evaluate_mad: Evaluate MAD

In shdam/cyCombine: Robust integration of single-cell cytometry datasets within and across technologies

Evaluate MAD

Description

The function computes the Median Absolute Deviation of the two given datasets. Then the reduction is calculated as the relative change in total MAD.

Usage

evaluate_mad(
  uncorrected,
  corrected,
  cell_col = "label",
  batch_col = "batch",
  markers = NULL,
  filter_limit = NULL
)

Arguments

uncorrected	Dataframe of uncorrected data
corrected	Dataframe of corrected data
cell_col	Column name of df that contains cell population labels (or clusters)
batch_col	Column name of df that contains batch numbers
markers	Vector of the markers to calculate EMD for. If NULL, get_markers will be used to find markers
filter_limit	Limit for MAD removal (Removing MADs that are below or equal to filter_limit in both before and after correction). Default filters none of the values.

See Also

Other mad: compute_mad()

shdam/cyCombine documentation built on June 12, 2022, 11:29 p.m.