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Score a published polygenic-score panel on a dosage matrix

Source: R/instruments_exposure.R
score_pgs_panel.Rd

Applies a published set of per-variant weights (e.g. a PGS Catalog scoring file, which is already LD-aware) directly to a genotype dosage matrix. Matching is by chr:pos:ref:alt key (with automatic allele-flip handling: when the genotype stores the opposite orientation, the weight is negated) or by rsID when present.

Usage

score_pgs_panel(weights, genotypes, impute_mean = TRUE, scale_score = TRUE)

Arguments

weights

A data.frame of variant weights. Recognized columns: chr/chr_name, pos/chr_position, a1/effect_allele, a0/other_allele, weight/effect_weight, and optionally rsid. PGS Catalog scoring files can be read directly with utils::read.delim() (skip the header comment lines).

genotypes

A numeric dosage matrix (variants x samples, dosages in 0-2) whose rownames are either chr:pos:ref:alt keys or rsIDs matching weights. A bigsnpr::snp_attach() bigSNP object is also accepted (requires bigsnpr).

impute_mean

Logical: mean-impute missing dosages per variant. Default TRUE.

scale_score

Logical: scale the resulting score to mean 0 / sd 1. Default TRUE.

Value

A list with:

score

named numeric vector of per-sample scores.

matched

data.frame of matched variants with the weights used (after any flip correction).

n_input

number of weight-panel variants.

Examples

# Toy dosage matrix: 4 variants x 50 samples
dos <- matrix(rbinom(4 * 50, 2, 0.3), nrow = 4,
              dimnames = list(c("1:100:A:G", "1:200:C:T",
                                "1:300:G:A", "2:400:T:C"),
                              paste0("S", 1:50)))
wts <- data.frame(chr = c(1, 1, 2), pos = c(100, 300, 400),
                  a1 = c("A", "G", "T"), a0 = c("G", "A", "C"),
                  weight = c(0.1, -0.2, 0.05))
out <- score_pgs_panel(wts, dos)
plot(out$score)