Data from: Interacting networks of resistance, virulence and core machinery genes identified by genome-wide epistasis analysis

Marcin J. Skwark, Nicholas J. Croucher, Santeri Puranen, Claire Chewapreecha, Maiju Pesonen, Ying Ying Xu, Paul Turner, Simon R. Harris, Stephen B. Beres, James M. Musser, Julian Parkhill, Stephen D. Bentley, Erik Aurell & Jukka Corander
Recent advances in the scale and diversity of population genomic datasets for bacteria now provide the potential for genome-wide patterns of co-evolution to be studied at the resolution of individual bases. Here we describe a new statistical method, genomeDCA, which uses recent advances in computational structural biology to identify the polymorphic loci under the strongest co-evolutionary pressures. We apply genomeDCA to two large population data sets representing the major human pathogens Streptococcus pneumoniae (pneumococcus) and...
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