Plot the U matrix (pathway-LV associations) as a heatmap

Displays the pathway loading matrix U after filtering by AUC and FDR thresholds. Only the top-top pathways per LV are shown.

CLAMPplotU(
  clampRes,
  auc.cutoff = 0.6,
  fdr.cutoff = 0.05,
  indexCol = NULL,
  indexRow = NULL,
  top = 3,
  sort.row = FALSE,
  cluster.rows = TRUE
)

Arguments

clampRes

A CLAMP result list containing at least U, Uauc, Up, and summary.

auc.cutoff

Minimum AUC threshold; entries below this are set to zero. Default 0.6.

fdr.cutoff

Maximum FDR threshold for pathway significance filtering. Default 0.05.

indexCol

Integer vector of LV column indices to include. NULL uses all LVs.

indexRow

Integer vector of pathway row indices to include. NULL uses all pathways.

top

Number of top pathways to retain per LV. Default 3.

sort.row

Logical; if TRUE, rows are sorted by the dominant LV. Default FALSE.

cluster.rows

Logical; if TRUE (default), rows are reordered by hierarchical clustering (overridden when sort.row = TRUE).

Value

Invisibly returns a ggplot2::ggplot() object.

Examples

set.seed(42)
pathways <- paste0("Path", 1:30)
lvs <- paste0("LV", 1:5)

U <- matrix(abs(rnorm(30 * 5)),
    nrow = 30,
    dimnames = list(pathways, lvs)
)
Uauc <- matrix(runif(30 * 5, 0.5, 1.0),
    nrow = 30,
    dimnames = list(pathways, lvs)
)
Up <- matrix(runif(30 * 5, 0, 3),
    nrow = 30,
    dimnames = list(pathways, lvs)
)

# Build a minimal summary table
nr <- 30 * 5
summ <- data.frame(
    pathway = rep(pathways, 5),
    LV = rep(lvs, each = 30),
    AUC = as.vector(Uauc),
    p_value = runif(nr, 0, 0.1),
    FDR = runif(nr, 0, 0.1),
    stringsAsFactors = FALSE
)

clampRes <- list(U = U, Uauc = Uauc, Up = Up, summary = summ)
CLAMPplotU(clampRes, auc.cutoff = 0.6, fdr.cutoff = 0.1, top = 3)