updates to aldex.glm and results interpretation

[mirpie]

Hello!

I'm trying to use aldex.glm() to explore differential abundance for a complex design involving both Genotype (B6 vs. TCR) and stress condition (Stress vs. NoStress). My code is as follows (dat_pr is my filtered phyloseq object):

#create model matrix
meta = data.frame(dat_pr_OBIT_f@sam_data)
mm = with(meta, model.matrix(~GENOTYPE + Stress + GENOTYPE:Stress))
#extract OTU table
otus = data.frame(dat_pr_OBIT_f@otu_table)
# check alignment
all(meta$SAMPLE_ID == colnames(otus))

#CLR transform values with model matrix
glm <- aldex.clr(otus, mm, mc.samples=128, denom="all")

glm.test <- aldex.glm(glm)
glm.test = rownames_to_column(glm.test, "ASV")

As mentioned in a previous issue, originally it seems that the glm function had a "drop1" argument, which based on my knowledge means that differentially abundant taxa for the first factor would only be tested within the baseline group of the second factor. For example, differentially abundant taxa B6 vs. TCR (model.GENOTYPETCR) would only be tested in the "NoStress" condition and vice versa. Is this still the case? If so, how can I construct a model that tests for the global effects of genotype on taxon abundance while still accounting/controlling for stress, without removing sample groups, similar to something like DESeq2 or corncob?

Thanks so much in advance!

Miranda

[ggloor]

the aldex.glm takes optional arguments which (in theory) should allow you to define your model specifically. The glm function inside ALDEx is just this: glm(x ~ model., ...), the model is specified in the matrix, and other parameters you want to pass to glm() should follow the verbose=FALSE parameter.

Does this help?

[mirpie]

Hi,

Yes it does somewhat! Although I guess what I’m wondering is what behaviour ALDEX2 exhibits when I input the model matrix as shown above with standard dummy coding (no special contrasts, pretty much equivalent to inserting the model as an argument). I.e., how can I interpret results for model.GENOTYPETCR with respect to stress conditions? Are all levels of stress “accounted for” in the model to isolate the genotype, or is the genotype effect only calculated within one level of the stress factor?
Thanks!