view celesta_plot_expression.R @ 1:44d4c885d9b5 draft

planemo upload for repository https://github.com/goeckslab/tools-mti/tree/main/tools/celesta commit 1f02a762ab43a29aa7f59760798ff084f86e37db

# --------------------------------------------------------------------------------------------
# Plot marker expression probabilities for cell assignment parameter optimization with CELESTA
# --------------------------------------------------------------------------------------------

suppressWarnings(suppressMessages(library(janitor)))
suppressWarnings(suppressMessages(library(optparse)))
suppressWarnings(suppressMessages(library(dplyr)))
suppressWarnings(suppressMessages(library(anndataR)))
suppressWarnings(suppressMessages(library(Rmixmod)))
suppressWarnings(suppressMessages(library(spdep)))
suppressWarnings(suppressMessages(library(ggplot2)))
suppressWarnings(suppressMessages(library(reshape2)))
suppressWarnings(suppressMessages(library(zeallot)))
suppressWarnings(suppressMessages(library(CELESTA)))

### Define command line arguments
option_list <- list(
  make_option(c("-i", "--imagingdata"), action = "store", default = NA, type = "character",
              help = "Path to imaging data"),
  make_option(c("-p", "--prior"), action = "store", default = NA, type = "character",
              help = "Path to prior marker info file"),
  make_option(c("-x", "--xcol"), action = "store", default = NA, type = "character",
              help = "Name of column in adata.obs containing X coordinate"),
  make_option(c("-y", "--ycol"), action = "store", default = NA, type = "character",
              help = "Name of column in adata.obs containing Y coordinate"),
  make_option(c("--filter"), action = "store_true", type = "logical", default = FALSE,
              help = "Boolean to filter cells or not (default: no filtering)"),
  make_option(c("--highfilter"), action = "store", default = 0.9, type = "double",
              help = "High marker threshold if filtering cells (default: 0.9)"),
  make_option(c("--lowfilter"), action = "store", default = 0.4, type = "double",
              help = "Low marker threshold if filtering cells (default: 0.4)"),
  make_option(c("-s", "--size"), action = "store", default = 1, type = "double",
              help = "Point size for plotting"),
  make_option(c("--width"), action = "store", default = 5, type = "integer",
              help = "Width of plot (inches)"),
  make_option(c("--height"), action = "store", default = 4, type = "integer",
              help = "Height of plot (inches)")
)

### Functions
anndata_to_celesta <- function(input_adata, x_col, y_col) {

  #' Function to convert anndata object to dataframe readable by CELESTA
  #' Coordinates columns in adata.obs are renamed to "X" and "Y", and placed at beginning of dataframe
  #' Marker intensities are concatted columnwise to the X and Y coords. cols: X,Y,Marker_1,...Marker N

  # initialize output as dataframe from adata.obs
  celesta_input_dataframe <- data.frame(input_adata$obs)

  # subset to X and Y coordinates from obs only
  celesta_input_dataframe <- celesta_input_dataframe %>%
    dplyr::select({{x_col}}, {{y_col}})

  # rename X,Y column names to what CELESTA wants
  colnames(celesta_input_dataframe) <- c("X", "Y")

  # merge X,Y coords with marker intensities from adata.X
  x_df <- data.frame(input_adata$X)
  colnames(x_df) <- input_adata$var_names
  celesta_input_dataframe <- cbind(celesta_input_dataframe, x_df)

  return(celesta_input_dataframe)
}

### Main
# parse args
opt <- parse_args(OptionParser(option_list = option_list))

# read anndata, convert to celesta format
adata <- read_h5ad(opt$imagingdata)
celesta_input_df <- anndata_to_celesta(adata, x_col = opt$xcol, y_col = opt$ycol)

# read prior marker info
prior <- read.csv(opt$prior, check.names = FALSE)

# clean prior names, keeping a copy of originals for writing output
prior_original_names <- colnames(prior)
prior <- janitor::clean_names(prior, case = "all_caps")

# clean input dataframe names
celesta_input_df <- janitor::clean_names(celesta_input_df, case = "all_caps")

# instantiate celesta object
CelestaObj <- CreateCelestaObject(
  project_title = "",
  prior_marker_info = prior,
  imaging_data_file = celesta_input_df
)

# if filtering is specified, filter out cells outside high and low thresholds
if (opt$filter) {
  print("filtering cells based on expression")
  CelestaObj <- FilterCells(CelestaObj,
                            high_marker_threshold = opt$highfilter,
                            low_marker_threshold = opt$lowfilter)
} else {
  print("Proceeding to marker expression plotting without cell filtering")
}

# create output directory if it does not already exist
dir.create("marker_exp_plots")

# plot expression probability
PlotExpProb(coords = CelestaObj@coords,
            marker_exp_prob = CelestaObj@marker_exp_prob,
            prior_marker_info = CelestaObj@prior_info,
            save_plot = TRUE,
            output_dir = "./marker_exp_plots")