Description Usage Arguments Details Value Examples
This function examines the column containig cells/μ L and determins if the measurement can be used for further analysis or not based on a supplied range.
1 | goodFcs(metafile, col_cpml = "CellspML", mxd_cellpML = 1000, mnd_cellpML = 50)
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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. |
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/μ L it counted in a sample. Too large value could mean possible doublets and too low value could mean too little cells.
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.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | require("stringr")
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[, seq_len(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)
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