Skip to contents

PolyFun: Munge summary stats

Source: R/POLYFUN_munge_summ_stats.R
POLYFUN_munge_summ_stats.Rd

Munge summary statistics using the PolyFun implementation of the LDSSC munge sum stats python script (munge_polyfun_sumstats.py). NOTE: This script is kept only for documentation purposes. Please use MungeSumstats instead as it is far more robust.

Usage

POLYFUN_munge_summ_stats(
  fullSS_path,
  polyfun_path = NULL,
  locus_dir = tempdir(),
  sample_size = NULL,
  min_INFO = 0,
  min_MAF = 0.001,
  chi2_cutoff = 30,
  keep_hla = FALSE,
  no_neff = FALSE,
  force_new_munge = FALSE,
  conda_env = "echoR_mini",
  verbose = TRUE
)

Source

fullSS_path <- echodata::example_fullSS() munged_path <- POLYFUN_munge_summ_stats(fullSS_path=fullSS_path)

Arguments

fullSS_path

Path to the full summary statistics file (GWAS or QTL) that you want to fine-map. It is usually best to provide the absolute path rather than the relative path.

polyfun_path

[Optional] Path to PolyFun directory where all the executables and reference data are stored. Will be automatically installed if set to NULL (default).

locus_dir

Locus-specific directory to store results in.

conda_env

Conda environment to use.

verbose

Print messages.

See also

Other polyfun: POLYFUN(), POLYFUN_compute_priors(), POLYFUN_download_ref_files(), POLYFUN_find_folder(), POLYFUN_finemapper(), POLYFUN_gather_annotations(), POLYFUN_gather_ldscores(), POLYFUN_help(), POLYFUN_import_priors(), POLYFUN_initialize(), POLYFUN_prepare_snp_input(), POLYFUN_run_ldsc()