Breast cancer IMC dataset for InterSTELLAR training

Preprocessed Breast cancer IMC dataset for InterSTELLAR training, saved as a<strong> .npy</strong> file. 1. Read this file with python and get a list named <strong>all_graph</strong>. This list includes <strong>366 </strong>elements as <strong>366 </strong>tissues. 2. Each sub-element <strong>all_graph[i]</strong> is alone a new list with three elements, including <strong>cell feature matrix all_graph[i][0]</strong>,<strong> cell locations all_graph[i][1]</strong> and<strong> tissue labels all_graph[i][2]</strong>. 3.<strong> all_graph[i][0]</strong> is a <strong>Nx30</strong> matrix, corresponding to<strong> 30 cell markers</strong>; <strong>all_graph[i][1]</strong> is a<strong> Nx2</strong> matrix, corresponding to <strong>x </strong>and <strong>y </strong>locations of a single cell; <strong> all_graph[i][2]</strong> is a list with<strong> 5</strong> elements, corresponding to <strong>tissue phenotypes</strong> (0: healthy, 1: TNBC, 2: Non-TNBC cancers), <strong>tissue area</strong> (um²),<strong> tumor grade</strong>, <strong>overall survival time </strong>(month) and <strong>patient status</strong> (alive or death).