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'