Probably something to do with how otu_table are transposed by default
library(devtools)
library(tidyverse)
library(phyloseq)
install_github("adw96/DivNet")
library(DivNet)
packageVersion("DivNet") # 0.3.2
data("GlobalPatterns")
# since this is just an illustration, just get the most abundant 5 taxa
top_five_taxa = names(sort(taxa_sums(GlobalPatterns), decreasing = TRUE)[1:5])
# don't specify covariates
dv <- GlobalPatterns %>% prune_taxa(top_five_taxa, .) %>% divnet
dv$fitted_z
# this explicitly strips the sample_data
dv2 <- GlobalPatterns %>% prune_taxa(top_five_taxa, .) %>% otu_table %>% divnet
dv2$fitted_z
Probably something to do with how
otu_table
are transposed by default