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The comparative statistics module allows the comparison of groups of samples to identify differences or similarities. Reliable statistical procedures are used and all results are reported with appropriate confidence and significance measures. The comparative statistics module requires different conditions with at least two samples per condition. Dependent on the present type of analysis the comparative statistics analysis results in figures such as principal component analysis (PCA) plots to visualize sample clustering or tables for differentially expressed genes or differentially abundant taxonomic groups.
Figure 1: PCA based on UniFrac distances displaying inter-sample similarities in a 16S rRNA based dataset. Samples were grouped by two conditions.
Table 1: Detail of a results table listing differentially expressed genes based on the comparison of two conditions in a shotgun metatranscriptomics study.