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Compute the genetic relationship matrix using expected haplotype counts

The genetic relationship matrix (GRM) is the covariance between samples over the measured genetic markers. It's utility is in accounting for relatedness among samples, as random effects in a Linear Mixed Effects Model, when performing a Genome Wide Association Study (GWAS) [1,2] and computing the heritability of complex traits [3]. The GRM is traditionally computed using SNP genotypes, but here we are interested in haplotype based covariance.

Running the software

The program is ran by supplying the path and filename of a VCF. Note, as of now this software does not support data streams with UNIX pipe or bgzip, gzip, etc. compression. The output is printed to standard out.

hgrm path/to/my_vcf > grm

Installation and availability

The program is only available as source from this repository and requires

• cmake (>= 3.31.4)
• make
• clang or gcc C++17 compiler

To install navigate to the top level directory of this repository, and make the build directory

mkdir build

then use cmake to generate make files, etc.,

cmake -S . -B build/

followed by navigating to the build directory and running GNU make

make

In the build directory you should now have a binary file called hgrm, this is the executable program. Move it to a directory in your shell's search path.

Contributing

I am using GoogleTest framework for organizing tests. If you contribute, please make tests for your contributions. To run tests, build directory and build the project

cmake -S ../ -B .
make

Then use cmake's utility

ctest

Acknowledgement

Code design and original version completed by Robert Vogel, reviewed by Claude Sonnet, the AI assistant from Anthropic (Jan 2025), with minor recommendations incorporated.

References

[1] Kang et al. Genetics 178: 1709-1723 (2008)

[2] Kang et al. Nature Genetics 42 348-354 (2010)

[3] Yang et al. Nature Genetics 42, 565-569 (2010)