generate_heatmap_pannels

This git repo is to generate 4-image panel as the one in example.png at the bottom.

There are different branches for different tumor types.

• 2_classes: for tumor types with binary classification, e.g, BRCA, PAAD
• 3_classes_prad: for 3-way classification, especially for PRAD.
• 6_classes_luad: for 6-way classification, especially for LUAD.

The run instructions are the same for all branches.

Setup Parameters

You need to change the path in the following codes in main.py. The variable names are self-explanatory

# these folders will be replaced by paramaters
svs_fol = '/data01/shared/hanle/svs_tcga_paad'
cancer_fol = '/data04/shared/hanle/paad_prediction/data/heatmap_txt_190_tcga'
til_fol = '/data04/shared/shahira/TIL_heatmaps/PAAD/vgg_mix_binary/heatmap_txt'
output_pred = '4panel_pngs'

prefix = "prediction-"
wsi_extension = ".svs"

NOTE: please make sure that the filename of prediction-xxx and color-xxx files of the same WSIs in cancer_fol and til_fol the SAME. For example, if the WSI is TCGA-TD-XL01-01-DX1, then there is one "prediction-TCGA-TD-XL01-01-DX1" and one "color-TCGA-TD-XL01-01-DX1" file in cancer_fol and one "prediction-TCGA-TD-XL01-01-DX1", one "color-TCGA-TD-XL01-01-DX1" files in til_fol

Usage

python main.py N

where N can be -1, 0, 1, or any positive integer.

• 0/1: not using parallel processing
• any number larger than 1, using N cores in parallel processing, limited to the available cores in the system.
• -1: use all available cores in parallel processing, left 2 cores for others