Post by xyyin666666 on Mar 8, 2017 21:19:41 GMT
Hi Jian,
I am using GCTA 1.26 loco-mlma to run single common marker association on a GWAS data set for a binary trait. I got an error "information matrix is invertible". The Vg component is near zero. Is that the reason? By the way, I checked the grm and did not find any strange kinship values there. Do you have any suggestions how to resolve this problem?
Thanks
Here is the log file:
*******************************************************************
* Genome-wide Complex Trait Analysis (GCTA)
* version 1.26.0
* (C) 2010-2016, The University of Queensland
* MIT License
* Please report bugs to: Jian Yang <jian.yang@uq.edu.au>
*******************************************************************
Analysis started: Wed Mar 8 16:00:53 2017
Options:
--bfile eur.qc
--mlma-loco
--grm-bin eur.qc
--pheno eur.phen
--covar eur.bcov
--qcovar eur.qcov
--keep eur.samp.id
--thread-num 30
--out eur.qc
Note: the program will be running on 30 threads.
Reading PLINK FAM file from [eur.qc.fam].
2742 individuals to be included from eur.qc.fam].
665 individuals are kept from [eur.samp.id].
Reading PLINK BIM file from [eur.qc.bim].
8851982 SNPs to be included from [eur.qc.bim].
Reading PLINK BED file from [eur.qc.bed] in SNP-major format ...
Genotype data for 665 individuals and 8851982 SNPs to be included from [eur.qc.bed].
Reading phenotypes from [eur.phen].
Non-missing phenotypes of 2742 individuals are included from [eur.phen].
Reading quantitative covariates from [eur.qcov].
1 quantitative covariate(s) of 2742 individuals read from [eur.qcov].
Reading discrete covariate(s) from [eur.bcov].
1 discrete covariate(s) of 2742 individuals are included from [eur.bcov].
665 individuals are in common in these files.
...
Performing REML analysis ... (Note: may take hours depending on sample size).
665 observations, 3 fixed effect(s), and 2 variance component(s)(including residual variance).
Calculating prior values of variance components by EM-REML ...
Updated prior values: 0.0008019 0.00091148
logL: 1780.81
Running AI-REML algorithm ...
Iter. logL V(G) V(e)
1 1791.52 0.00000 0.00517 (1 component(s) constrained)
2 1635.59 0.00000 0.05740 (1 component(s) constrained)
3 926.01 0.00000 19.86242 (1 component(s) constrained)
4 -1000.57 0.00000 2364417.27321 (1 component(s) constrained)
5 -4869.01 0.00000 33504319634841536.00000 (1 component(s) constrained)
6 -12605.94 0.00000 6727507069433473490563680573193191424.00000 (1 component(s) constrained)
7 -28079.80 0.00000 271244463241055019487978440181689384761423885161979078499527830459289671041024.00000 (1 component(s) constrained)
8 -59027.51 0.00000 440934743257014500762526456917998749691555546881860674049279903965444200439085094651064915071771346275002492628637685229411359276509665866113398311506830950400.00000 (1 component(s) constrained)
Error: the information matrix is not invertible.
I am using GCTA 1.26 loco-mlma to run single common marker association on a GWAS data set for a binary trait. I got an error "information matrix is invertible". The Vg component is near zero. Is that the reason? By the way, I checked the grm and did not find any strange kinship values there. Do you have any suggestions how to resolve this problem?
Thanks
Here is the log file:
*******************************************************************
* Genome-wide Complex Trait Analysis (GCTA)
* version 1.26.0
* (C) 2010-2016, The University of Queensland
* MIT License
* Please report bugs to: Jian Yang <jian.yang@uq.edu.au>
*******************************************************************
Analysis started: Wed Mar 8 16:00:53 2017
Options:
--bfile eur.qc
--mlma-loco
--grm-bin eur.qc
--pheno eur.phen
--covar eur.bcov
--qcovar eur.qcov
--keep eur.samp.id
--thread-num 30
--out eur.qc
Note: the program will be running on 30 threads.
Reading PLINK FAM file from [eur.qc.fam].
2742 individuals to be included from eur.qc.fam].
665 individuals are kept from [eur.samp.id].
Reading PLINK BIM file from [eur.qc.bim].
8851982 SNPs to be included from [eur.qc.bim].
Reading PLINK BED file from [eur.qc.bed] in SNP-major format ...
Genotype data for 665 individuals and 8851982 SNPs to be included from [eur.qc.bed].
Reading phenotypes from [eur.phen].
Non-missing phenotypes of 2742 individuals are included from [eur.phen].
Reading quantitative covariates from [eur.qcov].
1 quantitative covariate(s) of 2742 individuals read from [eur.qcov].
Reading discrete covariate(s) from [eur.bcov].
1 discrete covariate(s) of 2742 individuals are included from [eur.bcov].
665 individuals are in common in these files.
...
Performing REML analysis ... (Note: may take hours depending on sample size).
665 observations, 3 fixed effect(s), and 2 variance component(s)(including residual variance).
Calculating prior values of variance components by EM-REML ...
Updated prior values: 0.0008019 0.00091148
logL: 1780.81
Running AI-REML algorithm ...
Iter. logL V(G) V(e)
1 1791.52 0.00000 0.00517 (1 component(s) constrained)
2 1635.59 0.00000 0.05740 (1 component(s) constrained)
3 926.01 0.00000 19.86242 (1 component(s) constrained)
4 -1000.57 0.00000 2364417.27321 (1 component(s) constrained)
5 -4869.01 0.00000 33504319634841536.00000 (1 component(s) constrained)
6 -12605.94 0.00000 6727507069433473490563680573193191424.00000 (1 component(s) constrained)
7 -28079.80 0.00000 271244463241055019487978440181689384761423885161979078499527830459289671041024.00000 (1 component(s) constrained)
8 -59027.51 0.00000 440934743257014500762526456917998749691555546881860674049279903965444200439085094651064915071771346275002492628637685229411359276509665866113398311506830950400.00000 (1 component(s) constrained)
Error: the information matrix is not invertible.