Extract variants common to all GWAS studies

Opens multiple parquet files, filters to variants with minor allele frequency above maf_threshold, and returns only variants present in every file. Optionally selects one variant per megabase window per chromosome for LD-thinned analyses.

Usage

extract_common_variants(
  parquet_files,
  trait_type,
  maf_threshold = 0.05,
  select_per_mb_window = FALSE,
  window_size_mb = 1,
  seed = NULL,
  eaf_col = EAF,
  chr_col = CHR,
  pos_col = POS_38,
  rsid_col = RSID,
  ea_col = EffectAllele,
  oa_col = OtherAllele,
  n_col = N
)

Arguments

parquet_files

Character vector of paths to parquet files.

trait_type

"binary" or "quantitative" (required).

maf_threshold

Minimum minor allele frequency. Default 0.05.

select_per_mb_window

Logical; if TRUE, select one variant per window_size_mb Mb window per chromosome. Default FALSE.

window_size_mb

Window size in megabases for thinning. Default 1.

seed

Random seed for reproducible window selection. Default NULL.

eaf_col

Bare column name for EAF. Default EAF.

chr_col

Bare column name for chromosome. Default CHR.

pos_col

Bare column name for position. Default POS_38.

rsid_col

Bare column name for rsid. Default RSID.

ea_col

Bare column name for effect allele. Default EffectAllele.

oa_col

Bare column name for other allele. Default OtherAllele.

n_col

Bare column name for N. Default N.

Value

A tibble::tibble() with columns file, chromosome, position, rsid, effect allele, other allele, and minor_af. One row per variant × study combination.

Details

Extract common variants present in all studies

Examples

if (FALSE) { # \dontrun{
common <- extract_common_variants(
  parquet_files = c("study1.parquet", "study2.parquet"),
  trait_type    = "binary"
)
} # }