Segmentation fault with mlma

I´m trying to run a mlma analysis with gcta with the following command:


gcta64 --mlma --dosage-mach Chr1.mach.dose Chr1.mach.info --grm GRMcows_HD099 --pheno traitelisa_pcr_cultivo.phen --reml-no-lrt --out epc_chr1.gwas --thread-num 5


But I get the following "Segmentation fault" error:


*******************************************************************

* Genome-wide Complex Trait Analysis (GCTA)

* version 1.93.2 beta Linux

* (C) 2010-present, Jian Yang, The University of Queensland

* Please report bugs to Jian Yang <jian.yang.qt@gmail.com>

*******************************************************************

Analysis started at 14:24:54 CET on Tue Mar 09 2021.

Hostname: gt4.i2basque.es



Accepted options:

--mlma

--dosage-mach Chr1.mach.dose Chr1.mach.info

--grm GRMcows_HD099

--pheno traitelisa_pcr_cultivo.phen

--reml-no-lrt

--out epc_chr1.gwas

--thread-num 5



Note: the program will be running on 5 threads.



Reading map file of the imputed dosage data from [Chr1.mach.info].

2335707 SNPs to be included from [Chr1.mach.info].

Reading dosage data from [Chr1.mach.dose] in individual-major format (Note: may use huge RAM).

(Imputed dosage data for 984 individuals detected).

Imputed dosage data for 984 individuals are included from [Chr1.mach.dose].

Reading phenotypes from [traitelisa_pcr_cultivo.phen].

Non-missing phenotypes of 984 individuals are included from [traitelisa_pcr_cultivo.phen].

Reading IDs of the GRM from [GRMcows_HD099.grm.id].

984 IDs read from [GRMcows_HD099.grm.id].

Reading the GRM from [GRMcows_HD099.grm.bin].

GRM for 984 individuals are included from [GRMcows_HD099.grm.bin].

983 individuals are in common in these files.



Performing MLM association analyses (including the candidate SNP) ...



Performing REML analysis ... (Note: may take hours depending on sample size).

983 observations, 1 fixed effect(s), and 2 variance component(s)(including residual variance).

Calculating prior values of variance components by EM-REML ...

Updated prior values: 0.0261599 0.0285509

logL: 939.559

Running AI-REML algorithm ...

Iter. logL V(G) V(e)

1 942.80 0.01740 0.03515

2 951.27 0.01254 0.03935

3 954.76 0.00979 0.04197

4 956.15 0.00820 0.04361

5 956.71 0.00724 0.04466

6 956.94 0.00538 0.04678

7 957.10 0.00566 0.04656

8 957.11 0.00563 0.04658

9 957.11 0.00563 0.04658

Log-likelihood ratio converged.

Calculating allele frequencies ...



Running association tests for 2335707 SNPs ...

Segmentation fault (core dumped)




Any help is welcome!!!!