Post by jy on Jan 14, 2014 9:02:38 GMT
Hello,
I have the above error when running gcta and this is my log file:
*******************************************************************
* Genome-wide Complex Trait Analysis (GCTA)
* version 1.24
* (C) 2010-2013 Jian Yang, Hong Lee, Michael Goddard and Peter Visscher
* The University of Queensland
* MIT License
*******************************************************************
Analysis started: Tue Jan 14 15:06:50 2014
Options:
--reml-bivar 1 2
--grm Hongkong_GCTA
--pheno /data/jiayu/coherit/DATA/1474samples-HK-AMD-pheno.tsv
--qcovar /data/jiayu/coherit/DATA/1474samples-HK-AMD-CaseControl-Covariate-PCA_nohdr.tsv
--out /data/jiayu/coherit/OUTPUT/Hongkong_CNV_PCV_GCTA
--reml-bivar-prevalence 0.01 0.01
Note: This is a multi-thread program. You could specify the number of threads by the --thread-num option to speed up the computation if there are multiple processors in your machine.
Reading IDs of the GRM from [Hongkong_GCTA.grm.id].
1474 IDs read from [Hongkong_GCTA.grm.id].
Reading the GRM from [Hongkong_GCTA.grm.bin].
Reading the number of SNPs for the GRM from [Hongkong_GCTA.grm.N.bin].
Pairwise genetic relationships between 1474 individuals are included from [Hongkong_GCTA.grm.bin].
Reading phenotypes from [/data/jiayu/coherit/DATA/1474samples-HK-AMD-pheno.tsv].
There are 2 traits specified in the file [/data/jiayu/coherit/DATA/1474samples-HK-AMD-pheno.tsv].
Traits 1 and 2 are included in the bivariate analysis.
Non-missing phenotypes of 1472 individuals are included from [/data/jiayu/coherit/DATA/1474samples-HK-AMD-pheno.tsv].
Reading quantitative covariates from [/data/jiayu/coherit/DATA/1474samples-HK-AMD-CaseControl-Covariate-PCA_nohdr.tsv].
10 quantitative covariate(s) of 1474 individuals read from [/data/jiayu/coherit/DATA/1474samples-HK-AMD-CaseControl-Covariate-PCA_nohdr.tsv].
1472 individuals are in common in these files.
1316 non-missing phenotypes for trait #1 and 1162 for trait #2
310 cases and 1006 controls for trait #1
156 cases and 1006 controls for trait #2
10 quantitative variable(s) included as covariate(s).
Performing bivariate REML analysis ... (Note: may take hours depending on sample size).
2478 observations, 22 fixed effect(s), and 6 variance component(s)(including residual variance).
Calculating prior values of variance components by EM-REML ...
Updated prior values: 0.0763136 0.0519771 0.0422867 0.0757598 0.0516166 0.0422639
logL: 1515.08
Running AI-REML algorithm ...
Iter. logL V(G)_tr1 V(G)_tr2 C(G)_tr12 V(e)_tr1 V(e)_tr2 C(e)_tr12
Note: to constrain the correlation being from -1 to 1, a genetic (or residual) variance-covariance matrix is bended to be positive definite.
1 1732.13 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 (2 component(s) constrained)
Error: the variance-covaraince matrix V is not invertible.
Analysis finished: Tue Jan 14 15:06:58 2014
Computational time: 0:0:8
this is the pheno file
[jiayu@cello_eph OUTPUT]$ head /data/jiayu/coherit/DATA/1474samples-HK-AMD-pheno.tsv
FAM217_C547_01-W01_QA1_1_Quad610v1 217_C547_01-W01_QA1_1_Quad610v1 1 1
FAM217_C563_01-W01_QA1_1_Quad610v1 217_C563_01-W01_QA1_1_Quad610v1 1 1
FAM217_C576_01-W01_QA1_1_Quad610v1 217_C576_01-W01_QA1_1_Quad610v1 1 1
FAM217_C581_01-W01_QA1_1_Quad610v1 217_C581_01-W01_QA1_1_Quad610v1 1 1
FAM217_C622_01-W01_QA1_1_Quad610v1 217_C622_01-W01_QA1_1_Quad610v1 1 1
FAM217_C646_01-W01_QA1_1_Quad610v1 217_C646_01-W01_QA1_1_Quad610v1 1 1
FAM217_C648_01-W01_QA1_1_Quad610v1 217_C648_01-W01_QA1_1_Quad610v1 1 1
FAM217_C655_01-W01_QA1_1_Quad610v1 217_C655_01-W01_QA1_1_Quad610v1 1 1
FAM217_C658_01-W01_QA1_1_Quad610v1 217_C658_01-W01_QA1_1_Quad610v1 1 1
FAM217_C667_01-W01_QA1_1_Quad610v1 217_C667_01-W01_QA1_1_Quad610v1 1 1
can you kindly advise on the problem? Thanks
I have the above error when running gcta and this is my log file:
*******************************************************************
* Genome-wide Complex Trait Analysis (GCTA)
* version 1.24
* (C) 2010-2013 Jian Yang, Hong Lee, Michael Goddard and Peter Visscher
* The University of Queensland
* MIT License
*******************************************************************
Analysis started: Tue Jan 14 15:06:50 2014
Options:
--reml-bivar 1 2
--grm Hongkong_GCTA
--pheno /data/jiayu/coherit/DATA/1474samples-HK-AMD-pheno.tsv
--qcovar /data/jiayu/coherit/DATA/1474samples-HK-AMD-CaseControl-Covariate-PCA_nohdr.tsv
--out /data/jiayu/coherit/OUTPUT/Hongkong_CNV_PCV_GCTA
--reml-bivar-prevalence 0.01 0.01
Note: This is a multi-thread program. You could specify the number of threads by the --thread-num option to speed up the computation if there are multiple processors in your machine.
