GCTA-GREML: the X^t * V^-1 * X matrix is not invertible.

[Truongphikt]

Hi Cloufield team, it was a struggle for a GWAS newbie like me that finally went to the SNP-Heritability estimation by GCTA-GREML section. Now I have been stuck here for a few days in an error with the Estimation step. I guess that I have some wrong with my inputs (see below).

My command is as follows:

awk '{print $1,$2,$5,$6,$7,$8,$9}' projected.sscore > 5PCs.txt

gcta            --grm 1kg_eas         \
                --pheno 1kgeas_binary.phen         \
                --prevalence 0.5         \
                --qcovar  projected.sscore        \
                --reml         \
                --out 1kg_eas         \
                --thread-num 1

Needed inputs: inputs.zip

And I got an error:

Error

******************************************************************** 
Genome-wide Complex Trait Analysis (GCTA)
* version v1.94.1 Linux* Built at Nov 15 2022 21:14:25, by GCC 8.5
* (C) 2010-present, Yang Lab, Westlake University* Please report bugs to Jian Yang <[email protected]>
********************************************************************
Analysis started at 03:39:30 UTC on Sat Oct 19 2024.
Hostname: f9ed864a67df

Accepted options:
--grm 1kg_eas
--pheno 1kgeas_binary.phen
--prevalence 0.5
--qcovar projected.sscore
--reml
--out 1kg_eas
--thread-num 1

Note: This is a multi-thread program. If your machine has multiple processors, you can specify the number of threads with the—-thread-num option to speed up the computation.

Reading IDs of the GRM from [1kg_eas.grm.id].
504 IDs are read from [1kg_eas.grm.id].Reading the GRM from [1kg_eas.grm.bin].
GRM for 504 individuals are included from [1kg_eas.grm.bin].
Reading phenotypes from [1kgeas_binary.phen].
Non-missing phenotypes of 502 individuals are included from [1kgeas_binary.phen].
Reading quantitative covariate(s) from [projected.sscore].
12 quantitative covariate(s) of 501 individuals are included from [projected.sscore].
Assuming a disease phenotype for a case-control study: 248 cases and 250 controls 
12 quantitative variable(s) included as covariate(s).
498 individuals are in common in these files.

Performing  REML analysis ... (Note: may take hours depending on sample size).
498 observations, 13 fixed effect(s), and 2 variance component(s)(including residual variance).
Calculating prior values of variance components by EM-REML ...
Updated prior values: 5.24546e+19 3.07774e+21
logL: 1.6403e+14Running AI-REML algorithm ...
Iter.     logL    V(G)    V(e)    Error:   the X^t * V^-1 * X matrix is not invertible. Please check the covariate(s) and/or the environmental factor(s).
An error occurs, please check the options or data

Could someone tell me where was I wrong? Thanks.

[Cloufield]

Hi,
Sorry for the late reply. I updated this section and replaced the outdated paths. It should work now.
For the error, please see #15 in GCTA FAQ. It usually indicates that the inverse of variance-covariance matrix does not exist or there is something wrong with the GRM.

[Truongphi20]

@Cloufield Thank you so much. Based on your new updates, I have successfully run this step. My update command:

awk '{print $1,$2,$5,$6,$7,$8,$9}' projected.sscore > 5PCs.txt
gcta         --grm 1kg_eas         \
                --pheno 1kgeas_binary.phen         \
                --prevalence 0.5         \
                --qcovar  5PCs.txt        \
                --reml         \
                --out 1kg_eas

My input files:
inputs.zip