fcs2DF: Convert fcs files to a data frame

In hzc363/CytoDx: Robust prediction of clinical outcomes using cytometry data without cell gating

Description

A function that convert fcs files to a data frame.

Usage

fcs2DF(fcsFiles, y = NULL, assay = c("FCM", "CyTOF"), b = 1/200,
  fileSampleSize = 5000, compFiles = NULL, nameDict = NULL,
  excludeTransformParameters = c("FSC-A", "FSC-W", "FSC-H", "Time",
  "Cell_length"))

Arguments

fcsFiles	A vector specifying the location of fcs files (relative to working directory).
y	A vector containing the clinical outcome of each sample. Must have the same length as fcsFiles. Null for testing data.
assay	Either "FCM" or "CyTOF" to indicate the type of cytometry data.
b	A positive number used to specify the arcsinh transformation. f(x) = asinh (b*x) where x is the original value and f(x) is the value after transformation. The suggested value is 1/150 for flow cytometry (FCM) data and 1/8 for CyTOF data.
fileSampleSize	An integer specifying the number of events sampled from each fcs file. If NULL, all the events will be pre-processed and wrote out to the new fcs files.
compFiles	A vector specifying the paths of user supplied compensation matrix for each fcs file. The matrix must be stored in csv files.
nameDict	A vector used to change marker names.Each element in the vector is the prefered name of a marker. The name of each element is the marker name used in the fcs file. For example, a vector c("CD8b"="CD8","cd8"="CD8") will change "CD8b" and "cd8" into "CD8", making annotations more consistent.
excludeTransformParameters	A vector specifying the name of parameters not to be transformed (left at linear scale).

Value

Returns a data frame containing the preprocessed cytometry data. Cells from different fcs files are combined into one flow frame. A new column, xSample, is introduced to indicate the origin of each cell. The data frame also includes the clinical outcome y.

Examples

# Find the table containing fcs file names in CytoDx package
path <- system.file("extdata",package="CytoDx")
# read the table
fcs_info <- read.csv(file.path(path,"fcs_info.csv"))
# Specify the path to the cytometry files
fn <- file.path(path,fcs_info$fcsName)
# Read cytometry files using fcs2DF function
train_data <- fcs2DF(fcsFiles=fn,
                    y=fcs_info$Label,
                    assay="FCM",
                    b=1/150,
                    excludeTransformParameters=
                      c("FSC-A","FSC-W","FSC-H","Time"))

hzc363/CytoDx documentation built on May 8, 2019, 11:56 p.m.