Hello,
I am running MaasLin2 like this:
fit_data <- Maaslin2(input_data = df_input_data,
input_metadata = df_input_metadata,
output = paste0(read, "_", threshold, "_new"),
fixed_effects = c("Diagnosis"),
reference = c("Diagnosis,Ctrl"),
normalization = "CLR",
transform = "LOG",
analysis_method = "LM",
plot_heatmap = FALSE,
plot_scatter = FALSE,
max_significance = 0.05)
And a result I get a list of significant_results.tsv
where the counts of total values are correct while the non-zeros are not, i.e.:
feature metadata value coef stderr N N.not.0 pval qval
K03637 Diagnosis PD 1 3.70074341541719e-17 87 1 1.11773196541154e-49 2.33233403449207e-47
K00077 Diagnosis PD 1 7.40148683083438e-17 87 1 8.94185572329222e-49 1.67928050483428e-46
K06959 Diagnosis PD 1 1.11022302462516e-16 87 1 3.01787630661113e-48 5.15233791255973e-46
K03660 Diagnosis PD 1 1.48029736616688e-16 87 1 7.15348457863382e-48 1.03340338759033e-45
K05540 Diagnosis PD 1 1.48029736616688e-16 87 1 7.15348457863382e-48 1.03340338759033e-45
K02189 Diagnosis PD 1 2.96059473233375e-16 87 1 5.72278766290709e-47 7.67671087924251e-45
For example, for the KEGG KOs above my data includes at least 26 such KEGG KOs per sample, meaning at least 26 non-zero entries per sample. I obviously cannot rely on such results if counts are not correct.
I’ve tried multiple ways to fix it but still I cannot find an error or what could cause it.
Please let me know if you have any idea Thank you!