The Use of Informativity in the Development of Robust Metaviromics-based Examinations

13. CC-BY-NC 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not. Abstract 14 The field of metagenomics has developed insight into many of the complex microbial communities 15 responsible for maintaining life on this planet. Sequencing efforts often uncover novel genetic content; 16 this is most evident for viral metagenomics, in which upwards of 90% of all sequences demonstrate no 17 sequence similarity with present databases. For the small fraction which can be identified, the top BLAST 18 hit is often posited as being representative of the phage taxon. However, as previous research has 19 shown, the top BLAST hit is sometimes misinterpreted. Furthermore, the appearance of a particular 20 gene homolog is frequently not representative of the presence of the particular taxon in question. To 21 circumvent these limitations, we have developed a new method for the analysis of metaviromic 22 datasets. BLAST hits are weighted, integrating the sequence identity and length of alignments as well as 23 a phylogenetic signal. A genic rather than genomic approach is presented in which each gene is 24 evaluated with respect to its information content. Through this quantifiable metric, predictions of viral 25 community structure can be made with greater confidence. As a proof-of-concept, the approach 26 presented here was implemented and applied to seven metaviromes. While providing a more robust 27 means of evaluating metaviromic data, the tool is versatile and can easily be customized to 28 investigations of any environment or biome. 29 30 31. CC-BY-NC 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not .