Computational Virology:
We are utilizing and developing computational pipelines for the analysis of NGS data of viral samples.
“ViReMa” (Viral Recombination Mapper) is a versatile and flexible computational pipeline for the discovery of viral recombination events in NGS datasets that employs a novel ‘moving-seed’ approach for sequence alignment (Routh et al 2014 NAR). In addition to improved speed and sensitivity over other algorithms using canonical ‘fixed-seed’ approaches, ViReMa detects substitutions and non-reference insertions, multiple recombination events and virus to host recombination. This flexibility has proven critical for mapping viral recombinations as these events rarely conform to predefined (or known) rules. Using ViReMa, we have found that after resistance to protease inhibitors had developed in HIV positive patients, virus populations haboured short duplications proximal to the proteolysis sites in the GAG protein. Sourceforge-link
Routh A.*, Johnson J.E.
Nucleic Acids Research, 2014 Jan 42(2):e11
Discovery of functional genomic motif in viruses with ViReMa – a Virus Recombination Mapper for analysis of Next-Generation Sequencing data
“CoVaMa” (Co-Variation Mapper) takes NGS alignment data and populates large matrices of contingency tables that correspond to every possible pairwise interaction of nucleotides in the viral genome or amino acids in the chosen open reading frame (Routh et al. 2015 Methods). These tables are then analysed using classical linkage disequilibrium to detect and report evidence of epistasis. CoVaMa found epistatically linked loci in FHV genomic RNA grown under controlled cell culture conditions as well as correlated amino acid substitutions in the protease genes among a large cohort of HIV infected patients undergoing anti-retroviral therapy. Sourceforge-link
Routh A.*, Chang M.W., Okulicz J.F., Johnson J.E., Torbett B.E.*
Methods, 2015 Dec 91:40-47
CoVaMa: Co-Variation Mapper for disequilibrium analysis of mutant loci in viral populations using next-generation sequence data.