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Analyses were repeated three times to check for likelihood and parameter mixing and congruence.
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We determined the burn-in period by checking for likelihood stability.
We conducted similar robustness checks for the likelihood of adverse events variables (both for hospital and non-hospital-related harm) and the results of our analysis are presented in Additional file 3: Panels 2 and 3.
We ran Structure for K ranging from 1 to 13 and we performed at least six repetitions to check for convergence of likelihood values for each value of K. Convergence of the MCMC could not be achieved for K values higher than 13.
Tracer [ 39] was used to check for stabilization of overall likelihood within and convergence between runs.
Tracer 1.5 [ 40] was used to check for stabilization of overall likelihood within and convergence between runs.
We ran STRUCTURE for K clusters ranging from 1 to 8, and performed five repetitions to check for the convergence of likelihood values for each value of K. Evanno's method, ΔK, was used to best estimate K [ 36, 37].
Tracer 1.4 [ 99] was used to check for convergence of the model likelihood and parameters between each run.
The use of duplicate assays allowed an internal check for data quality, reducing the likelihood of a minority allele mistakenly being recorded.
We used the likelihood ratio test to check for model fit by dropping insignificant variables first and refit the model until we got the best fit.
A summary of the descriptive statistics including the locus-wise heterozygosity (h), probability of homozygosity (P), Exact test (ET) and Likelihood ratio test (LR) (performed to check for departure from Hardy-Weinberg equilibrium) values are shown in Table 1.
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