getTable() can be used to generate frequently used parameters on cell populations defined by clustering or prediction, while considering a meta variable for grouping. It can produce cell numbers (counts), cell population frequencies as well as median or mean marker expression for each group to cell population combination.
Usage
getTable(
fcd,
output_type = "frequency",
expr_slot = "orig",
cluster_slot,
cluster_var,
group_var,
numeric = F
)Arguments
- fcd
flow cytometry data set, that has been subjected to clustering or cell type label prediction with cyCONDOR
- output_type
type of parameter that should be reported in table. One of the following option needs to be selected:
"counts" : gives cell numbers per group_var and cell population
"frequency" : returns proportion of each cell population for each level in group_var (default)
"median": calculates median expression for each group_var and cell population combination for each available feature in expression matrix
"mean": calculates mean expression for each group_var and cell population combination for each available feature in expression matrix
- expr_slot
expr_slot from which to take marker expression values, default is "orig". Corrected input data should be handled cautiously.
- cluster_slot
string specifying which clustering slot to use to find variable specified in cluster_var
- cluster_var
string specifying variable name in cluster_slot that identifies cell population labels to be used (e.g. clusters, metaclusters or predicted labels).
- group_var
string indicating variable name in cell_anno that should be used to group the output, e.g. group or sample ID.
- numeric
logical, if TRUE numeric levels in cluster_var are ordered in increasing order and "Cluster_" is pasted before number, if FALSE alphabetical ordering is applied.
Value
getTable() returns a data frame with parameters in columns and observations in rows. In case of output_type of "counts" or "frequency", counts and frequencies for each cell population (columns) are reported in one row for each level in group_var. Given an output_type of "mean" or "median", aggregated expression for each feature (columns) is reported for each group_var and cell population combination (cluster).