Unexpected Projected Prediction and Log Ratio Plots from Gneiss

[mortonjt (Jamie Morton)]

Hi @Zachary_Bendiks note that we are currently deprecating these functionality in gneiss and recommend to instead look at songbird and aldex2

There have been a few other related posts on this, so feel free to read those

Interpretation of gneiss lme-regression output

Hi @cdl, note that we are in the middle deprecating LME regression in favor of other differential abundances methods such as songbird and aldex2. See this post as well: Linear Regression Summary in Gneiss Concerning your other questions, y1 is the name of the log ratio. See the original gneiss tutorial on this https://docs.qiime2.org/2019.10/tutorials/gneiss/ The coefficients are slopes (i.e. differences across groups) in units of log-fold change (also covered in the tutorial). It’s not clea…

Some clarifications on gneiss correlation-clustering

Hi again @Sparkle, The visualizers you are using in gneiss are actually deprecated… when running them or reading the help docs you should see this note: This command is deprecated and will be removed in a future version of this plugin. So just beware that you are using a visualizer that the developers plan to remove in the next release of gneiss. The developer of gneiss, @mortonjt, now favors his newer method, songbird, so you may want to try that out instead: Because that ASV is only…

Regarding your questions

1. Yes, log ratios largely negate the need for rarefaction - but the issue with zeros remains. This is better handled in songbird and aldex2 due to their Multinomial model.
2. Definitely, collinearity is still a problem in differential abundance. The standard statistical recommendations still apply here - I'd start with fitting multiple models and comparing their differences.
3. We're deprecating this functionality and recommend songbird/aldex2 instead. So no, please don't trust those results.
4. Nature is often non-linear, so maybe this isn't completely unexpected. Linear methods can help with insights on this, but certainly won't be the best model for this.