Takes data from load_results() and appends columns used for plotting results.

augment_results(data, alpha)

Arguments

data

data.table from load_results().

alpha

significance level used for hypothesis tests.

Value

A data.table containing the new appended results.

Details

This function requires that this data has been loaded with load_results().
It generates new columns for all columns that represent p-values generated by analysis_association(). One of the columns, having "_significant" as its suffix, denotes whether or not the p-value is significant at the specified alpha level. The other column, having "_bonferroni" as suffix, denotes whether the p-value is significant with Bonferroni-corrected alpha level.
Furthermore, the user is prompted to decide if they want to create a column named "causal", which denotes whether or not a SNP is truly causal for the phenotype status of an individual. The user needs to have loaded "beta.txt" with load_results() in order to create this column.
Lastly, the user is prompted to decide if they want to create a column named "LTFH_transformed", which is the estimated effect sizes of a regression using the LT-FH phenotype transformed to the liability scale.
Transforming the effect sizes requires that the user has loaded results from analysis_association() with both pheno_name = "line_pheno" and pheno_name = "LTFH_pheno". These need to be laoded with load_results() along with MAFs.txt.