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The Non-parametric ANOVA task uses the Kruskal-Wallis and Dunn's tests to identify differentially deferentially expressed genes between among two or more groups. Note that such rank-based tests are generally advised for use with larger sample sizes.
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Select Non-parametric ANOVA under the Statistical analysis section of the context-sensitive menu (Figure 1).
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For more complicated experimental designs, go back to the original count data that will be used as input and perform Rank normalization at the feature Features level (Figure 3). The resulting Normalized counts data node can then be analyzed using the Detect differential expression (ANOVA) task, which can take into account multiple factors as well as interactions.
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