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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.
Recombination in the dataset was tested by using a Genetic Algorithm for Recombination Detection (GARD) [15].
The plasma-and-urine subproteome dataset was tested against the input-plasma proteome dataset (the reference dataset) for the enrichment analysis.
The difference in likelihood scores between these runs comprised the null distribution against which the likelihood value from the harpy eagle dataset was tested.
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Then the input dataset is tested and trained.
The different acceptable SH coefficients from the whole dataset were tested individually.
During Jackknife Cross-Validation, each ORF in the dataset is tested in turn by the translation rate predictor, which is trained by the other ORFs in the data set.
Alternative topologies for the concatenated dataset were tested using the Approximately Unbiased (AU) test [ 31].
Assigned genes to each dataset were tested for enriched GO slim term annotations.
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