如何在R语言中显示Simper()分析的P值与Global R²？

Hey there! Let's tackle your SIMPER analysis issues step by step. I'll assume you're using the vegan package in R (the standard tool for this kind of analysis) and walk you through extracting P-values and getting the Global R² you need.

1. Extract and View SIMPER P-values #

The simper() function in vegan calculates permutation-based P-values for species contributions, but it doesn't show them in the default print output. You can access these values directly from the result object:

Example Code: #

# Load the required package
library(vegan)

# Use sample data (replace with your own dataset)
data(dune)
data(dune.env)

# Run your SIMPER analysis
simper_out <- simper(dune, dune.env$Management)

# Default print output only shows contribution stats
print(simper_out)

# Extract and display the P-values
# Access the significance table from the simper result
simper_pvals <- simper_out$signif
print(simper_pvals)

# For better readability, combine contribution stats with P-values
simper_full_summary <- cbind(simper_out$average, simper_pvals)
print(simper_full_summary)

The $signif element of the simper result holds the P-values for each species' dissimilarity contribution between groups.

2. Retrieve Global R² Value #

SIMPER itself doesn't compute a Global R², but this metric is tied to PERMANOVA (Permutational Multivariate Analysis of Variance)—which tests overall group differences using the same dissimilarity metric (usually Bray-Curtis, the default for SIMPER). Use adonis2() from vegan to get this value:

Example Code: #

# Calculate Bray-Curtis dissimilarity (matches SIMPER's default)
bray_dist <- vegdist(dune, method = "bray")

# Run PERMANOVA to get Global R²
adonis_out <- adonis2(bray_dist ~ Management, data = dune.env)

# View the result—look for the "R2" column in the output
print(adonis_out)

The R² value here represents the proportion of variance in community composition explained by your grouping variable (e.g., Management), which is the "Global R²" you're seeking.

Quick Notes: #

• Ensure your grouping variable is formatted as a factor (use as.factor() if needed) before running both simper() and adonis2().
• Both the SIMPER P-values and PERMANOVA results rely on permutations, so they test whether observed patterns are significantly different from random.

内容的提问来源于stack exchange，提问作者Jesse001