I am a post-doc working on respiratory (nasopharyngeal) microbiota development. I was highly interested when reading up on this new version of MaAsLin, given it provides options to appropriately model repeated measures, which is extremely important when studying microbial succession over time.
Until recently, I used the metagenomeSeq::fitTimeSeries-function for these analyses. By prefiltering features, I hope I was able to control false-positive detection to a certain degree. I would be very interested in (re)running my models using MaAsLin2, yet I need advice on two problems I encounter.
- I find that some microbiota show unimodal/non-linear, rather than linear patterns over time (for example: Staphylococcus typically sharply increases just after birth, peaking at ~1month, after which it decreases in abundance). How would you model these non-linear trends in MaAsLin (is that even possible? Should I include splines, use a different model than “LM”)?
- The advantage of metagenomeSeq::fitTimeSeries-function (which is spline-based, focussed on the (covariate-adjusted) differential abundance between 2 groups over time), is that it seems to cater non-linearity over time AND gives some indication within what time period microbial abundance is different. Is that also possible with MaAsLin?
Any pointers/ideas/advice is very welcome.
PS: I really enjoyed reading the preprint on BioRxiv and am highly impressed by the amount of benchmarking done (also using other packages). This is a very minor detail, but do I understand correctly that the term ‘univariate’ is used to refer to ‘univariable’ models (it is slightly unclear combined with the use of the term ‘multivariable’)?