params <-
list(test = FALSE)

## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
library(BiocStyle)

## ----warning = FALSE, message = FALSE-----------------------------------------
# Loading required packages
library(Statial)
library(tidyverse)
library(SingleCellExperiment)

theme_set(theme_classic())

## ----eval = FALSE-------------------------------------------------------------
#  # Install the package from Bioconductor
#  if (!requireNamespace("BiocManager", quietly = TRUE)) {
#    install.packages("BiocManager")
#  }
#  BiocManager::install("Statial")

## -----------------------------------------------------------------------------
# Load head and neck data
data("headSCE")

# Examine all cell types in image
unique(headSCE$cellType)

# Set up cell populations
tumour <- c("SC1", "SC2", "SC3", "SC4", "SC5", "SC6", "SC7")

bcells <- c("BC1", "BC2", "BC3")
tcells <- c("TC_CD4", "TC_CD8")
myeloid <- c("MC1", "MC2", "MC3")

endothelial <- c("EC1", "EC2")
epithelial <- c("EP")

tissue <- c(endothelial, epithelial)
immune <- c(bcells, tcells, myeloid, "GC") # GC = granulocytes

all <- c(tumour, tissue, immune, "Undefined")

## -----------------------------------------------------------------------------
CD4_Konditional <- Konditional(
  cells = headSCE,
  r = 50,
  from = "TC_CD4",
  to = "SC1",
  parent = immune,
  cores = 1
)

head(CD4_Konditional)

## ----fig.wide = TRUE----------------------------------------------------------

ggplot(CD4_Konditional, aes(x = original, y = konditional, col = imageID)) +
  geom_point(size = 2) +
  geom_hline(yintercept = 0, col = "red", linetype = "dashed") +
  geom_vline(xintercept = 0, col = "red", linetype = "dashed") +
  theme(
    axis.title.x = element_text(size = 14),
    axis.text.x = element_text(size = 10),
    axis.text.y = element_text(size = 10),
    axis.title.y = element_text(size = 14)
  )

## -----------------------------------------------------------------------------
# Get all relationships between cell types and their parents
parentDf <- parentCombinations(
  all = all,
  tumour,
  bcells,
  tcells,
  myeloid,
  endothelial,
  epithelial,
  tissue,
  immune
)
head(parentDf)

## -----------------------------------------------------------------------------
# Selecting Image 1 as an example
image_1 <- headSCE |>
  colData() |>
  data.frame() |>
  filter(imageID == "1")


image1_Konditional <- Konditional(
  cells = image_1,
  parentDf = parentDf[1:20, ],
  r = 50,
  cores = 1
)

head(image1_Konditional)

## -----------------------------------------------------------------------------
data("kerenImage")

kerenImage |>
  filter(cellType %in% c("Keratin+Tumour", "Immune", "p53")) |>
  arrange(cellType) |>
  ggplot(aes(x = x, y = y, color = cellType)) +
  geom_point(size = 1) +
  scale_colour_manual(values = c("#505050", "#D6D6D6", "#64BC46"))

## -----------------------------------------------------------------------------
rsDf <- rsCurve(
  cells = kerenImage,
  from = "p53",
  to = "Immune",
  parent = c("p53", "Keratin+Tumour"),
  rs = seq(10, 510, 100),
  cores = 1
)


ggplotRs(rsDf)

## -----------------------------------------------------------------------------
sessionInfo()