Hi Jamie,

Thank you so much for the fast reply!

Running the lme-regression simplified with --p formula “Size” worked, the coefficients summary doesn’t look too promising tho.

Running the lme-regression with the verbose flag gives the following errors - I scanned the whole report and shortened it here, since these lines are repeating:

/home/qiime/anaconda3/envs/qiime2/lib/python3.5/site-packages/statsmodels/base/model.py:496: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals

"Check mle_retvals", ConvergenceWarning)

/home/qiime/anaconda3/envs/qiime2/lib/python3.5/site-packages/statsmodels/regression/mixed_linear_model.py:2001: ConvergenceWarning: Gradient optimization failed.

warnings.warn(msg, ConvergenceWarning)

/home/qiime/anaconda3/envs/qiime2/lib/python3.5/site-packages/statsmodels/regression/mixed_linear_model.py:2019: ConvergenceWarning: The MLE may be on the boundary of the parameter space.

/home/qiime/anaconda3/envs/qiime2/lib/python3.5/site-packages/statsmodels/regression/mixed_linear_model.py:2039: ConvergenceWarning: The Hessian matrix at the estimated parameter values is not positive definite.

warnings.warn(msg, ConvergenceWarning)

/home/qiime/anaconda3/envs/qiime2/lib/python3.5/site-packages/statsmodels/base/model.py:1029: RuntimeWarning: invalid value encountered in sqrt

return np.sqrt(np.diag(self.cov_params()))

/home/qiime/anaconda3/envs/qiime2/lib/python3.5/site-packages/scipy/stats/_distn_infrastructure.py:879: RuntimeWarning: invalid value encountered in greater

return (self.a < x) & (x < self.b)

/home/qiime/anaconda3/envs/qiime2/lib/python3.5/site-packages/scipy/stats/_distn_infrastructure.py:879: RuntimeWarning: invalid value encountered in less

return (self.a < x) & (x < self.b)

/home/qiime/anaconda3/envs/qiime2/lib/python3.5/site-packages/scipy/stats/_distn_infrastructure.py:1818: RuntimeWarning: invalid value encountered in less_equal

cond2 = cond0 & (x <= self.a)

/home/qiime/anaconda3/envs/qiime2/lib/python3.5/site-packages/statsmodels/stats/multitest.py:320: RuntimeWarning: invalid value encountered in less_equal

reject = pvals_sorted <= ecdffactor*alpha

Traceback (most recent call last):

File “/home/qiime/anaconda3/envs/qiime2/lib/python3.5/site-packages/q2cli/commands.py”, line 224, in **call**

results = action(**arguments)

File “”, line 2, in lme_regression

File “/home/qiime/anaconda3/envs/qiime2/lib/python3.5/site-packages/qiime2/sdk/action.py”, line 228, in bound_callable

output_types, provenance)

File “/home/qiime/anaconda3/envs/qiime2/lib/python3.5/site-packages/qiime2/sdk/action.py”, line 424, in *callable_executor*

ret_val = self._callable(output_dir=temp_dir, **view_args)

File “/home/qiime/anaconda3/envs/qiime2/lib/python3.5/site-packages/q2_gneiss/regression/_regression.py”, line 73, in lme_regression

lme_summary(output_dir, res, tree)

File “/home/qiime/anaconda3/envs/qiime2/lib/python3.5/site-packages/gneiss-0.4.2-py3.5.egg/gneiss/plot/_regression_plot.py”, line 357, in lme_summary

plot_width=900, plot_height=400)

File “/home/qiime/anaconda3/envs/qiime2/lib/python3.5/site-packages/gneiss-0.4.2-py3.5.egg/gneiss/plot/_regression_plot.py”, line 186, in _heatmap_summary

ind = int(np.floor((x - _min) / (_max - _min) * (N - 1)))

ValueError: cannot convert float NaN to integer

Do I interpret correctly, this means, there just isn’t enough variation in the data, apart from the variation caused by my random effects (Site)?

Some more information on my data:

2539 taxa and 120 samples

Fixed effects:

Size - categorical variable with two levels

Al, Cr, Cu, Zn, As - continuous variables, values were clr-transformed

Random effects:

Site - categorical variable with ten levels.

Thank you for your help!

Lena