I am struggling to understand the output from first-distances with baseline (qiime longitudinal first-distances with –p-baseline). I have longitudinal data on the impact of antibiotics on microbial composition in 10 individuals split into three experimental groups. I chose a pre-treatment baseline point, ran first-distances on a weighted UniFrac distance matrix, exported the raw calculations, and then plotted the distances over time.
In the qiime2 longitudinal tutorial, first-distances are described as measuring the “rate of change” from a static sample/point so I think my confusion is about the understanding the ‘unit’ (for lack of a better term) for first-distance calculations. For purposes of this question, I’ve included the plot showing first-distance calculations (y-axis) over day (x-axis) with mean stat-summary lines. I am having trouble wrapping my brain around what the y-axis truly means. Does a higher value on the y-axis mean a greater rate of change or is it just a greater distance value for the pairwise comparison (e.g. the comparison of community at baseline vs. at day X). And does a very low value a low rate of change or that the community at that time-point is very similar to the baseline community?
Thanks for any help!