Prerequisites

1. Snakemake
2. Singularity

Input data

• Plink binary genotype data (.bed, .bim, .fam)
  • See https://www.cog-genomics.org/plink/1.9/input#bed
  • Recommended to filter out variants with extremely high missingness¹.
• GCTA-GRM data (.grm.bin, .grm.id, .grm.N.bin)
  • See https://yanglab.westlake.edu.cn/software/gcta/#MakingaGRM
• Phenotype values

Phenotype values

The format of the phenotype file needs to be as shown below.

SampleA	0.312
SampleB	0.150

The file needs to be a headerless, tab-separated file with two columns: first column with sample ID that matches the sample IDs in the .fam file, second column with the phenotype value for the corresponding samples.

Running the analysis

Before running

Examine the following two configuration files:

• config.yaml
• analyse/config.yaml

The config.yaml file is used to configure the can be modified to is where the user can define configuration values which will affect the overall result of the analysis. The analyse.config.yaml is a snakemake configuration profile for running the workflow. Modify the values here based on your server resource availability.

Running the pipeline

To run the pipeline, you must specify the cohort, bfile, grm, group, phenotype, and phenotype_file configuration values either in the config.yaml file or using the --config option (See Snakemake Configuration).

For example, running one association analysis using the --config option:

snakemake \
    run \
    --profile analyse \
    --config \
        cohort=MANOLIS \
        bfile=/path/to/cohort-bfile \
        grm=/path/to/GCTA-grm \
        group=Anthropometric \
        phenotype=BMI \
        phenotype_file=/path/to/phenotype_file.txt

Running the pipeline for multiple phenotypes

You can run the above command in a loop with different phenotype and phenotype_file value to run association on multiple traits.
Alternatively, if you have a job scheduler available (e.g. Slurm), submit each individual run as jobs.
If you are running multiple jobs in parallel, you may need to add the --nolock option to your snakemake command. The output files should not overlap as long as you specify a different combination of the group and phenotype values, but please be aware of why Snakemake locks the working directory.

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Footnotes

1. This is due to the GCTA-COJO algorithm having issues analysing variants with low sample size. ↩