R/mean_expression.R
compute_mean_expression.RdFind the cells with the highest (or lowest) expression of the given parameter within the given phenotype. Report the mean expression of the high-expressing cells.
compute_mean_expression(csd, phenotype, param, percentile = NULL, count = NULL)Cell seg data to use. This should already have been filtered for the slides or fields of interest.
A phenotype selector. This will be passed to phenoptr::select_rows.
The parameter (column) to report, as a string.
The percentile cutoff for top-expressing cells. For example, to measure the top quartile, the percentile is 0.75. Negative numbers will use low-expressing cells; to measure the bottom decile, use a percentile of -0.1.
The number of top expressing cells to use. Only one of
percentile and count can be provided. If both are omitted,
the mean expression of all cells is returned.
A data frame with columns for count and mean.
Other aggregation functions:
compute_density_from_cell_summary(),
compute_density_from_table(),
compute_h_score_from_score_data(),
compute_h_score(),
compute_mean_expression_many(),
compute_positivity_many(),
compute_positivity(),
count_phenotypes(),
counts_to_percents()