#Then we perform correlation heatmap to show the associations between eigengenes and environmental factors.
create trans_env object
t2 <- trans_env$new(dataset = dataset, add_data = metadata[, 1:7])
head(t2$data_env)
Carbon_source Time Group Treatment Peak Replicate Fraction
A1F10 13C-S D21 A D21-13C-S HF 1 F10
A1F11 13C-S D21 A D21-13C-S HF 1 F11
B1F13 12C-S D21 A D21-12C-S LF 1 F13
A2F9 13C-S D21 A D21-13C-S HF 2 F9
A2F10 13C-S D21 A D21-13C-S HF 2 F10
A2F11 13C-S D21 A D21-13C-S HF 2 F11
calculate correlations
t2$cal_cor(add_abund_table = t1$res_eigen)
head(t2$res_cor)
by_group Taxa Env Correlation Pvalue AdjPvalue Significance
V1 All M11 Replicate 0.2721824 0.18808941 0.3177362
V2 All M1 Replicate -0.3576988 0.07916599 0.3177362
V3 All M2 Replicate 0.2953269 0.15179069 0.3177362
V4 All M3 Replicate 0.3427625 0.09347944 0.3177362
V5 All M15 Replicate 0.2706764 0.19064171 0.3177362
V6 All M4 Replicate -0.1009713 0.63105674 0.7324662
plot the correlation heatmap
t2$plot_cor()
I am trying to plot the correlation heatmap, but when I run the command "t2$plot_cor()", the following errors occurs.
Error in hclust(dist(t(clu_data))) : N must be at least 2.
Could you facilitate me to solve this error?
