### 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