% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/hit_selection.R
\name{select_hits_sigma}
\alias{select_hits_sigma}
\title{Select hits by a sigma (z-score) threshold}
\usage{
select_hits_sigma(
  data,
  score_col = "zscore_delta_auc",
  n_sigma = 3,
  direction = c("less", "greater"),
  standardize = FALSE,
  drug_col = "drug_name"
)
}
\arguments{
\item{data}{A data frame with one row per drug.}

\item{score_col}{Name of the numeric (typically already z-scored) score
column, as a string. Default \code{"zscore_delta_auc"}.}

\item{n_sigma}{Number of standard deviations defining the threshold. Default
\code{3}.}

\item{direction}{Either \code{"less"} (default, select strongly negative scores,
i.e. sensitising drugs) or \code{"greater"} (select strongly positive scores).}

\item{standardize}{Logical. If \code{TRUE}, the score column is z-scored before
thresholding; if \code{FALSE} (default) the column is assumed to already be on a
standardised (sigma) scale and is thresholded directly.}

\item{drug_col}{Name of the drug identifier column, as a string. Default
\code{"drug_name"}.}
}
\value{
The subset of \code{data} whose score is beyond the sigma threshold in the
requested direction, ordered by score.
}
\description{
Nominates drugs whose standardised score exceeds a given number of standard
deviations from the mean, in the desired direction. This implements the
sigma-based (for example 2-sigma or 3-sigma) hit-selection strategy applied
to z-scored differential AUC values.
}
\examples{
df <- data.frame(
  drug_name = paste0("Drug", 1:6),
  zscore_delta_auc = c(-3.4, -1.2, 0.1, 0.5, 1.1, -2.8)
)
select_hits_sigma(df, n_sigma = 2, direction = "less")

}
\seealso{
\code{\link[=select_hits_cutoff]{select_hits_cutoff()}}, \code{\link[=compute_delta_auc]{compute_delta_auc()}}
}
