maldipickr (version 1.3.1)

pick_spectra: Cherry-pick Bruker MALDI Biotyper spectra

Description

Using the clusters information, and potential additional metadata as external criteria, spectra are labeled as to be picked for each cluster. Note that some spectra and therefore clusters can be explicitly removed (masked) from the picking decision if they have been previously picked or should be discarded, using logical columns in the metadata table. If no metadata are provided, the reference spectra of each cluster will be picked.

Usage

pick_spectra(
  cluster_df,
  metadata_df = NULL,
  criteria_column = NULL,
  hard_mask_column = NULL,
  soft_mask_column = NULL,
  is_descending_order = TRUE,
  is_sorted = FALSE
)

Value

A tibble with as many rows as cluster_df with an additional logical column named to_pick to indicate whether the colony associated to the spectra should be picked. If metadata_df is provided, then additional columns from this tibble are added to the returned tibble.

Arguments

cluster_df

A tibble with clusters information from the delineate_with_similarity or the import_spede_clusters function.

metadata_df

Optional tibble with relevant metadata to guide the picking process (e.g., OD600).

criteria_column

Optional character indicating the column in metadata_df to be used as a criteria.

hard_mask_column

Column name in the cluster_df or metadata_df tibble indicating whether the spectra, and the clusters to which they belong should be discarded (TRUE) or not (FALSE) before the picking decision.

soft_mask_column

Column name in the cluster_df or metadata_df tibble indicating whether the spectra should be discarded (TRUE) or not (FALSE) before the picking decision.

is_descending_order

Optional logical indicating whether to sort the criteria_column from the highest-to-lowest value (TRUE) or lowest-to-highest (FALSE).

is_sorted

Optional logical to indicate that the cluster_df is already sorted by cluster based on (usually multiple) internal criteria to pick the first of each cluster. This flag is overridden if a metadata_df is provided.

See Also

delineate_with_similarity, set_reference_spectra. For a useful utility function to soft-mask specific spectra: is_well_on_edge.

Examples

# 0. Load a toy example of a tibble of clusters created by
#   the `delineate_with_similarity` function.
clusters <- readRDS(
  system.file("clusters_tibble.RDS",
    package = "maldipickr"
  )
)
# 1. By default and if no other metadata are provided,
#   the function picks reference spectra for each clusters.
#
# N.B: The spectra `name` and `to_pick` columns are moved to the left
# only for clarity using the `relocate()` function.
#
pick_spectra(clusters) %>%
  dplyr::relocate(name, to_pick) # only for clarity

# 2.1 Simulate OD600 values with uniform distribution
#  for each of the colonies we measured with
#  the Bruker MALDI Biotyper
set.seed(104)
metadata <- dplyr::transmute(
  clusters,
  name = name, OD600 = runif(n = nrow(clusters))
)
metadata

# 2.2 Pick the spectra based on the highest
#   OD600 value per cluster
pick_spectra(clusters, metadata, "OD600") %>%
  dplyr::relocate(name, to_pick) # only for clarity

# 3.1 Say that the wells on the right side of the plate are
#   used for negative controls and should not be picked.
metadata <- metadata %>% dplyr::mutate(
  well = gsub(".*[A-Z]([0-9]{1,2}$)", "\\1", name) %>%
    strtoi(),
  is_edge = is_well_on_edge(
    well_number = well, plate_layout = 96, edges = "right"
  )
)

# 3.2 Pick the spectra after discarding (or soft masking)
#   the spectra indicated by the `is_edge` column.
pick_spectra(clusters, metadata, "OD600",
  soft_mask_column = "is_edge"
) %>%
  dplyr::relocate(name, to_pick) # only for clarity

# 4.1 Say that some spectra were picked before
#   (e.g., in the column F) in a previous experiment.
# We do not want to pick clusters with those spectra
#   included to limit redundancy.
metadata <- metadata %>% dplyr::mutate(
  picked_before = grepl("_F", name)
)
# 4.2 Pick the spectra from clusters without spectra
#   labeled as `picked_before` (hard masking).
pick_spectra(clusters, metadata, "OD600",
  hard_mask_column = "picked_before"
) %>%
  dplyr::relocate(name, to_pick) # only for clarity