Compute distance matrices

Calculates distance matrices for every valid input value of argument method_dist and stores the results in the celltracer object. Requires that initiateHierarchicalClustering() has been called.

computeDistanceMatrices(
  object,
  variable_set,
  phase = NULL,
  method_dist = NULL,
  force = FALSE,
  p = 2,
  verbose = NULL
)

Arguments

object	A valid cypro object.
variable_set	Character value. Denotes the variable set of interest. Use getVariableSetNames() to obtain all names of currently stored variable sets in your object.
phase	Character or numeric. If character, the ordinal value referring to the phase of interest (e.g. 'first', 'second' etc.). referring to the phase of interest or 'all'. If numeric, the number referring to the phase. If set to NULL takes the phase denoted as default with adjustDefault(). Ignored if the experiment design contains only one phase.
method_dist	Character vector (or value see details for more.) Denotes the distance method(s) of interest (e.g. 'euclidean' or 'manhattan'). Use validDistanceMethods() to obtain all valid input options.
force	Logical value. Needs to be set to TRUE if you want to overwrite an already existing set up or already existing results.
verbose	Logical. If set to TRUE informative messages regarding the computational progress will be printed. (Warning messages will always be printed.)

Value

An updated version of the input cypro-object.

Details

computeDistanceMatrices() is the second step in the convenient hierarchical clustering of celltracer. It calculates the distance matrices according to all methods you are interested in in a loop. Argument method_dist therefore either takes a value or a vector of valid character strings. Each input value is given to argument method of function stats::dist().

Based on the distance matrices computed and saved this way the function agglomerateHierarchicalCluster() can be used as the third step of the hierarchical clustering pipeline.