knitr::opts_chunk$set(echo = TRUE)
Data were aquired from the public flow repository FR-FCM-Z29V and uploaded by Charles Bagwell on 2022-09-22. The web address is https://flowrepository.org/id/FR-FCM-Z29V. The file used to create extdata is REP_1_deid.fcs.
The original fcs file was read in with readCytof and then labeled with \code{labelQC} using the default settings. The dataset was then subset using the labels to ensure it was sufficiently small to meet Bioconductor requirements and still include enough of each type of event to be informative in the vignette.
Read in the data using readCytof and then label the events as follows:
library(cytofQC) file.name <- "path_to_file/REP_1_deid.fcs" x <- readCytof(file.name, beads = c("Bead"), dna = c("DNA1", "DNA2"), event_length = "Event_length", viability = "Live_Dead", gaussian = c("Center", "Offset", "Width", "Residual")) x <- labelQC(x) table(label(x))
Subset the data using the labels as follows:
bead <- sample(seq_along(label(x))[label(x) == "bead"], 150) cell <- sample(seq_along(label(x))[label(x) == "cell"], 5000) debris <- sample(seq_along(label(x))[label(x) == "debris"], 600) doublet <- sample(seq_along(label(x))[label(x) == "doublet"], 400) gdpZero <- sample(seq_along(label(x))[label(x) == "gdpZero"], 300) index <- sort(c(bead, cell, debris, doublet, gdpZero))
The data were then subset and saved as an fcs file using the flowCore package.
library(flowCore) extdata <- read.FCS(file.name, which.lines = index) write.FCS(extdata, "extdata.fcs")
Bagwell, Charles Bruce, et al. "Automated data cleanup for mass cytometry." Cytometry Part A 97.2 (2020): 184-198.
Spidlen, Josef, Karin Breuer, and Ryan Brinkman. "Preparing a Minimum Information about a Flow Cytometry Experiment (MIFlowCyt) compliant manuscript using the International Society for Advancement of Cytometry (ISAC) FCS file repository (FlowRepository. org)." Current protocols in cytometry 61.1 (2012): 10-18.
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