genstats provide easy access to tools for statistical analysis of genetic data. Genetic data is difficult to come by, but provides a very informative basis for statistical anaysis. We have therefore through some assumptions provided method for simulating genetic data which can be used for both association analysis and predictive statistics. The package provides standard methods for association analysis such as GWAS and LT-FH. Furthermore, we have provided a method which can be used to predict the phenotypes of individuals, based on the their genotypes. The structure of simulated data is easy to use in combination with dplyr and it is therefore easy to implement your own methods. This also means that the functions are very dependent on column names. It is therefore important if this package is used with data not simulated by genstats, that the columns match the following column names.
genstats::get_names(c('l', 'l_g', 'pheno'), n_sib = 1)
#> [1] "l_0" "l_g_0" "pheno_0" "l_p1" "l_g_p1" "pheno_p1"
#> [7] "l_p2" "l_g_p2" "pheno_p2" "l_s3" "l_g_s3" "pheno_s3"With the amount of siblings being variable from 1 to what the computer can handle.
Examples and details about each method can be found in the articles. Due to a large amount of data, many of the plots are included as images. Source code for all plots can be found in https://github.com/Holdols/genstats/blob/main/src_plots.Rmd.
The packages uses the method of LT-FH as described by Hujoel, M.L.A., Gazal, S., Loh, PR. et al.. Link to article is found in Bibliography.
The package is developed as a part of our bachelor’s program in data science at Aarhus University.
We would like to thank our supervisor Emil Michael Pedersen for patience and great supervision!
Installation
You can install the development version of genstats from GitHub with:
# install.packages("devtools")
devtools::install_github("Holdols/genstats")Bibliography
- Hujoel, M.L.A., Gazal, S., Loh, PR. et al. Liability threshold modeling of case–control status and family history of disease increases association power. Nat Genet 52, 541–547 (2020). https://doi.org/10.1038/s41588-020-0613-6”
The package uses functions and methods from both bigsnpr: https://privefl.github.io/bigsnpr/ and bigstatsr: https://privefl.github.io/bigstatsr/index.html
Please visit those site for more information about how data is stored