Interpretation of gneiss lme-regression output


I am quite new working with lme-regression in gneiss. I have data from the same individuals taken at 7 different time points (so I chose lme-regression instead of ols-regression). I used performed gradient clustering based on the day the samples were taken (Time_days) and used --p-formula Time_days and --p-groups ‘Subject_ID’ in lme-regression.

I got a FDR corrected coefficient p-value of 2.52EXP-12 for balance ‘y1’ at the species level with 20 taxa in the numerator and 122 in the denominator.

What does exactly the coefficient for that balance ‘y1’ mean?
Group variance = 1.275354
Intercept = 0.370015
Time_days = 0.027925

Also, is there any way I can see using gneiss the variance explained (R2) by that particular balance?

Thank you a lot in advance,

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

The coefficients are slopes (i.e. differences across groups) in units of log-fold change (also covered in the tutorial).

It’s not clear how to compute R2 in LME, this is an open statistics question as far as I am aware.

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Hi @mortonjt,

Thanks a lot for the clarifications. I will also have a deep look to the other differential abundance methods you proposed.


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