Multivariable GWAS (-lmm) has NaN values when including more than 3 phenotypes about gemma

[pcarbo]

@winterwang I think this is a different issue from #45. Is there any way you would be able to share the data you are using? It does not even need to be the full data---it can be a single chromosome, for example. I'd like to run some tests to understand what is going on.

[winterwang]

@pcarbo Thanks for the reply

[pcarbo]

@winterwang I was able to successfully run this command on my MacBook Pro:

~/git/gemma/bin/gemma -g GEMMAchr22txt.gz -p GEMMApheno.txt \
  -n 1 2 3 4 -k GEMMA_standardrelatedmat005.sXX.txt -lmm

See the attached log file.

What OS are you using? What version of gemma are you using?

result.log.txt.gz

[winterwang]

@pcarbo Thanks for the feedback.
However, I still get nan for the command.
Previously I used latest version 0.97 downloaded from github.com, compiled and tested on my Ubuntu 16.04 machine:

*********************************************************
  Genome-wide Efficient Mixed Model Association (GEMMA)  
  Version 0.97, 07/07/2017                              
  Visit http://www.xzlab.org/software.html For Updates   
  (C) 2017 Xiang Zhou                                   
  GNU General Public License                             
  For Help, Type ./gemma -h                              
*********************************************************

I found you are using version 0.96 on a Mac Pro. So I switched to version 0.96, the problem still not fixed still on my Ubuntu 16.04 platform:

*********************************************************
  Genome-wide Efficient Mixed Model Association (GEMMA)  
  Version 0.96, 05/17/2017                              
  Visit http://www.xzlab.org/software.html For Updates   
  (C) 2017 Xiang Zhou                                   
  GNU General Public License                             
  For Help, Type ./gemma -h                              
*********************************************************

./gemma -g/GEMMAchr22txt.gz -p GEMMApheno.txt -n 1 2 3 4 -k GEMMA_centerrelatedmat005.cXX.txt -lmm 
Reading Files ... 
## number of total individuals = 807
## number of analyzed individuals = 795
## number of covariates = 1
## number of phenotypes = 4
## number of total SNPs = 163763
## number of analyzed SNPs = 114095
Start Eigen-Decomposition...
REMLE estimate for Vg in the null model: 
-nan	
-nan	-nan	
-nan	-nan	-nan	
-nan	-nan	-nan	-nan	
se(Vg): 
-nan	
-nan	-nan	
-nan	-nan	-nan	
-nan	-nan	-nan	-nan	
REMLE estimate for Ve in the null model: 
-nan	
-nan	-nan	
-nan	-nan	-nan	
-nan	-nan	-nan	-nan	
se(Ve): 
-nan	
-nan	-nan	
-nan	-nan	-nan	
-nan	-nan	-nan	-nan	
REMLE likelihood = -nan
MLE estimate for Vg in the null model: 
-nan	
-nan	-nan	
-nan	-nan	-nan	
-nan	-nan	-nan	-nan	
se(Vg): 
-nan	
-nan	-nan	
-nan	-nan	-nan	
-nan	-nan	-nan	-nan	
MLE estimate for Ve in the null model: 
-nan	
-nan	-nan	
-nan	-nan	-nan	
-nan	-nan	-nan	-nan	
se(Ve): 
-nan	
-nan	-nan	
-nan	-nan	-nan	
-nan	-nan	-nan	-nan	
MLE likelihood = -nan
Reading SNPs                                                    0.00%

Reading SNPs kept 0.00% and not moving forward.
Can you succeed when using all of the 5 phenotypes on your Mac Pro?

[pcarbo]

@winterwang I was able to reproduce the NaN's using gemma v0.96 for Linux. It is worrying that we have a platform-dependent issue! I will look in to it.

[pcarbo]

@winterwang The discovered the problem: the Linux binary provided in the GEMMA 0.96 release was linked to GSL 2.2.1, and it seems that it only works with GSL 1.x, so I linked with GSL 1.16 instead. Now I am no longer getting the NaN's. I've attached the new binary, and we will soon make a GEMMA 0.97 release available for download.

