ComputeCellData

Computes a per-cell pathway activation score by measuring each cell's distance to the pathway ON and OFF reference states from PathwayMaxMin(). Scores are normalized to [0, 1]\, where 1 indicates proximity to the ON state and 0 indicates proximity to the OFF state.

Usage

ComputeCellData(expr_data, pathway.stat, distance.method = "manhattan")

Arguments

expr_data

A z-scored gene-by-cell numeric matrix, e.g. from DataPreProcess().

pathway.stat

A data frame from PathwayMaxMin() with columns pathway.on and pathway.off. Rownames must be gene symbols.

distance.method

Character string specifying the distance metric. One of "manhattan" (default) or "euclidean".

Value

A named numeric vector of length equal to the number of cells, with scores in [0, 1]. A score near 1 indicates the cell is close to the ON state; a score near 0 indicates proximity to the OFF state. Cells where both distances are 0 return NaN with a warning.

Examples

if (FALSE) { # \dontrun{
pathwaydata   <- LoadPathway("Hypoxia_6hr", "human")
expr_filtered <- DataPreProcess(norm_matrix, pathwaydata)
pathway_stat  <- PathwayMaxMin(expr_filtered, pathwaydata)
scores        <- ComputeCellData(expr_filtered, pathway_stat)
} # }