RAS-package: RAS: Regional Association Score for Genome-Wide Association...

In RAS: Regional Association Score for Genome-Wide Association Studies

RAS: Regional Association Score for Genome-Wide Association Studies

Description

The RAS package implements the Regional Association Score method for genome-wide association studies. It converts per-SNP effect sizes into a genomic -\log_{10}(p) time series and applies changepoint detection to locate peaks that mark significant association regions. The method supports both continuous and binary traits.

Option A — one call (recommended)

ras runs the complete pipeline and returns a "ras" object; use plot.ras to visualise results.

result <- ras(geno, phenotype, covariates,
              covariate_cols = c("age", "sex", paste0("pc", 1:10)),
              is_continuous  = TRUE,
              chrom = 1, save_dir = "results/")

print(result)             # detected changepoint positions
plot(result)              # full-chromosome scan profile
plot(result, zoom = TRUE) # zoomed view around each changepoint

Option B — step-by-step (advanced)

ras_scan \to ras_detect \to ras_validate \to plot.ras

## Step 1: compute averaged -log10(p) profile
scan     <- ras_scan(geno, phenotype, covariates,
                     covariate_cols = c("age", "sex", paste0("pc", 1:10)),
                     is_continuous = TRUE, chrom = 1, save_dir = "results/")

## Step 2: first-pass changepoint detection
detected <- ras_detect(scan$x, scan$y,
                       window_size = 3000,
                       slope.p.values.threshold.left  = 1e-10,
                       slope.p.values.threshold.right = 1e-20)

## Step 3: second-pass validation
final    <- ras_validate(detected, x = scan$x, y = scan$y,
                         this.skip = 10, p.value.threshold = 1e-10)

## Step 4: plot
result   <- structure(
  list(scan = scan, detection = final, chrom = 1, save_dir = "results/"),
  class = "ras")

plot(result)
plot(result, zoom = TRUE)

Stage 1 — Scan

ras_scan performs num_rep independent 50/50 train/hold-out splits. In each repetition it fits per-SNP regressions on the training half (compute_gwas_weights), builds a weighted dosage matrix for the hold-out half (compute_pgs_matrix), and runs a forward scan (screen_forward_max_region) that slides an expanding window and records the minimum p-value at each grid position. The -\log_{10}(p) vectors are averaged across repetitions. For continuous traits, covariates are residualised from the training phenotype each repetition (no hold-out leakage); for binary traits, logistic regression is used in the scan step.

Stage 2 — First-pass changepoint detection

ras_detect slides a window of width cp_window_size across the profile. At each position get_break_points fits a segmented linear model and applies the Davies test. A candidate is retained only when three conditions all hold: Davies p < cp_p_threshold, left-side slope significantly positive (slope_test, p < cp_slope_left), and right-side slope significantly negative (p < cp_slope_right). Each accepted candidate is snapped to the nearest local peak via get_local_maximum.

Stage 3 — Second-pass validation

ras_validate re-tests each first-pass candidate with local Davies tests on both sides within a window of half-width second_window_size. A candidate is accepted if either side passes p < second_p_threshold. Candidates with -\log_{10}(p) \le min_signal at the estimated position are discarded regardless.

Stage 4 — Plots

plot.ras with zoom = FALSE produces two files: the RAS scan profile with detected changepoints highlighted, and a dual-axis overlay with Davies test significance at every candidate. plot.ras with zoom = TRUE produces a multi-panel figure with one zoomed panel per changepoint.

Author(s)

Jiahe Jin [e-mail] (maintainer), Yiran Jiang [e-mail], Heping Zhang [e-mail]

See Also

• compute_gwas_weights

• compute_pgs_matrix

• get_break_points

• get_local_maximum

• plot.ras

• print.ras

• ras

• ras_detect

• ras_memory

• ras_scan

• ras_validate

• release_memory

• screen_forward_max_region

• slope_test

RAS documentation built on July 24, 2026, 5:06 p.m.