Closed AlexiPearson-Lund closed 6 months ago
Not a problem, @AlexiPearson-Lund , and thanks for your great question.
I appreciate your difficulty -- that these are clearly differentially abundant taxa, and you'd like to quantify that with a p-value, but corncob won't give you a p-value in this case.
You have at least two options, one of which I recommend much more strongly
I personally recommend Option 1.
I hope this helps but feel free to reopen this issue if not.
Hello,
I have a data set where I am trying to determine the differential abundance of ASVs between groups using differentialTest(). I am looking at the microbiome before and after treatment. Before treatment I have no reads of a particular ASV (ASV3) and then after treatment this ASV is in very high abundance (an average of 40% abundance in my after-treatment group). I've read that corncob has issues when one group doesn't have any reads. I tried artificially adding in either 1 or 100 reads to each sample. When I added in 1 I got 1400 significant ASVs and when I did 100 to each, I got 96. I don't understand why that is or if this technique is a reasonable workaround. Is there a better workaround?
I am extremely new to this kind of analysis and greatly appreciate the help!