@misc{meng_endo_blanc-mathieu_hernandez-velazquez_kaneko_ogata_2020, 
  title={Quantitative assessment of NCLDV-host interactions predicted by co-occurrence analyses}, 
  DOI={10.1101/2020.10.16.342030}, 
  abstractNote={<jats:p>Nucleocytoplasmic DNA viruses (NCLDVs) are highly diverse and abundant in marine environments. However, knowledge of their hosts is limited because only a few NCLDVs have been isolated. By taking advantage of the rapidly increasing metagenomic data, in silico host prediction approaches are expected to fill this gap between known virus-host relationships and the true but largely unknown amount of NCLDVs. In this study, we built co-occurrence networks between NCLDVs and eukaryotes using the Tara Oceans metagenome and metabarcoding datasets to predict virus-host interactions. Using the positive likelihood ratio to assess the performance of host prediction for NCLDVs, we demonstrated that co-occurrence approaches can increase the odds of predicting true positive relationships four-fold compared with random host predictions in the high-weight region (weight &gt; 0.4). To refine the host predictions from high-dimensional co-occurrence networks, we employed a recently proposed phylogeny-based method, Taxon Interaction Mapper, and showed that Taxon Interaction Mapper further improved the prediction performance eight-fold using weight cut-off filtration (&gt; 0.4). Finally, we inferred virophage and NCLDV networks that further corroborated that co-occurrence approaches are effective for predicting NCLDV hosts in marine environments.</jats:p>}, 
  publisher={Cold Spring Harbor Laboratory}, 
  author={Meng, Lingjie and Endo, Hisashi and Blanc-Mathieu, Romain and Hernandez-Velazquez, Rodrigo and Kaneko, Hiroto and Ogata, Hiroyuki}, 
  year={2020}, 
  month={Oct}
  }