Calculate MR-MEGA MDS coordinates from allele frequency data — calculate_mr_mega

Computes multidimensional scaling (MDS) coordinates from study-level effect allele frequency (EAF) data. The approach follows the MR-MEGA method (Mägi et al. 2017): a population-genetic distance matrix is computed from EAF values, double-centred, and decomposed via SVD to produce principal coordinates.

Usage

calculate_mr_mega_mds(
  common_variants_data,
  pcCount = 4,
  chr_col = CHR,
  pos_col = POS_38,
  rsid_col = RSID,
  ea_col = EffectAllele,
  oa_col = OtherAllele,
  eaf_col = minor_af,
  file_col = file
)

Arguments

common_variants_data: A data frame (long format) with one row per variant × study combination. Must contain columns identified by chr_col, pos_col, ea_col, oa_col, eaf_col, and file_col. Typically the output of extract_common_variants().
pcCount: Number of principal coordinates to return. Default 4.
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.
eaf_col: Bare column name for EAF. Default minor_af.
file_col: Bare column name for study/file identifier. Default file.

Value

A named list with elements:

pc_coordinates: Data frame of MDS coordinates (pcCount columns).
distance_matrix: Population-genetic distance matrix.
centered_distance_matrix: Double-centred distance matrix.
eigenvalues: Eigenvalues from SVD.
eaf_matrix: Wide EAF matrix (variants × studies).
used_variants: Variants with complete EAF data.
studies: Character vector of study names.
summary: List with n_studies, n_variants_used, n_variants_total, pc_count.

Details

Calculate MR-MEGA multidimensional scaling coordinates

References

Mägi R, et al. (2017). Trans-ethnic meta-regression of genome-wide association studies accounting for ancestry increases power for discovery and improves fine-mapping resolution. Hum Mol Genet, 26(18), 3639–3650.

Examples

if (FALSE) { # \dontrun{
common <- extract_common_variants(files, trait_type = "binary")
mds    <- calculate_mr_mega_mds(common)
} # }