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We used Spearman's correlation coefficient to identify correlation of each transcript with SI.
P-values <0.2 were further examined by Spearman's correlation coefficient to identify confounding factors.
Correlations between explanatory variables were also assessed using Pearson's correlation coefficient to identify groups of variables tending to capture the same phenomena.
We used Spearman's rank correlation coefficient to identify possible associations between both the FA values of each ROI and the clinical symptoms (MMSE scores, FAB scores, TUG scores, H&Y stage, and UPDRS motor scores).
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The number of coefficients to identify is reduced and their modeling capacity is preserved in real problems where the number of interacting elements is limited.
Our main purpose was to compare the decay in similarity through time between observed and neutral data using different dissimilarity measures, rather than testing for the significance of Mantel's coefficients to identify particular temporal structures.
To identify conserved expression signatures underling the above patterns, we used hierarchical clustering with pair-wise correlation coefficients to identify co-expressed genes for each species.
The correlation of sucrose levels with a large proportion of previously identified sucrose-responsive gene transcripts reinforces the validity of the use of correlation coefficients to identify interesting relationships.
With these parameters, using the method of taking the D loci with the highest selection coefficients to identify drivers, the linked method showed a large improvement over the unlinked method in its ability to discern driver from passenger loci.
Since WGCNA uses Pearson correlation coefficients to identify co-expressed modules, it could not group genes that have similar patterns of transcript abundance but different levels into separate modules.
Since the expression coefficients can be subjected to statistical tests to indicate the physiological interpretation of the component we used unpaired, two-tailed t-tests on these coefficients to identify PCs that were differentially expressed between healthy controls and PD patients (significance level p < 0.05).
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