funkycells1.1.1 package

Functional Data Analysis for Multiplexed Cell Images

computePseudoROCCurves

Compute Pseudo-ROC Curves

funkyForest

Compute a Modified Random Forest Model

funkyModel

Fit a Modified Random Forest Model with Bounds and Alignment

getCountData

Get Agent Count Data

getKFunction

Get K function

getKsPCAData

Get K Functions and Compute Principal Components

plot_K_functions

Compare K Functions Between outcomes

plotPP

Plot Spatial Point Process

predict_funkyForest

Predict a funkyForest

simulateMeta

Simulate Meta Variables

simulatePP

Simulate a Point Process

Download source packageRead PDF manual

Compare variables of interest between (potentially large numbers of) spatial interactions and meta-variables. Spatial variables are summarized using K, or other, functions, and projected for use in a modified random forest model. The model allows comparison of functional and non-functional variables to each other and to noise, giving statistical significance to the results. Included are preparation, modeling, and interpreting tools along with example datasets, as described in VanderDoes et al., (2023) <doi:10.1101/2023.07.18.549619>.

  • Maintainer: Jeremy VanderDoes
  • License: GPL (>= 3)
  • Last published: 2023-08-09

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