profile_cluster_DEG_permute

Permutation Null Distribution for Profile-Based Differential Expression

Usage

profile_cluster_DEG_permute(P, G, dpt, n = 50)

Arguments

P

A matrix of soft profile assignments for each cell (cells × 2, typically: target vs. control).

G

A gene expression matrix (genes × cells).

dpt

A numeric pseudotime vector (length = number of columns in `G`).

n

Integer. Number of permutations (default: 50).

Value

A list of p-value vectors (one per permutation) representing the null distribution.

Details

Computes a null distribution of p-values for profile-based differential gene expression by repeatedly permuting the soft profile assignment matrix. This supports empirical calibration of DE gene significance in pseudotime analysis.

Examples

# Simulated example
G <- matrix(rnorm(5000), nrow = 100)
P <- matrix(runif(200), nrow = 100)
P <- cbind(target = P[, 1], control = 1 - P[, 1])
dpt <- seq(0, 1, length.out = 100)
null_pvals <- profile_cluster_DEG_permute(P, G, dpt, n = 10)
#> Error in profile_cluster_DEG_permute(P, G, dpt, n = 10): could not find function "profile_cluster_DEG_permute"
length(null_pvals)
#> Error in eval(expr, envir, enclos): object 'null_pvals' not found