Viral Taxonomy Derived From Evolutionary Genome Relationships

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Abstract/Contents

Abstract: We describe a new genome alignment-based model for classification of viruses based on evolutionary genetic relationships. This approach uses information theory and a physical model to determine the information shared by the genes in two genomes. Pairwise comparisons of genes from the viruses are created from alignments using NCBI BLAST, and their match scores are combined to produce a metric between genomes, which is in turn used to determine a global classification using the 5,817 viruses on RefSeq. In cases where there is no measurable alignment between any genes, the method falls back to a coarser measure of genome relationship: the mutual information of k-mer frequency. This results in a principled model which depends only on the genome sequence, which captures many interesting relationships between viral families, and which creates clusters which correlate well with both the Baltimore and ICTV classifications. The incremental computational cost of classifying a novel virus is low and therefore newly discovered viruses can be quickly identified and classified.

Type of resource	text
Date created	May 15, 2018

Author	Dougan, Tyler
Primary advisor	Quake, Stephen
Advisor	Schleier-Smith, Monika
Degree granting institution	Stanford University, Department of Physics

Subject	Virus Taxonomy
Genre	Thesis

Related Publication	Tyler Dougan and Stephen R. Quake. 2018. Viral Taxonomy Derived From Evolutionary Genome Relationships. bioRxiv doi: https://doi.org/10.1101/322511
Location	https://purl.stanford.edu/kk817bd4850

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License: This work is licensed under a Creative Commons Attribution Non Commercial No Derivatives 3.0 Unported license (CC BY-NC-ND).

Preferred Citation: Dougan, Tyler and Quake, Stephen. (2018). Viral Taxonomy Derived From Evolutionary Genome Relationships. Stanford Digital Repository. Available at: https://purl.stanford.edu/kk817bd4850

Undergraduate Theses, Department of Physics

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