[R-sig-ME] Questions about design and convergence warnings
Thierry Onkelinx
thierry.onkelinx at inbo.be
Fri Sep 29 13:34:32 CEST 2017
Dear Umber,
Can you clarify what a tissue is? Distinct parts of an organ (tissue 1
for organ 1 refers to the same part as tissue 1 for organ 2)? Or
merely different samples for the same organ (no link between tissue 1
between organs). Tissue as random effect is only relevant in the first
case. In the latter case is depends on the number of replicates per
tissue:organ. In case of one replication go for (1|Organ), in case of
multiple replications go for (1|Organ/Tissue).
It looks like you have very strong species effects. That is an
indication for quasi-complete separation, which can trigger
convergence warnings.
Best regards,
ir. Thierry Onkelinx
Statisticus/ Statistician
Vlaamse Overheid / Government of Flanders
INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE
AND FOREST
Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance
thierry.onkelinx op inbo.be
Kliniekstraat 25, B-1070 Brussel
www.inbo.be
///////////////////////////////////////////////////////////////////////////////////////////
To call in the statistician after the experiment is done may be no
more than asking him to perform a post-mortem examination: he may be
able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data. ~ Roger Brinner
The combination of some data and an aching desire for an answer does
not ensure that a reasonable answer can be extracted from a given body
of data. ~ John Tukey
///////////////////////////////////////////////////////////////////////////////////////////
Van 14 tot en met 19 december 2017 verhuizen we uit onze vestiging in
Brussel naar het Herman Teirlinckgebouw op de site Thurn & Taxis.
Vanaf dan ben je welkom op het nieuwe adres: Havenlaan 88 bus 73, 1000 Brussel.
///////////////////////////////////////////////////////////////////////////////////////////
2017-09-28 16:58 GMT+02:00 Dube, Umber <udube op wustl.edu>:
> Thanks for your continued development of lme4 and all the support you've provided.
>
> This is my first mixed model analysis. I've done my best to read over the past messages and think I've found a proper method for performing it, but I would like to verify that is correct.
>
> I'm interested in performing a generalized linear mixed model analysis on RNA-sequencing data from different tissues derived from the same organ (I have 4 different tissues from ~160 diseased organs, ~60 healthy organs).
>
> I have been modelling the following as fixed effects:
> RNA Integrity Number (RIN) - quality of the total RNA extracted from each tissues (continuous)
> Post-mortem Interval (PMI) - how much time elapsed following death until the tissue was frozen (continuous)
> Sex - genetic sex of the organ (categorical)
> Age at death (AOD) - age of organ at death (continuous)
> Species - species of organ (categorical)
> Gene - normalized count data of gene expression (continuous)
>
> I have been modelling the following as random effects:
> Batch (categorical)
>
> I understand that I have a nested model Organ/Tissue, but after reading (https://stackoverflow.com/questions/19414336/using-glmer-for-nested-data), I modeled tissue as a fixed effect due to the small numbers (4 tissues).
>
> Altogether, my model is:
>
> glmer(Disease ~ RIN + SEX + AOD + PMI + Species + (1|batch) + Tissue + (1|Tissue:Organ) + Gene, data=NormDEGenes, family=binomial(), control=glmerControl(optCtrl=list(maxfun=1e9) ) )
>
> I unfortunately get convergence warnings with these models, but after going through the ?convergence documentation I hope they are false positives.
>
> Warning messages:
> 1: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
> unable to evaluate scaled gradient
> 2: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :
> Model failed to converge: degenerate Hessian with 1 negative eigenvalues
>
> To address this:
>
> 1) I've centered and scaled my continous predictors
>
> 2) I've checked for singularity #False
>
> 3) I've printed and compared with internal calculations
>
> 4) I've tried all available optimizers. I believe all of them have failed to converge, but they all end up with approximately the same log-liklihoods.
>
>
>> ss$ fixef ## extract fixed effects
> (Intercept) RIN_scale SEXF AOD_scale PMI_scale Species1 Species2 Species3 Tissue1 Tissue2 Tissue3 Gene
> bobyqa 0.11463 -0.41005 0.409846 -0.07834 -0.65198 14.79972 13.30085 14.88501 -0.35383 -0.31039 0.666657 -2.42662
> Nelder_Mead -0.10894 -0.41005 0.40988 -0.07834 -0.652 15.02298 13.52411 15.10837 -0.35371 -0.31033 0.666808 -2.42659
> nlminbw 0.067 -0.41005 0.409846 -0.07834 -0.65198 14.84728 13.34841 14.93257 -0.35383 -0.3104 0.666653 -2.4266
> optimx.L-BFGS-B 0.066515 -0.40992 0.40951 -0.07822 -0.65189 14.84686 13.34846 14.93227 -0.35369 -0.3102 0.666332 -2.42644
> nloptwrap.NLOPT_LN_NELDERMEAD -0.19423 -0.40082 0.401142 -0.07745 -0.63582 14.74898 13.28662 14.83122 -0.3464 -0.30534 0.646181 -2.36802
> nloptwrap.NLOPT_LN_BOBYQA -0.19423 -0.40082 0.401142 -0.07745 -0.63582 14.74898 13.28662 14.83122 -0.3464 -0.30534 0.646181 -2.36802
>
>
>> ss$ llik ## log-likelihoods
> bobyqa Nelder_Mead nlminbw optimx.L-BFGS-B nloptwrap.NLOPT_LN_NELDERMEAD nloptwrap.NLOPT_LN_BOBYQA
> -327.896 -327.896 -327.896 -327.896 -327.933 -327.933
>
>> ss$ sdcor ## SDs and correlations
> Organ:Tissue.(Intercept) batch.(Intercept)
> bobyqa 3.68E-05 0.520826
> Nelder_Mead 5.56E-03 0.52084
> nlminbw 3.10E-08 0.520826
> optimx.L-BFGS-B 0.00E+00 0.52084
> nloptwrap.NLOPT_LN_NELDERMEAD 4.56E-08 0.517555
> nloptwrap.NLOPT_LN_BOBYQA 4.56E-08 0.517555
>
>
>
>> ss$ theta ## Cholesky factors
> Organ:Tissue.(Intercept) batch.(Intercept)
> bobyqa 3.68E-05 0.520826
> Nelder_Mead 5.56E-03 0.52084
> nlminbw 3.10E-08 0.520826
> optimx.L-BFGS-B 0.00E+00 0.52084
> nloptwrap.NLOPT_LN_NELDERMEAD 4.56E-08 0.517555
> nloptwrap.NLOPT_LN_BOBYQA 4.56E-08 0.517555
>
>
>> ss$ which.OK ## which fits worked
> bobyqa Nelder_Mead nlminbw nmkbw optimx.L-BFGS-B nloptwrap.NLOPT_LN_NELDERMEAD nloptwrap.NLOPT_LN_BOBYQA
> TRUE TRUE TRUE FALSE TRUE TRUE TRUE
>
>
> I would appreciate comment on my design, convergence warnings, and troubleshooting results.
>
> Thanks,
>
> Umber
>
>
> [[alternative HTML version deleted]]
>
> _______________________________________________
> R-sig-mixed-models op r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
More information about the R-sig-mixed-models
mailing list