BR_ss.RdBR_ss is a function which aims to use summary statistics to alleviate
Winner's Curse bias in SNP-trait association estimates, obtained from a
discovery GWAS. The function implements a parametric bootstrap approach, proposed
by Forde et al. (2023). This approach was inspired by the bootstrap
resampling method detailed in Faye et
al. (2011), which requires original individual-level data.
BR_ss(summary_data, seed_opt = FALSE, seed = 1998)A data frame containing summary statistics from the
discovery GWAS. It must have three columns with column names rsid,
beta and se, respectively, and columns beta and
se must contain numerical values. Each row must correspond to a
unique SNP, identified by rsid. The function requires that there must
be at least 5 SNPs as any less will result in issues upon usage of the
smoothing spline.
A logical value which allows the user to choose if they wish
to set a seed, in order to ensure reproducibility of adjusted estimates.
Small differences can occur between iterations of the function with the same
data set due to the use of parametric bootstrapping. The default setting is
seed_opt=FALSE.
A numerical value which specifies the seed used if
seed_opt=TRUE. The default setting is the arbitrary value of
1998.
A data frame with the inputted summary data occupying the first three
columns. The new adjusted association estimates for each SNP are returned in
the fourth column, namely beta_BR_ss. The SNPs are contained in this
data frame according to their significance, with the most significant SNP,
i.e. the SNP with the largest absolute \(z\)-statistic, now located in the
first row of the data frame.
Forde, A., Hemani, G., & Ferguson, J. (2023). Review and further developments in statistical corrections for Winner’s Curse in genetic association studies. PLoS Genetics, 19(9), e1010546.
https://amandaforde.github.io/winnerscurse/articles/winners_curse_methods.html
for illustration of the use of BR_ss with a toy data set and further
information regarding the computation of the adjusted SNP-trait association
estimates.