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# read_data

Source: `R/data_load_and_transform.R`
`read_data.Rd`

Load .fcs or .csv files into a dataframe and prepare the condor object.

## Usage

    read_data(
      data_path,
      max_cells,
      useCSV,
      separator,
      simple_names,
      truncate_max_range,
      emptyValue,
      ignore.text.offset,
      verbose,
      cross_path_with_anno,
      anno_table,
      separator_anno,
      filename_col
    )

## Arguments

data_path

  Path to the .fcs or .csv files.

max_cells

  number of cells to subset.

useCSV

  Logical, if input is .csv and not .fcs.

separator

  Separator used the flow csv files (if loading from csv).

simple_names

  If TRUE only the channel description is used to name the column, if FALSE both channel name and description are pasted together.

truncate_max_range

  From FlowCore: logical type. Default is FALSE. can be optionally turned off to avoid truncating the extreme positive value to the instrument measurement range .i.e.'$PnR'.

emptyValue

  From FlowCore: boolean indicating whether or not we allow empty value for keyword values in TEXT segment. It affects how the double delimiters are treated. IF TRUE, The double delimiters are parsed as a pair of start and end single delimiter for an empty value. Otherwise, double delimiters are parsed one part of string as the keyword value. default is TRUE.

ignore.text.offset

  From FlowCore: whether to ignore the keyword values in TEXT segment when they don't agree with the HEADER. Default is FALSE, which throws the error when such discrepancy is found. User can turn it on to ignore TEXT segment when he is sure of the accuracy of HEADER so that the file still can be read.

verbose

  Default FALSE, if TRUE the at each file loaded something is printed in the screen.

cross_path_with_anno

  Defautl FALSE. If TRUE is the 'data_path' contains more files then the annotation table only the overlap will be loaded.

anno_table

  Passed from 'prep_fcd'

separator_anno

  Passed from 'prep_fcd'

filename_col

  Passed from 'prep_fcs'

## Value

load flow cytometry dataset

## Details

read_data