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To assess the statistical significance of the difference in datasets, the Student t-test was performed using the significance level of 0.05.
The difference in datasets also helps to prevent over-optimization of heuristic parameters.
Therefore, though the dataset varies across the 72 strategies, other factors beyond the difference in datasets are contributing substantially to the difference in results.
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Due to the difference in dataset setting, we cannot arbitrarily compare our results with the prior research results.
The possible explanation for this may lay in the difference in dataset selection.
However, the two orders of magnitude difference in dataset size (462 genes versus 10 proteins) made the standard correlation methods inapplicable.
The difference in dataset sample size is accounted for by the p-value assigned to the correlation coefficients, as smaller datasets would require a higher correlation coefficient between a pair of genes to match the p-value of lower coefficients in big datasets.
Our QC pipeline was able to overcome significant biases in the LRR data, correcting for intensity differences in datasets originating from separate collections and sample types that differed systematically between phenotypes.
Such cases include those where the coordinate differences in datasets are significant, where the shapes of the same objects are dissimilar, or even where the shapes are too similar for different objects.
ANOSIM results identified no significant reef treatment effects and also suffered from design constraints and an inability to generate enough permutations to test for significant differences in datasets with relatively small sample sizes.
Despite the differences in datasets and classifiers, the two methods largely agree on the taxonomic affiliations of the sequence data.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com