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Pve is .999 #271

Open
9 of 10 tasks
aguilar-gomez opened this issue Mar 31, 2023 · 1 comment
Open
9 of 10 tasks

Pve is .999 #271

aguilar-gomez opened this issue Mar 31, 2023 · 1 comment

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@aguilar-gomez
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Describe the bug
Most of the genomic associations I run results in pve .999.I have decent value peaks that are outliers. I have small sample size.

To Reproduce
Steps to reproduce the behavior:

for n in $(seq 1 13)
do
echo $n
nohup gemma -bfile pumilio.v4 -lmm 4 -o n${n}_${pc}_rescaffold -k pum.v4.sXX.txt -n $n 1> n$n}out 2> out.gemma.n$n &  
done

This is the log file :

##
## GEMMA Version    = 0.98.5 (2021-08-25)
## Build profile    = /gnu/store/8rvid272yb53bgascf5c468z0jhsyflj-profile
## GCC version      = 7.5.0
## GSL Version      = 2.6
## OpenBlas         = OpenBLAS 0.3.9  - OpenBLAS 0.3.9 DYNAMIC_ARCH NO_AFFINITY SkylakeX MAX_THREADS=128
##   arch           = SkylakeX
##   threads        = 64
##   parallel type  = threaded
##
## Command Line Input = gemma -bfile pumilio.v4 -lmm 4 -o n1__rescaffold -k pum.v4.sXX.txt -n 1 
##
## Date = Tue Nov 22 16:54:08 2022
##
## Summary Statistics:
## number of total individuals = 347
## number of analyzed individuals = 199
## number of covariates = 1
## number of phenotypes = 1
## number of total SNPs/var = 10788793
## number of analyzed SNPs/var = 6359583
## REMLE log-likelihood in the null model = -322.303
## MLE log-likelihood in the null model = -317.703
## pve estimate in the null model = 0.99999
## se(pve) in the null model = 0.000833612
## vg estimate in the null model = 1.61183
## ve estimate in the null model = 1.61183e-05
## beta estimate in the null model =   2.36683
## se(beta) =   0.000284599
##
## Computation Time:
## total computation time = 63.7511 min 
## computation time break down: 
##      time on eigen-decomposition = 0.460148 min 
##      time on calculating UtX = 5.07513 min 
##      time on optimization = 52.3442 min 
##

The output is:
**** INFO: Done.
and the assoc file head:

chr	rs	ps	n_miss	allele1	allele0	af	beta	se	logl_H1	l_remle	l_mle	p_wald	p_lrp_score
P_RNA_scaffold_2	.	30316	0	T	C	0.018	7.373270e-01	5.112214e-01	-3.166582e+02	1.000000e+05	1.000000e+05	1.508099e-01	1.482381e-01	1.508918e-01
P_RNA_scaffold_2	.	30337	0	A	C	0.447	-1.177313e-01	1.213347e-01	-3.172290e+02	1.000000e+05	1.000000e+05	3.330857e-01	3.300302e-01	3.317995e-01
P_RNA_scaffold_2	.	30360	0	A	T	0.015	9.879762e-01	5.263806e-01	-3.159398e+02	1.000000e+05	1.000000e+05	6.200688e-02	6.037101e-02	6.299756e-02
P_RNA_scaffold_2	.	30515	0	G	A	0.035	-5.207134e-01	3.915204e-01	-3.168139e+02	1.000000e+05	1.000000e+05	1.850633e-01	1.822937e-01	1.848092e-01
P_RNA_scaffold_2	.	30608	0	T	C	0.023	4.795118e-01	4.024873e-01	-3.169890e+02	1.000000e+05	1.000000e+05	2.349412e-01	2.319874e-01	2.342600e-01
P_RNA_scaffold_2	.	30645	0	T	C	0.070	-5.327640e-02	2.423960e-01	-3.176790e+02	1.000000e+05	1.000000e+05	8.262617e-01	8.251780e-01	8.254173e-01
P_RNA_scaffold_2	.	30843	0	A	C	0.183	-6.070896e-02	1.671540e-01	-3.176367e+02	1.000000e+05	1.000000e+05	7.168511e-01	7.151341e-01	7.155711e-01
P_RNA_scaffold_2	.	56591	0	C	T	0.123	1.191875e-01	2.133095e-01	-3.175458e+02	1.000000e+05	1.000000e+05	5.769643e-01	5.745517e-01	5.753409e-01
P_RNA_scaffold_2	.	56801	0	T	C	0.193	-1.983927e-01	1.757588e-01	-3.170619e+02	1.000000e+05	1.000000e+05	2.603642e-01	2.573548e-01	2.594963e-01

Expected behavior
Get values that describe how much of the variance is explained by the genetics

Additional context
I found a similar issue in the google group discussion but it was not solved:
https://groups.google.com/g/gemma-discussion/c/QmIfq3yDFas/m/eBPmLZF_DQAJ

Check list:

  1. I have found an issue with GEMMA
  2. I have searched for it on the issue tracker (incl. closed issues)
  3. I have searched for it on the mailing list
  4. I have tried the latest release of GEMMA
  5. I have read and agreed to below code of conduct
  6. If it is a support/install question I have posted it to the mailing list
  7. If it is software development related I have posted a new issue on the issue tracker or added to an existing one
  8. In the message I have included the output of my GEMMA run
  9. In the message I have included the relevant .log.txt file in the output directory
  10. I have made available the data to reproduce the problem (optional)

To find bugs the GEMMA software developers may ask to install a
development version of the software. They may also ask you for your
data and will treat it confidentially. Please always remember that
GEMMA is written and maintained by volunteers with good
intentions. Our time is valuable too. By helping us as much as
possible we can provide this tool for everyone to use.
@zy66-su
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zy66-su commented Aug 1, 2024

Describe the bug Most of the genomic associations I run results in pve .999.I have decent value peaks that are outliers. I have small sample size.

