Rescue borderline/removed cells by cluster coherence

Usage

rescue_by_coherence(
  obj,
  metrics,
  detected,
  celltype_col = "auto_celltype",
  min_cluster_size = 50,
  rescue_mode = c("none", "lenient", "moderate", "strict"),
  cancer_bypass = FALSE,
  coherence_min = NULL,
  gates_min_pass = NULL
)

Arguments

obj: Seurat object
metrics: Character vector of metric names to consider.
detected: Numeric vector of detected gene counts per cell (length = ncol(obj)).
celltype_col: optional meta column with labels (e.g. 'celltype'); if missing, label-coherence is skipped
min_cluster_size: minimum cluster size to consider for rescue (default 25)
rescue_mode: "moderate" (default), "lenient", "strict", or "none"
cancer_bypass: Logical. If TRUE, clusters with healthy splicing profiles but high removal rates are exempt from the removal-fraction penalty, allowing potential cancer cell populations to be rescued. Default FALSE.
coherence_min: Minimum coherence score required to rescue (default 0.5).
gates_min_pass: Minimum number of gates a cell must pass to be rescued (default 1).

Value

same base with possibly updated qc_status; adds rescue_flag and rescue_reason