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2. *Multiple-response items between clusters were tested with two-proportion z-test.
Differences in overall significance of chromatin state changes between clusters were tested by a non-parametric one-sided Wilcoxon test since distribution of the P-values was skewed.
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The statistical differences between the clusters were tested using a one-way ANOVA followed by Tukey post-hoc test.
Differences between the sample clusters were tested using the Chi-squared test, and genes differentially expressed between the tumors of responder and nonresponder patients were assessed using the t-test followed by Benjamini and Hochberg correction.
Differences between groups and clusters were tested using the Pearson χ test for categorical data.
Differences in co-activation patterns between the respective clusters were tested by performing MACM separately on the experiments associated with either cluster and computing the voxel-wise difference between the ensuing ALE maps.
Given the predominantly pericentromeric location of rDNA clusters and the co-occurrence of centromeres and clusters at breakpoints, the evolutionary association between centromeres and rDNA clusters was tested.
Between one and five clusters (K) were tested assuming admixture between populations and linkage equilibrium between loci.
Statistical associations between loci were tested within each cluster through Fisher's exact tests using Genepop version 3.3 [ 37].
Baseline characteristics with a skewed distribution were calculated as median (interquartile range) within each cluster, and differences between clusters were analyzed by Kruskal Wallis test.
Differences between clusters were determined by Kruskal-wallis test for continuous variables and chi-square test for categorical variables.
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