getKsPCAData {funkycells}

Get K Functions and Compute Principal Components

Description

This function computes K functions from point process data then converts it into PCs. Note, if there are replicates, i.e. multiple observations per unit, the K functions will be a weighted average based on the number of the first agents.

Usage

getKsPCAData(
  data,
  outcome = colnames(data)[1],
  unit = colnames(data)[5],
  replicate = NULL,
  rCheckVals = NULL,
  nPCs = 3,
  agents_df = as.data.frame(expand.grid(unique(data[, 4]), unique(data[, 4]))),
  xRange = NULL,
  yRange = NULL,
  edgeCorrection = "isotropic",
  nbasis = 21,
  silent = FALSE,
  displayTVE = FALSE
)

Arguments

data

Data.frame with column titles for at least outcome, x, y, agents, and unit. For consistency (and avoiding errors), use that order. Additionally, replicate can be added.

outcome

(Optional) String of the column name in data indicating the outcome or response. Default is the 1st column.

unit

(Optional) String of the column name in data indicating a unit or base thing. Note this unit may have replicates. Default is the 4th column.

replicate

(Optional) String of the column name in data indicating the replicate id. Default is NULL.

rCheckVals

(Optional) Numeric vector indicating the radius to check. Note, if not specified, this could take a lot of memory, particularly with many units and replicates.

nPCs

(Optional) Numeric indicating the number of principal components.

agents_df

(Optional) Two-column data.frame. The first for agent 1 and the second for agent 2. Both should be in data agents column. This determines which K functions to compute. Default is to compute all, but may be misspecified if the data is in a different order.

xRange, yRange

(Optional) Two value numeric vector indicating the min and max x/y values. Note this is re-used for all replicates. The default just takes the min and max x from each replicate. This allows different sized images, but the edges are defined by some agent location.

edgeCorrection

(Optional) String indicating type of edgeCorrection(s) to apply when computing the K functions. Options include: "border", "bord.modif", "isotropic", "Ripley", "translate", "translation", "periodic", "none", "best" or "all" selects all options.

nbasis

(Optional) Numeric indicating number of basis functions to fit K functions in order to compute PCA. Current implementation uses a b-spline basis.

silent

(Optional) Boolean indicating if progress should be printed.

displayTVE

(Optional) Boolean to indicate if total variance explained (TVE) should be displayed. Default is FALSE.

Value

Data.frame with the outcome, unit and principle components of computed K functions.

Examples

dataPCA_pheno <- getKsPCAData(
  data = TNBC_pheno, unit = "Person",
  agents_df = data.frame(rep("B", 2), c("Tumor", "Fake")),
  nPCs = 3,
  rCheckVals = seq(0, 50, 1),
  displayTVE = TRUE
)