Hi,
I had some questions about min_abundance and min_prevalence filtering before I run Maaslin2 (in R) on my data set.
I will give some details about my dataset first: I am planning on using relative abundance values for genera, calculated from normalized read counts, as opposed to using the read counts themselves, for my ‘input_data’.
Here is the code chunk:
Hrare_noFL_fit = Maaslin2(input_data = genus_rel_abundH.rarefied_noFL_4maaslin,
input_metadata = H.rarefied_noFL_sampledata,
analysis_method = “CPLM”,
normalization = “NONE”,
output = “Hrare_noFL_fit_output”,
fixed_effects = “Loc”,
reference = c(“Loc,CA”))
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If one feature (in my case, genus) is below the min_abundance level in one sample, is that feature excluded for all other samples where it otherwise does exceed the min_abundance level?
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“If both min_prevalence and min_abundance are specified in the Maaslin2 function, would a feature be excluded, for all other samples, if it does not meet: (i) both the min_prevalence and min_abundance levels, or (ii) either the min_prevalence or min_abundance levels?”
Thanks and please let me know if you need any more info,
Tammy