Host variation data practical session

Hint

This practical session uses software available on the course-provided virtual machines. To follow this workshop at a later date, see the github repo for installation instructions.

microbiome-GWAS using GEMMA

  1. Prepare microbiome composition data

  2. Prepare individual covariate data

  3. Run GEMMA

  4. Visualise GWAS results

  5. Extract SNP annotation

Prerequisites

For this tutorial you will need to first load the conda environment by running:

conda activate mgwas-env

The software GEMMA is already installed on the virtual machine. The user manual can be found on the GEMMA github repo.

The rest of this practical is available on a dedicated page (which is also downloadable from the github repo).

Further reading

Here are the references for some of the papers cited in the above practical, plus some additional published examples of microbiome-GWAS:

  • Price et al. (2006). Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet 38: 904–909. https://doi.org/10.1038/ng1847

  • van den Berg et al. (2019). Significance testing and genomic inflation factor using high-density genotypes or whole-genome sequence data. J Anim Breed Genet 136: 418-429. https://doi.org/10.1111/jbg.12419

  • Qin et al. (2022). Combined effects of host genetics and diet on human gut microbiota and incident disease in a single population cohort. Nat Genet 54: 134–142. https://doi.org/10.1038/s41588-021-00991-z

  • Lopera-Maya et al. (2022). Effect of host genetics on the gut microbiome in 7,738 participants of the Dutch Microbiome Project. Nat Genet 54: 143–151. https://doi.org/10.1038/s41588-021-00992-y