spatialTIME: ripleys_k – R documentation

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ripleys_k

Calculate Univariate Ripley's K function for IF data

Description

This function calculates Ripley's K function of IF data to characterize correlation of spatial point process using tranlation and isotropic edge correction method.

Usage

ripleys_k(
  mif,
  id,
  mnames,
  r_range = seq(0, 100, 50),
  num_permutations = 50,
  edge_correction = "translation",
  kestimation = TRUE,
  keep_perm_dis = FALSE,
  mlabels = NULL
)

Arguments

`mif`	An MIF object
`id`	Character string of variable name for subject ID in TMA data.
`mnames`	Character vector of marker names to calculate Ripley's K on.
`r_range`	Numeric vector of potential r values to estimate K at.
`num_permutations`	Numeric value indicating the number of permutations used. Default is 50.
`edge_correction`	Character value indicating the type of edge correction to use. Options include "translation", "isotropic" or "border". Various edges corrections are most appropriate in different settings. Default is "translation".
`kestimation`	Logical value determining the type estimation performed. TRUE estimates Ripley's reduced second moment function while FALSE estimates Besags's transformation of Ripley's K.
`keep_perm_dis`	Logical value determining whether or not to keep the full distribution of permuted K values
`mlabels`	Character vector of label for marker names to display in the marker column.

Value

Returns a list

`r`	Subject ID in TMA data
`theo`	Ripley's K estimate

spatialTIME

Spatial Analysis of Vectra Immunoflourescent Data

v1.0.0

MIT + file LICENSE

Authors

Jordan Creed [aut], Ram Thapa [aut], Christopher Wilson [aut], Brooke Fridley [cph], Fridley Lab [cre]

Initial release