两组/多组比较横向柱形图

Two-Group Comparison Writing Template

Methods Section

To identify differentially abundant microbial features between groups, we performed statistical analysis using the "Two-Group Comparison Horizontal Bar Chart" tool. The raw abundance table was preprocessed by filtering features with prevalence below 20%, filling zeros with half of the minimum non-zero value, and applying log10 transformation to reduce skewness.

Differential abundance between the experimental and control groups was assessed using the Mann-Whitney U test. To control for false discovery rate (FDR) in multiple testing, we applied the Benjamini-Hochberg correction. Effect sizes were calculated as Hedges' g and log2 fold change (log2FC) to quantify the magnitude of differences. Statistical significance was defined as FDR-adjusted p-value < 0.05.

Results Section

Comparative analysis revealed [X] significantly differentially abundant microbial features between the experimental and control groups (FDR < 0.05). Among these, [Y] features were significantly enriched in the experimental group (e.g., [Feature1], log2FC = [value], p_adj = [value]), while [Z] features were enriched in the control group (e.g., [Feature2], log2FC = [value], p_adj = [value]). Effect size analysis indicated that [Feature3] showed the largest between-group difference (Hedges' g = [value]).

Figure Legend

Figure X. Differentially abundant microbial features between experimental and control groups.

(A) Horizontal bar chart showing mean relative abundance of features in the experimental group (user-defined color) and control group (user-defined color).

(B) Difference plot displaying between-group differences with 95% confidence intervals (error bars).

(C) Effect size (Hedges' g) plot, with points farther from zero indicating larger effect sizes.

(D) Fold change (log2FC) plot, with positive values indicating enrichment in the experimental group.

FDR-adjusted p-values and significance levels are shown on the right (*p < 0.05, **p < 0.01, ***p < 0.001).

Multi-Group Comparison Writing Template

Methods Section

To identify differentially abundant microbial features across multiple groups, we employed the "Multi-Group Comparison Horizontal Bar Chart" tool. Data preprocessing included filtering features with prevalence below 20%, zero-value imputation, and log10 transformation.

Global differences among groups were tested using the Kruskal-Wallis test, with FDR adjustment using the Benjamini-Hochberg method. Statistical significance was defined as FDR-adjusted p-value < 0.05.

Results Section

The Kruskal-Wallis test identified [X] microbial features with significant abundance differences across [GroupA], [GroupB], and [GroupC] (FDR < 0.05). Specifically, [Feature1] showed highest abundance in [GroupA] (mean abundance = [value]), while [Feature2] was most abundant in [GroupC] (mean abundance = [value]). These differentially abundant features may reflect group-specific microbial composition patterns.

Figure Legend

Figure X. Differentially abundant microbial features across multiple groups.

Horizontal bar chart displaying mean relative abundance of the top [N] most significant features across groups, with different colors representing different groups (colors user-defined). FDR-adjusted p-values from Kruskal-Wallis test and significance levels are shown on the right (*p < 0.05, **p < 0.01, ***p < 0.001).

Discussion Section Guidance

The significant enrichment of [FeatureX] in the experimental group may be associated with [biological process]. Previous studies have reported similar patterns of [FeatureX] abundance under [similar conditions] [citation]. Additionally, the enrichment of [FeatureY] in the control group might reflect [adaptive response]. These differentially abundant microbial features could serve as potential biomarkers worthy of further investigation into their functional significance.

Note: The discussion should integrate specific research context and existing literature to explain the biological significance of differential features.