Can you please test that the attached binary works for you on your Ubuntu system?

gemma.linux.gz

[pcarbo]

Also, I updated the binary for the v0.96 release.

[winterwang]

Hi, @pcarbo . Your help is greatly appreciated. Now using the new binary you attached for me I am able to compute the command with 4 and 5 phenotypes on my Ubuntu 16.04. No more nan is created.

Thank you so much!

##
## GEMMA Version = 0.97
##
## Command Line Input = ./gemma.linux -g GEMMAchr22txt.gz -p GEMMApheno.txt -n 1 2 3 4 -k ./output/GEMMA_centerrelatedmat005.cXX.txt -lmm -o test 
##
## Date = Fri Jul 28 09:14:00 2017
##
## Summary Statistics:
## number of total individuals = 807
## number of analyzed individuals = 795
## number of covariates = 1
## number of phenotypes = 4
## number of total SNPs = 163763
## number of analyzed SNPs = 114095
## REMLE log-likelihood in the null model = -4299.15
## MLE log-likelihood in the null model = -4302.56
## REMLE estimate for Vg in the null model: 
9.96209e-06	
7.58463e-14	9.71815e-06	
-7.87707e-13	1.66e-11	9.56255e-06	
4.365e-13	1.44716e-12	-1.9888e-13	9.37882e-06	
## se(Vg): 
1.06002	
0.760842	1.08813	
0.722019	0.88268	0.981513	
0.663478	0.669846	0.640012	0.841037	
## REMLE estimate for Ve in the null model: 
0.996209	
0.00285371	0.971815	
-0.01166	0.538287	0.956255	
0.0264271	0.0530889	-0.0166509	0.937882	
## se(Ve): 
0.333927	
0.237622	0.337159	
0.227644	0.27476	0.309713	
0.209418	0.209679	0.202253	0.266001	
## MLE estimate for Vg in the null model: 
9.96208e-06	1.26323e-13	-1.08012e-12	1.76122e-13	
1.26323e-13	9.71815e-06	1.63898e-11	1.25851e-12	
-1.08012e-12	1.63898e-11	9.56255e-06	7.06729e-14	
1.76122e-13	1.25851e-12	7.06729e-14	9.37882e-06	
## se(Vg): 
1.08775	
0.781956	1.11965	
0.74072	0.908896	1.00651	
0.67756	0.684627	0.653495	0.85589	
## MLE estimate for Ve in the null model: 
0.994956	0.00285012	-0.0116453	0.0263939	
0.00285012	0.970592	0.53761	0.0530221	
-0.0116453	0.53761	0.955052	-0.01663	
0.0263939	0.0530221	-0.01663	0.936702	
## se(Ve): 
0.342888	
0.244368	0.347138	
0.233676	0.28309	0.317762	
0.214008	0.214445	0.20664	0.270878	
## estimate for B (d by c) in the null model (columns correspond to the covariates provided in the file): 
-0.00670195	
-0.00196422	
0.00190655	
-0.00429808	
## se(B): 
0.035399	
0.034963	
0.0346819	
0.0343471	
##
## Computation Time:
## total computation time = 7.03936 min 
## computation time break down: 
##      time on eigen-decomposition = 0.00856403 min 
##      time on calculating UtX = 0.162786 min 
##      time on optimization = 6.42819 min 
##

[pjotrp]

Can we add a test to the test suite?

[pcarbo]

@pjotrp Good idea. I will do that.

[pcarbo]

@pjotrp I'm having trouble reproducing the error we had earlier, and I no longer have the GEMMA binary linked to the GSL 2.x library. I suggest we close this issue---I don't think this requires an additional test.

[pjotrp]

I can test GSL versions with GNU Guix. We had the same problem in GeneNetwork.org - I'll try to find a dataset.

[pjotrp]

I have reproduced the problem. Will add test data to GEMMA soon - is a plink file which is good too.

[pcarbo]

@pjotrp Great!

[pjotrp]

Looks like the fix of issue 26 also fixes the GSLv2 for this issue. Test that fails on master coming up.

[pjotrp]

This has been fixed and tests added in #92. Note that if you get NaNs again, it is probably due to highly correlated phenotypes/covariates. Please reopen if an issue resurfaces.