Reading IDs of the GRM from [Hongkong_GCTA.grm.id].
1474 IDs read from [Hongkong_GCTA.grm.id].
Reading the GRM from [Hongkong_GCTA.grm.bin].
Reading the number of SNPs for the GRM from [Hongkong_GCTA.grm.N.bin].
Pairwise genetic relationships between 1474 individuals are included from [Hongkong_GCTA.grm.bin].
Reading phenotypes from [/data/jiayu/coherit/DATA/1474samples-HK-AMD-pheno.tsv].
There are 2 traits specified in the file [/data/jiayu/coherit/DATA/1474samples-HK-AMD-pheno.tsv].
Traits 1 and 2 are included in the bivariate analysis.
Non-missing phenotypes of 1472 individuals are included from [/data/jiayu/coherit/DATA/1474samples-HK-AMD-pheno.tsv].
Reading quantitative covariates from [/data/jiayu/coherit/DATA/1474samples-HK-AMD-CaseControl-Covariate-PCA_nohdr.tsv].
10 quantitative covariate(s) of 1474 individuals read from [/data/jiayu/coherit/DATA/1474samples-HK-AMD-CaseControl-Covariate-PCA_nohdr.tsv].
1472 individuals are in common in these files.
1316 non-missing phenotypes for trait #1 and 1162 for trait #2
310 cases and 1006 controls for trait #1
156 cases and 1006 controls for trait #2
10 quantitative variable(s) included as covariate(s).
Performing bivariate REML analysis ... (Note: may take hours depending on sample size).
2478 observations, 22 fixed effect(s), and 6 variance component(s)(including residual variance).
Calculating prior values of variance components by EM-REML ...
Updated prior values: 0.0763136 0.0519771 0.0422867 0.0757598 0.0516166 0.0422639
logL: 1515.08
Running AI-REML algorithm ...
Iter. logL V(G)_tr1 V(G)_tr2 C(G)_tr12 V(e)_tr1 V(e)_tr2 C(e)_tr12
Note: to constrain the correlation being from -1 to 1, a genetic (or residual) variance-covariance matrix is bended to be positive definite.
1 1732.13 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 (2 component(s) constrained)
Error: the variance-covaraince matrix V is not invertible.
Analysis finished: Tue Jan 14 15:06:58 2014
Computational time: 0:0:8
this is the pheno file
[jiayu@cello_eph OUTPUT]$ head /data/jiayu/coherit/DATA/1474samples-HK-AMD-pheno.tsv
FAM217_C547_01-W01_QA1_1_Quad610v1 217_C547_01-W01_QA1_1_Quad610v1 1 1
FAM217_C563_01-W01_QA1_1_Quad610v1 217_C563_01-W01_QA1_1_Quad610v1 1 1
FAM217_C576_01-W01_QA1_1_Quad610v1 217_C576_01-W01_QA1_1_Quad610v1 1 1
FAM217_C581_01-W01_QA1_1_Quad610v1 217_C581_01-W01_QA1_1_Quad610v1 1 1
FAM217_C622_01-W01_QA1_1_Quad610v1 217_C622_01-W01_QA1_1_Quad610v1 1 1
FAM217_C646_01-W01_QA1_1_Quad610v1 217_C646_01-W01_QA1_1_Quad610v1 1 1
FAM217_C648_01-W01_QA1_1_Quad610v1 217_C648_01-W01_QA1_1_Quad610v1 1 1
FAM217_C655_01-W01_QA1_1_Quad610v1 217_C655_01-W01_QA1_1_Quad610v1 1 1
FAM217_C658_01-W01_QA1_1_Quad610v1 217_C658_01-W01_QA1_1_Quad610v1 1 1
FAM217_C667_01-W01_QA1_1_Quad610v1 217_C667_01-W01_QA1_1_Quad610v1 1 1
can you kindly advise on the problem? Thanks