To Reproduce Steps to reproduce the behavior:

for n in $(seq 1 13)
do
echo $n
nohup gemma -bfile pumilio.v4 -lmm 4 -o n${n}_${pc}_rescaffold -k pum.v4.sXX.txt -n $n 1> n$n}out 2> out.gemma.n$n &  
done

This is the log file :

##
## GEMMA Version    = 0.98.5 (2021-08-25)
## Build profile    = /gnu/store/8rvid272yb53bgascf5c468z0jhsyflj-profile
## GCC version      = 7.5.0
## GSL Version      = 2.6
## OpenBlas         = OpenBLAS 0.3.9  - OpenBLAS 0.3.9 DYNAMIC_ARCH NO_AFFINITY SkylakeX MAX_THREADS=128
##   arch           = SkylakeX
##   threads        = 64
##   parallel type  = threaded
##
## Command Line Input = gemma -bfile pumilio.v4 -lmm 4 -o n1__rescaffold -k pum.v4.sXX.txt -n 1 
##
## Date = Tue Nov 22 16:54:08 2022
##
## Summary Statistics:
## number of total individuals = 347
## number of analyzed individuals = 199
## number of covariates = 1
## number of phenotypes = 1
## number of total SNPs/var = 10788793
## number of analyzed SNPs/var = 6359583
## REMLE log-likelihood in the null model = -322.303
## MLE log-likelihood in the null model = -317.703
## pve estimate in the null model = 0.99999
## se(pve) in the null model = 0.000833612
## vg estimate in the null model = 1.61183
## ve estimate in the null model = 1.61183e-05
## beta estimate in the null model =   2.36683
## se(beta) =   0.000284599
##
## Computation Time:
## total computation time = 63.7511 min 
## computation time break down: 
##      time on eigen-decomposition = 0.460148 min 
##      time on calculating UtX = 5.07513 min 
##      time on optimization = 52.3442 min 
##

The output is: **** INFO: Done. and the assoc file head:

chr	rs	ps	n_miss	allele1	allele0	af	beta	se	logl_H1	l_remle	l_mle	p_wald	p_lrp_score
P_RNA_scaffold_2	.	30316	0	T	C	0.018	7.373270e-01	5.112214e-01	-3.166582e+02	1.000000e+05	1.000000e+05	1.508099e-01	1.482381e-01	1.508918e-01
P_RNA_scaffold_2	.	30337	0	A	C	0.447	-1.177313e-01	1.213347e-01	-3.172290e+02	1.000000e+05	1.000000e+05	3.330857e-01	3.300302e-01	3.317995e-01
P_RNA_scaffold_2	.	30360	0	A	T	0.015	9.879762e-01	5.263806e-01	-3.159398e+02	1.000000e+05	1.000000e+05	6.200688e-02	6.037101e-02	6.299756e-02
P_RNA_scaffold_2	.	30515	0	G	A	0.035	-5.207134e-01	3.915204e-01	-3.168139e+02	1.000000e+05	1.000000e+05	1.850633e-01	1.822937e-01	1.848092e-01
P_RNA_scaffold_2	.	30608	0	T	C	0.023	4.795118e-01	4.024873e-01	-3.169890e+02	1.000000e+05	1.000000e+05	2.349412e-01	2.319874e-01	2.342600e-01
P_RNA_scaffold_2	.	30645	0	T	C	0.070	-5.327640e-02	2.423960e-01	-3.176790e+02	1.000000e+05	1.000000e+05	8.262617e-01	8.251780e-01	8.254173e-01
P_RNA_scaffold_2	.	30843	0	A	C	0.183	-6.070896e-02	1.671540e-01	-3.176367e+02	1.000000e+05	1.000000e+05	7.168511e-01	7.151341e-01	7.155711e-01
P_RNA_scaffold_2	.	56591	0	C	T	0.123	1.191875e-01	2.133095e-01	-3.175458e+02	1.000000e+05	1.000000e+05	5.769643e-01	5.745517e-01	5.753409e-01
P_RNA_scaffold_2	.	56801	0	T	C	0.193	-1.983927e-01	1.757588e-01	-3.170619e+02	1.000000e+05	1.000000e+05	2.603642e-01	2.573548e-01	2.594963e-01

Expected behavior Get values that describe how much of the variance is explained by the genetics

Additional context I found a similar issue in the google group discussion but it was not solved: https://groups.google.com/g/gemma-discussion/c/QmIfq3yDFas/m/eBPmLZF_DQAJ

Check list:

  1. I have found an issue with GEMMA
  2. I have searched for it on the issue tracker (incl. closed issues)
  3. I have searched for it on the mailing list
  4. I have tried the latest release of GEMMA
  5. I have read and agreed to below code of conduct
  6. If it is a support/install question I have posted it to the mailing list
  7. If it is software development related I have posted a new issue on the issue tracker or added to an existing one
  8. In the message I have included the output of my GEMMA run
  9. In the message I have included the relevant .log.txt file in the output directory
  10. I have made available the data to reproduce the problem (optional)

To find bugs the GEMMA software developers may ask to install a development version of the software. They may also ask you for your data and will treat it confidentially. Please always remember that GEMMA is written and maintained by volunteers with good intentions. Our time is valuable too. By helping us as much as possible we can provide this tool for everyone to use.

Hello, may I ask if your issue(pve estimate in the null model = 0.99999) has been resolved？

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@aguilar-gomez @zy66-su