In-Depth Python usage

This section of the Docs is to describe each function and its utility in the ProcessMRXS Class.

Functions specifics

Call the process_data method to process MRXS data, merge it with inventory, and calculate immunopositivity statistics for every slide (this function is called internally for each file in the process_directory method):

result_df = processor.process_data()

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To process immunopositivity rate from Excel/CSV files and merge into a unique main DataFrame, call the process_positivity method:

xlsx_file = "path/to/your/immunopositivity_data.xlsx"
final_df = ProcessMRXSData.process_positivity(xlsx_file, result_df)

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Process MRXS data from a directory, save antibody-specific data, and return the final DataFrame using the process_directory method (internally calling the process_data):

directory_path = "path/to/your/mrxs/files/directory"
output_path = "path/to/output/data/directory"
output_filename = "output_data.csv"  # Name of the output CSV file
final_data = ProcessMRXSData.process_directory(directory_path, inventory_file, output_path, output_filename)

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Process immunopositivity rate from saved files and merge it into a final DataFrame using the process_rate method:

final_rate = ProcessMRXSData.process_rate(output_path, final_data)

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To generate and save correlation heatmaps based on immunopositivity rate data, call the process_heatmaps method:

data_file = "path/to/your/immunopositivity_data.csv"
ProcessMRXSData.process_heatmaps(data_file)

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To generate and save scatterplots based on immunopositivity rate data, use the process_scatterplots method:

data_file = "path/to/your/immunopositivity_data.csv"
ProcessMRXSData.process_scatterplots(data_file)

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For more details, examples, and command-line usage, please refer to the code and documentation in this repository.

License

This project is licensed under the MIT License - see the LICENSE file for details to the rightful owner.