cytonormpy.mad_comparison_from_fcs

cytonormpy.mad_comparison_from_fcs#

cytonormpy.mad_comparison_from_fcs(input_directory, original_files, normalized_files, norm_prefix='Norm_', channels=None, cell_labels=None, groupby=None, truncate_max_range=False, transformer=None)#

This function is a wrapper around mad_from_fcs that directly combines the normalized and unnormalized dataframes. Currently only works if the normalized and unnormalized files are in the same directory.

Parameters:

  • input_directory (PathLike) – Path specifying the input directory in which the .fcs files are stored. If left None, the current working directory is assumed.

  • original_files (Union[list[str], str]) – A list of original files ending with .fcs.

  • normalized_files (Union[list[str], str]) – A list of normalized files ending with .fcs.

  • norm_prefix (str) – The prefix of the normalized files.

  • channels (Optional[Union`[:py:class:`list[str], Index]]) – A list of detectors to analyze.

  • labels (cell) – A dictionary of shape {file_name: [cell_label, cell_label, …]}. The cell labels will be added to the dataframe. If None, MADs will be calculated per file and channel.

  • groupby (Optional[Union`[:py:class:`list[str], str]]) – Specify on what the MADs should be grouped. Can be “file_name”, “label” or [“file_name”, “label”].

  • truncate_max_range (bool) – If True, FCS data will be truncated to the range specified in the PnR values of the file.

  • transformer (Optional[Transformer]) – An instance of the cytonormpy transformers.

Return type:

A pandas.DataFrame containing the MAD values per file or per file and cell_label.

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