Viral Voyager



Viral Voyager is a website that shows a large-scale mapping of analysed metaviriome data collected from the Tara Oceans Project.

The Tara Oceans Project collected water samples data worldwide for shotgun metagenomic sequencing, and this data was then mapped to metabolomic pathways.

Users can play, explore, and download the genome dataset to gain understanding into the microscopic life living in Earths oceans. Explore the interactive map of samples, some example summaries, or download the data!

299 size-fractioned water samples were collected. Viral and bacterial DNA sequences were then aligned with BLAST and and associated to a biological pathway that is likely to be regulated by each viral DNA sequence using MetaPathways v2.5, Pathway Tools and the MetaCyc hierarchy. This dataset currently has 1050 different pathways that fall into 61 subcategories, which can be further organized into nine categories:

  1. Biosynthesis
  2. Energy-Metabolism
  3. Degradation
  4. Detoxification
  5. Macromolecule Modification
  6. Activation-Inactivation-Interconversion
  7. Generation of Precursor Metabolites and Energy
  8. Super-Pathways
  9. Metabolic-Clusters

Please contact us if you have any questions.

Steven Hallam email: shallam@mail.ubc.ca phone: 604-827-3420.

Hackseq team leader: Arjun Baghela email: arjunsbaghela@gmail.com

Hallam Lab on Twitter

Ecoscope UBC

Hackseq 2018

Map of Viral Metabolic Pathways

Controls

Sample Information

Future Directions



In the future, Virus Voyager will update and integrate data sets and become the platform for global ocean biomes for both researchers and general audiences. These datasets can be found on MGnify’s website: https://www.ebi.ac.uk/metagenomics/studies/ERP001736 https://www.ebi.ac.uk/metagenomics/api/v1/studies/MGYS00000410 https://www.ebi.ac.uk/metagenomics/api/v1/analyses https://www.ebi.ac.uk/metagenomics/studies/MGYS00001482 We will also explore more interactive and user friendly analytical functions utilizing the existing vast Tara ocean virus data set. We will look to complete a well documented manual script.

Meet the Team

Arjun Baghela
@arjunsbaghela
abaghela

B. Ogan Mancarci

@oganm
oganm
Dan Dan Fornika
dfornika
Kristen Gray
@agrayowl
klgray25

Olga Solodova

solodova
Javier J. Castillo Arnemann
yavyx
Jasmine Lai
laijasmine
Tony Shen
tsa87
Heather Van Tassel
heathervant

Amy Zheng
awlzhng
Kevin Lam
KlamChowder1