Differential latent-variable activity between sample groups

For each row of a CLAMP B matrix, compares mean activity in a reference sample group against all other samples using a Wilcoxon rank-sum test, with Benjamini–Hochberg FDR adjustment.

Usage

differentialLVActivity(
  x,
  metadata,
  sample_col = "id",
  group_col = "type",
  reference
)

Arguments

x: A CLAMP result list (with element B) or a numeric matrix with latent variables in rows and samples in columns.
metadata: Data frame with sample identifiers and group labels.
sample_col: Name of the column in metadata holding sample identifiers matching colnames(B).
group_col: Name of the column in metadata holding group labels.
reference: Label of the reference group. All other samples are treated as the comparison group.

Value

A data frame with one row per latent variable, ordered by FDR. Columns: LV, Mean_Reference, Mean_Comparison, Mean_Diff, P_Value, FDR.

Examples

B <- matrix(rnorm(30), nrow = 3)
rownames(B) <- paste0("LV", seq_len(3))
colnames(B) <- paste0("S", seq_len(10))
meta <- data.frame(
    id = colnames(B),
    type = rep(c("Control", "Case"), each = 5)
)
differentialLVActivity(B, meta, reference = "Control")
#>      LV Mean_Reference Mean_Comparison  Mean_Diff   P_Value       FDR
#> LV1 LV1     0.09618778     -0.41251441 -0.5087022 0.3095238 0.4642857
#> LV3 LV3    -0.63789922     -0.13613513  0.5017641 0.3095238 0.4642857
#> LV2 LV2     0.25218352     -0.02508714 -0.2772707 0.6904762 0.6904762