an Amazon machine image and a virtual machine to facilitate seamless deployment. GigaDB is hosting the version of the software as reviewed in the associated article, please refer to the sourceforge site for the most recent updates to the software.

Additional details

Read the peer-reviewed publication(s):

Lin, H.-H., & Liao, Y.-C. (2017). drVM: a new tool for efficient genome assembly of known eukaryotic viruses from metagenomes. GigaScience, 6(2). doi:10.1093/gigascience/gix003

Additional information:

https://hub.docker.com/r/990210oliver/drvm/

https://sourceforge.net/projects/sb2nhri/files/drVM/





File NameSample IDData TypeFile FormatSizeRelease Date 
Mixed archivearchive223.67 MB2017-01-12
Mixed archivearchive1.19 GB2017-01-12
Mixed archivearchive36.44 MB2017-01-12
Mixed archiveTAR6.65 MB2017-01-12
Mixed archivearchive2.55 GB2017-01-12
ArticlePDF2.7 MB2017-01-12
TextTEXT1.86 KB2017-01-12
Mixed archiveTAR1.55 MB2017-01-12
Mixed archivearchive1.36 GB2017-01-12
Mixed archiveTAR419.99 MB2017-01-12
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Funding body Awardee Award ID Comments
National Health Research Institute Taiwan PH-105-PP-05
Ministry of Science and Technology Taiwan MOST-104-2320-B-400-021-MY2
Date Action
January 16, 2017 Dataset publish
March 6, 2017 Manuscript Link added : 10.1093/gigascience/gix003