convert_flowset: Convert a flowSet into a tibble

In biosurf/cyCombine: Robust integration of single-cell cytometry datasets within and across technologies

Convert a flowSet into a tibble

Description

Use this function to convert a flowSet into the tibble object that the remaining functions in cyCombine relies on. A tibble is a Tidyverse implementation of a data.frame and can be treated as a such. The majority of arguments revolves adding relevant info from the metadata file/object. The panel argument is included to adjust the output column names using a panel with channel and antigen columns. Bear in mind the column names will be altered with the following: stringr::str_remove_all("^\d+[A-Za-z]+_") %>% stringr::str_remove_all("[ _-]").

Usage

convert_flowset(
  flowset,
  metadata = NULL,
  filename_col = "filename",
  sample_ids = NULL,
  batch_ids = NULL,
  condition = NULL,
  anchor = NULL,
  down_sample = TRUE,
  sample_size = 5e+05,
  sampling_type = "random",
  seed = 473,
  clean_colnames = TRUE,
  panel = NULL,
  panel_channel = "fcs_colname",
  panel_antigen = "antigen"
)

Arguments

flowset	The flowset to convert
metadata	Optional: Can be either a filename or data.frame of the metadata file. Please give the full path from working directory to metadata file
filename_col	Optional: The column in the metadata containing the fcs filenames. Needed if metadata is given, but sample_ids is not
sample_ids	Optional: If a character, it should be the sample column in the metadata. If its a vector, it should have the same length as the total flowset. If NULL, sample ids will be the file names. If a single value, all rows will be assigned this value.
batch_ids	Optional: If a character, it should be the column in the metadata containing the batch ids. If its a vector, it should have the same length as the total flowset. If a single value, all rows will be assigned this value.
condition	Optional: The column in the metadata containing the condition. Will be used as the covariate in ComBat, but can be specified later. You may use this to add a different column of choice, in case you want to use a custom column in the ComBat model matrix.
anchor	Experimental: The column in the metadata referencing the anchor samples (control references). Will be used as a covariate in ComBat, if specified. Please be aware that this column may be confounded with the condition column. You may use this to add a different column of choice, in case you want to use a custom column in the ComBat model matrix. You may use a custom column name, but it is good practice to add the name to the 'non_markers' object exported by cyCombine, to reduce the risk of unexpected errors.
down_sample	If TRUE, the output will be down-sampled to size sample_size
sample_size	The size to down-sample to. If a non-random sampling type is used and a group contains fewer cells than the sample_size, all cells of that group will be used.
sampling_type	The type of down-sampling to use. "random" to randomly select cells across the entire dataset, "batch_ids" to sample evenly (sample_size) from each batch, or "sample_ids" sample evenly (sample_size) from each sample.
seed	The seed to use for down-sampling
clean_colnames	(Default: TRUE). A logical defining whether column names should be cleaned or not. Cleaning involves removing isotope tags, spaces, dashes, underscores, and all bracket types.
panel	Optional: Panel as a filename or data.frame. Is used to define colnames from the panel_antigen column
panel_channel	Optional: Only used if panel is given. It is the column name in the panel data.frame that contains the channel names
panel_antigen	Optional: Only used if panel is given. It is the column name in the panel data.frame that contains the antigen names

See Also

Other dataprep: compile_fcs(), prepare_data(), transform_asinh()

Examples

## Not run: 
df <- convert_flowset(flowset = flowset,
 metadata = file.path(data_dir, "metadata.csv"),
 filename_col = "FCS_files",
 sample_ids = "sample_id",
 batch_ids = "batch_ids",
 down_sample = FALSE)
 
## End(Not run)

biosurf/cyCombine documentation built on May 23, 2024, 4:07 a.m.