compare_metagenome_results {ggpicrust2}

Compare Metagenome Results

Description

Compare Metagenome Results

Arguments

metagenomes

A list of metagenomes matrices with rows as KOs and columns as samples. Each matrix in the list should correspond to a different metagenome.

names

A vector of names for the metagenomes in the same order as in the 'metagenomes' list.

daa_method

A character specifying the method for differential abundance analysis (DAA). Possible choices are: "ALDEx2", "DESeq2", "edgeR", "limma voom", "metagenomeSeq", "LinDA", "Maaslin2", and "Lefse". The default is "ALDEx2".

p.adjust

A character specifying the method for p-value adjustment. Possible choices are: "BH" (Benjamini-Hochberg), "holm", "bonferroni", "hochberg", "fdr", and "none". The default is "BH".

reference

A character specifying the reference group level for DAA. This parameter is used when there are more than two groups. The default is NULL.

Value

A list containing two elements:

• "daa": a list of results from the 'pathway_daa' function. Each result is a data frame containing the differential abundance analysis results with columns for the feature ID, the test statistic, the raw p-value, and the adjusted p-value.

• "correlation": a list with two elements: "cor_matrix" and "p_matrix", which are matrices of Spearman correlation coefficients and their corresponding p-values, respectively, between every pair of metagenomes.

Examples

library(dplyr)
library(ComplexHeatmap)
# Generate example data
set.seed(123)
# First metagenome
metagenome1 <- abs(matrix(rnorm(1000), nrow = 100, ncol = 10))
rownames(metagenome1) <- paste0("KO", 1:100)
colnames(metagenome1) <- paste0("sample", 1:10)
# Second metagenome
metagenome2 <- abs(matrix(rnorm(1000), nrow = 100, ncol = 10))
rownames(metagenome2) <- paste0("KO", 1:100)
colnames(metagenome2) <- paste0("sample", 1:10)
# Put the metagenomes into a list
metagenomes <- list(metagenome1, metagenome2)
# Define names
names <- c("metagenome1", "metagenome2")
# Call the function
results <- compare_metagenome_results(metagenomes, names, daa_method = "LinDA")
# Print the correlation matrix
print(results$correlation$cor_matrix)
# Print the p-value matrix
print(results$correlation$p_matrix)