R/data.R

In KotulskaLab/AmyloGraph: AmyloGraph: a comprehensive database of amyloid-amyloid interactions

#' AmyloGraph interactions list
#' 
#' @return `data.frame` coming from `interactions_data.csv` file with the
#' following changes:
#' * `from_id` and `to_id` are unique hashes of interactor and interactee names,
#' * `interactor_sequence` and `interactee_sequence` are transformed with
#'   \code{\link{read_chains}()} to a vector of tibbles.
#' 
#' @importFrom digest digest
#' @importFrom dplyr mutate
#' @importFrom purrr map_chr map
#' @importFrom readr read_csv
#' @export
ag_data_interactions <- NULL

if (packageVersion("rlang") >= "1.0.0") {
  rlang::on_load({
    ag_data_interactions <- read_csv(
      system.file("AmyloGraph", "interactions_data.csv", package = "AmyloGraph"),
      col_types = "ccccfffcccccc"
    ) %>%
      mutate(from_id = map_chr(interactor_name, digest),
             to_id = map_chr(interactee_name, digest),
             interactor_sequence = map(interactor_sequence, read_chains),
             interactee_sequence = map(interactee_sequence, read_chains),
             AGID_button = AGID_button(AGID))
  })
}

#' Build list of proteins from interactions list
#' 
#' @return `data.frame` with a list of proteins that interact with others,
#' described with `label` (human-readable name), `id` (machine-readable name),
#' and `shape` (for the purpose of drawing a graph only).
#' 
#' @importFrom digest digest
#' @importFrom dplyr select tibble
#' @importFrom purrr map_chr
ag_data_nodes <- NULL

if (packageVersion("rlang") >= "1.0.0") {
  rlang::on_load({
    ag_data_nodes <- ag_data_interactions %>%
      select(interactor_name, interactee_name) %>% 
      unlist() %>% 
      unique() %>% 
      tibble(label = .,
             id = map_chr(label, digest),
             shape = "box")
  })
}

#' @importFrom purrr map map_chr
#' @rdname ag_data_attributes
ag_data_group_labels <- NULL

#' @rdname ag_data_attributes
ag_data_attribute_values <- NULL

#' @rdname ag_data_attributes
ag_data_color_map <- NULL

if (packageVersion("rlang") >= "1.0.0") {
  rlang::on_load({
    interaction_attrs <- ag_option("interaction_attrs")
    
    ag_data_group_labels <- interaction_attrs %>%
      map_chr(text_label_attribute) %>%
      setNames(interaction_attrs) %>%
      invert_names()
    
    # TODO: implement & use napply() or nmap() for named return
    ag_data_attribute_values <- setNames(map(
      interaction_attrs,
      ~ sort(unique(ag_data_interactions[[.x]]))
    ), interaction_attrs)
    
    ag_data_color_map <- map(
      ag_data_attribute_values,
      ~ setNames(ag_option("palette")[seq_along(.x)], .x)
    )
    
    rm(interaction_attrs)
  })
}

#' AmyloGraph proteins list
#' 
#' @return `data.frame` coming from `protein_data.csv` file with the
#' following changes:
#' * `id` contains unique hashes of protein names.
#' 
#' @importFrom digest digest
#' @importFrom dplyr mutate
#' @importFrom purrr map_chr
#' @importFrom readr read_csv
ag_data_proteins <- NULL

if (packageVersion("rlang") >= "1.0.0") {
  rlang::on_load({
    ag_data_proteins <- read_csv(
      system.file("AmyloGraph", "protein_data.csv", package = "AmyloGraph"),
      col_types = "ccc"
    ) %>%
      mutate(id = map_chr(name, digest))
  })
}

#' AmyloGraph references list
#' 
#' @return `data.frame` coming from `reference_table.csv` file with no changes.
#' 
#' @importFrom readr read_csv
#' @export
ag_data_references <- NULL

if (packageVersion("rlang") >= "1.0.0") {
  rlang::on_load({
    ag_data_references <- read_csv(
      system.file("AmyloGraph", "reference_table.csv", package = "AmyloGraph"),
      col_types = "cccccn"
    )
  })
}