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.