GWAS is a popular method to detect the genetic variants associated with a trait in different individuals.

I found a series of four papers written by Wellcome Trust Center for Human Genetics published on Nature Protocol, which is a great resource for beginners (list shown below).

This blog is the notebook for these four paper.

Study design

  1. phenotype
  2. heritability
  3. consider the population-based method
  4. controls
  5. sample size
  6. de novo or repliction study

Data quality control

  • Per-individual QC
    • identification of individuals with discordant sex information
    • identification of individuals with outlying missing genotype or heterozygosity rates
    • identification of duplicated or related individuals
    • identification of individuals of divergent ancestry
  • Per-marker QC
    • identification of SNPs with an excessive missing genotype
    • identification of SNPs showing a significant deviation from Hardy-Weinberg equilibrium (HWE)
    • identification of SNPs with significantly different missing genotype rates between cases and controls
    • the removal of all markers with a very low minor allele frequency (MAF)

Paper list

  • Zondervan, K. T., & Cardon, L. R. (2007). Designing candidate gene and genome-wide case–control association studies. Nature Protocols, 2(10), 2492–2501. https://doi.org/10.1038/nprot.2007.366
  • Pettersson, F. H., Anderson, C. A., Clarke, G. M., Barrett, J. C., Cardon, L. R., Morris, A. P., & Zondervan, K. T. (2009). Marker selection for genetic case–control association studies. Nature Protocols, 4(5), 743–752. https://doi.org/10.1038/nprot.2009.38
  • Anderson, C., Pettersson, F., Clarke, G., Cardon, L., Morris, A., & Zondervan, K. (2010). Data quality control in genetic case-control association studies. Nat Protoc., 5(9), 1564–1573. https://doi.org/10.1038/nprot.2010.116
  • Clarke, G. M., Anderson, C. a, Pettersson, F. H., Cardon, L. R., & Andrew, P. (2011). Basic statistical analysis in genetic case-control studies. Nature Protocols, 6(2), 121–133. https://doi.org/10.1038/nprot.2010.182.Basic