Skip to contents

Post-process SuSiE Analysis Results

Source: R/susie_wrapper.R
susie_post_processor.Rd

This function processes the results from SuSiE (Sum of Single Effects) genetic analysis. It extracts and processes various statistics and indices based on the provided SuSiE object and other parameters. The function can operate in 3 modes: 'susie', 'susie_rss', 'mvsusie', based on the method used for the SuSiE analysis.

Usage

susie_post_processor(
  susie_output,
  data_x,
  data_y,
  X_scalar,
  y_scalar,
  maf = NULL,
  secondary_coverage = c(0.5, 0.7),
  signal_cutoff = 0.1,
  other_quantities = NULL,
  prior_eff_tol = 1e-09,
  min_abs_corr = 0.8,
  mode = c("susie", "susie_rss", "mvsusie")
)

Arguments

susie_output

Output from running susieR::susie() or susieR::susie_rss() or mvsusieR::mvsusie()

data_x

Genotype data matrix for 'susie' or Xcorr matrix for 'susie_rss'.

data_y

Phenotype data vector for 'susie' or summary stats object for 'susie_rss' (a list contain attribute betahat and sebetahat AND/OR z). i.e. data_y = list(betahat = ..., sebetahat = ...), or NULL for mvsusie

X_scalar

Scalar for the genotype data, used in residual scaling.

y_scalar

Scalar for the phenotype data, used in residual scaling.

maf

Minor Allele Frequencies vector.

secondary_coverage

Vector of coverage thresholds for secondary conditional analysis.

signal_cutoff

Cutoff value for signal identification in PIP values.

other_quantities

A list of other quantities to be added to the final object.

prior_eff_tol

Prior effective tolerance.

min_abs_corr

Minimum absolute correlation for credible set purity filtering. Default is 0.8, which is stricter than the susieR default of 0.5. Credible sets with purity below this threshold are excluded from the results.

mode

Specify the analysis mode: 'susie' or 'susie_rss'.

Value

A list containing modified SuSiE object along with additional post-processing information.

Examples

# Example usage for SuSiE
# result <- susie_post_processor(susie_output, X_data, y_data, maf, mode = "susie")
# Example usage for SuSiE RSS
# result <- susie_post_processor(susie_output, Xcorr, z, maf, mode = "susie_rss")