While our work primarily focused on analyzing inter-protein correlated mutations in IAV sub-systems, we have also created intra-protein correlated mutation graphs to understand differences and gain relevant insights. These graphs are created based on computation of MIC correlations between residues within a protein in Influenza. Our overall methodology to analyze mutational patterns using a network analysis approach is elucidated here.
In this blog, we have included results for intra-protein correlated mutations within residues in proteins in IAV sub-systems for our 6 primary datasets.
These figures depict the node and edge counts for each protein. These figures suggest significant differences between the 6 datasets. There are significantly higher number of nodes and edges in the ‘NA’ network of Avian_H5. The edge count plot also suggests that the intra-protein correlated mutations graphs for Human H3N2, Swine H3N2 and H7N9 are very sparse with a significantly lower edge to node ratio.
