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Predicted interactions within this dataset were tested by co-immunoprecipitation, resulting in a high rate of validation, suggesting the high quality of networks produced.
The different acceptable SH coefficients from the whole dataset were tested individually.
Assigned genes to each dataset were tested for enriched GO slim term annotations.
In this stage, only the 1,941 SNPs common to both dataset were tested.
Alternative topologies for the concatenated dataset were tested using the Approximately Unbiased (AU) test [ 31].
The 59 codons usage values for individual genome in each DENV dataset were tested for phylogenetic dependence.
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The robustness of the dataset was tested by eliminating incrementally higher numbers of fast-evolving sites using six levels of stringency in Gblocks 091b56.
Then the input dataset is tested and trained.
Also, the dataset was tested for asymmetry using skewness.
Thus, each sample in the dataset was tested once, using a model that was not fitted with that sample.
The 17 predictor dataset was tested using a pairwise Spearman correlation analysis, and all predictors with Spearman correlation ≤ 0.7 were selected, retaining those predictors with the greatest ecological relevance for the species.
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