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GWAS.utils

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GWAS.utils is an R package with basic helper functions for manipulating GWAS data, including two GWAS datasets.

To get started, please refer to this vignette.

Install

remotes::install_github("sinarueeger/GWAS.utils")

Install including vignettes:

remotes::install_github("sinarueeger/GWAS.utils", build = TRUE, 
build_opts = c("--no-resave-data", "--no-manual"))

vignette("gwas-utils-package")

Note: The vignette needs to have the Rmpfr package installed. Use an old version if you have not updated R in a while.

Usage

There are six functions:

  • eaf2maf(eaf = eaf_vec): Transforms effect allele frequencies into minor allele frequencies.

  • inv_normal(x = vec): Inverse normal transformation of a variable.

  • z2p(z = z_vec): Transforms Z-statistics to P-values, includes an option for very large Z-statistics.

  • eff_nbr_tests(mat = genotype_df): Calculates the effective number of tests of a GWAS, based on the correlation between the SNPs.

  • QQplot(p = p_vec): Q-Q-plot of P-values (uniformly distributed under the null).

  • genomic_inflation(Z = z_vec): Calculates genomic inflation, with either P-values or Z-statistics. Most of the functions are just handy and trivial helper functions. For QQplot() and genomic_inflation() there are a number of other packages with similar functions, e.g. GenABEL or qqman. Our genomic_inflation function takes two types of summary statistics as input by making an assumption about the P-value origin. And QQplot can inlcude the number of effective tests.

And two datasets:

  • giant: Summary statistics of 10'000 SNPs from a GWAS in human body height.
  • opensnp data: Genotype data and human body height of 784 individuals from the publicly accessible openSNP database.

Contributing

Please note that the 'GWAS.utils' project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.