Table 2.

Introduction to various analysis and visualization methods

Method	Scientific question	Visualization	Description and example reference
Alpha diversity	Within-sample diversity	Boxplot	Distribution (Edwards et al., 2015) or significant difference (Zhang et al., 2019) of alpha diversity among groups (Fig. 3A)
		Rarefaction curve	Sample diversity changes with sequencing depth or evaluation of sequencing saturation (Beckers et al., 2017)
		Venn diagram	Common or unique taxa (Ren et al., 2019)
Beta diversity	Distance among samples or groups	Unconstrained PCoA scatter plot	Major differences of samples showing group differences (Fig. 3B) or gradient changes with time (Zhang et al., 2018b)
		Constrained PCoA scatter plot	Major differences among groups (Zgadzaj et al., 2016; Huang et al., 2019)
		Dendrogram	Hierarchical clustering of samples (Chen et al., 2019)
Taxonomic composition	Relative abundance of features	Stacked bar plot	Taxonomic composition of each sample (Beckers et al., 2017) or group (Jin et al., 2017) (Fig. 3C)
		Flow or alluvial diagram	Relative abundance (RA) of taxonomic changes among seasons (Smits et al., 2017) or time-series (Zhang et al., 2018b)
		Sanky diagram	A variety of Venn diagrams showing changes in RA and common or unique features among groups (Smits et al., 2017)
Difference comparison	Significantly different biomarkers between groups	Volcano plot	A variety of scatter plots showing P-value, RA, fold change, and number of differences (Shi et al., 2019a)
		Manhattan plot	A variety of scatter plots showing P-values, taxonomy, and highlighting significantly different biomarkers (Zgadzaj et al., 2016) (Fig. 3D)
		Extend bar plot	Bar plot of RA combined with difference and confidence intervals (Parks et al., 2014)
Correlation analysis	Correlation between features and sample metadata	Scatter plot with linear fitting	Shows changes in features with time (Metcalf et al., 2016) or relationships with other numeric metadata (Fig. 3E)
		Corrplot	Correlation coefficient or distance triangular matrix visualized by color and/or shape (Zhang et al., 2018b)
		Heatmap	RA of features that change with time (Subramanian et al., 2014)
Network analysis	Global view correlation of features	Colored based on taxonomy or modules	Finding correlation patterns of features based on taxonomy (Fig. 3F) and/or modules (Jiao et al., 2016)
		Colors highlight important features	Highlighting important features and showing their positions and connections (Wang et al., 2018b)
Machine learning	Classification groups or regression analysis for numeric metadata prediction	Heatmap	Colored block showing classification results (Fig. 3G) (Wilck et al., 2017) or feature patterns in a time series (Subramanian et al., 2014).
		Bar plot	Feature importance, RA (Zhang et al., 2019), and increase in mean squared error (Subramanian et al., 2014).
Treemap	Phylogenetic tree or taxonomy hierarchy	Phylogenetic tree or cladogram	Phylogenetic tree (Fig. 3H) shows relationship of OTUs or species (Levy et al., 2018). Taxonomic cladogram highlighting interesting biomarkers (Segata et al., 2011).
		Circular tree map	Shows features in a hierarchy color bubble (Carrión et al., 2019)