cyanoFilter (version 0.1.3)

goodfcs: indicates if measurement from a flowfile is good or bad.

Description

This function examines the column containig \(cells/\mu L\) and determins if the measurement can be used for further analysis or not based on a supplied range.

Usage

goodfcs(metafile, col_cpml = "CellspML", mxd_cellpML = 1000,
  mnd_cellpML = 50)

Arguments

metafile

associated metafile to the supplied fcsfile. This is a csv file containig computed stats from the flow cytometer.

col_cpml

column name or column number in metafile containing cell per microlitre measurements.

mxd_cellpML

maximal accepted cell per microlitre. Flowfiles with larger cell per microlitre are termed bad. Defaults to 1000.

mnd_cellpML

minimum accepted cell per microlitre. Flowfiles with lesser cell per microlitre are termed bad. Defaults to 50.

Value

character vector with length same as the number of rows in the metafile whose entries are good for good files and bad for bad files.

Details

Most flow cytometer makers will always inform clients within which range can measurements from the machine be trusted. The machines normally stores the amount of \(cells/\mu L\) it counted in a sample. Too large value could mean possible doublets and too low value could mean too little cells.

Examples

# NOT RUN {
 metadata <- system.file("extdata", "2019-03-25_Rstarted.csv", package = "cyanoFilter",
              mustWork = TRUE)
 metafile <- read.csv(metadata, skip = 7, stringsAsFactors = FALSE,
                     check.names = TRUE, encoding = "UTF-8")
 metafile <- metafile[, 1:65] #first 65 columns contains useful information
 #extract the part of the Sample.ID that corresponds to BS4 or BS5
 metafile$Sample.ID2 <- stringr::str_extract(metafile$Sample.ID, "BS*[4-5]")
 #clean up the Cells.muL column
 names(metafile)[which(stringr::str_detect(names(metafile), "Cells."))] <- "CellspML"
 goodfcs(metafile = metafile, col_cpml = "CellspML", mxd_cellpML = 1000, mnd_cellpML = 50)

# }