Hi

I having a similar problem (see log below). I am analyzing a quantitative trait without covariates in a sub set of SNPs. I extracted (using PLINK) the subset of SNPs, created the GRM for the subset and then performed the REML.

The same pheno works if I calculate the REML for single SNPs.

any help?

Thank you in advance

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

* Genome-wide Complex Trait Analysis (GCTA)

* version 1.24.1

* (C) 2010-2013 Jian Yang, Hong Lee, Michael Goddard and Peter Visscher

* The University of Queensland

* MIT License

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

Analysis started: Mon May 19 14:48:57 2014

Options:

--grm 552_chr1_GRM

--pheno 552_NEW.pheno

--reml-no-constrain

--reml-no-lrt

--reml

--out 552_variance

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 [552_chr1_GRM.grm.id].

460 IDs read from [552_chr1_GRM.grm.id].

Reading the GRM from [552_chr1_GRM.grm.bin].

Reading the number of SNPs for the GRM from [552_chr1_GRM.grm.N.bin].

Pairwise genetic relationships between 460 individuals are included from [552_chr1_GRM.grm.bin].

Reading phenotypes from [552_NEW.pheno].

Non-missing phenotypes of 460 individuals are included from [552_NEW.pheno].

460 individuals are in common in these files.

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

460 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: 0.453744 0.795935

logL: -203.3

Running AI-REML algorithm ...

Iter. logL V(G) V(e)

Error: the information matrix is not invertible.