Vorpal: A novel RNA virus feature-extraction algorithm demonstrated through interpretable genotype-to-phenotype linear models

Phillip Davis; John Bagnoli; David Yarmosh; Alan Shteyman; Lance Presser; Sharon Altmann; Shelton Bradrick; Joseph A. Russell

words" methods with the complications presented by the intrinsic variance of RNA virus 24 space, a method to resolve the fragility of extracted K-mers in a way that faithfully reflects 25 an underlying biological phenomenon was devised. Our algorithm, Vorpal, allows the 26 construction of interpretable linear models with clustered, representative 'degenerate' K-27 mers as the input vector and, through regularization, sparse predictors of binary 28 phenotypes as the output. Here, we demonstrate the utility of Vorpal by identifying 29 nucleotide-level genomic motif predictors for binary phenotypes in three separate RNA 30 virus clades; human pathogen vs. non-human pathogen in Orthocoronavirinae, 31 hemorrhagic fever causing vs. non-hemorrhagic fever causing in Ebolavirus, and human-32 host vs. non-human host in Influenza A. The capacity of this approach for in silico 33