Also inspired by MSKCC SPECTRUM paper. Using the measured pairwise bin
distances between cells (dlptools::pairwise_bin_differences()), this
function takes the nearest neighbour of each cell and fits a beta
distribution. Then using this distribution, it finds outlier cells based on
a selected percentile of the distribution (default 99th).
Usage
find_outlier_cells(cell_diffs, outlier_percentile = 0.99)
Arguments
- cell_diffs
the dataframe of differences from
dlptools::pairwise_bin_differences()
- outlier_percentile
double. Default 0.99. What percentile of the
distribution to consider an outlier cell.
Value
NA or tibble of information on cells considered outliers. NA if no outliers found.