CLEAR-IT supplementary data: models, embeddings, and analysis outputs for tumor microenvironment cell phenotyping

This dataset provides supplementary research data for the manuscript "CLEAR-IT, a framework for Contrastive Learning to Capture the Immune Composition of Tumor Microenvironments".<br>The archive contains derived and supporting artifacts used to reproduce the analyses, including precomputed embeddings, pretrained model weights, and precomputed output tables/results for benchmarking, ranking, SHAP analysis, survival analysis, and hyperparameter evaluation workflows.<br>The supplementary artifacts cover analyses on multiple cohorts/modalities used in the study:TNBC1-MxIF8 (Hammerl et al., 2021, https://doi.org/10.1038/s41467-021-25962-0; dataset record: https://doi.org/10.4121/126d8103-6de5-4493-a48e-5d529fef471e),TNBC2-MIBI44 (Keren et al., 2018, https://doi.org/10.1016/j.cell.2018.08.039; data resources: https://www.weizmann.ac.il/mcb/Keren/resources and https://www.angelolab.com/mibi-data),CRC-CODEX26 (Schurch et al., 2020, https://doi.org/10.1016/j.cell.2020.07.005; image resource: https://doi.org/10.7937/TCIA.2020.FQN0-0326),and TONSIL-IMC41 (Hunter et al., 2024, https://doi.org/10.1002/cyto.a.24803; image/segmentation resource: https://www.ebi.ac.uk/biostudies/bioimages/studies/S-BSST1047).<br>A README.MD file is included in the ZIP archive and provides the detailed folder inventory, file-level organization, and usage notes.<br>This record is intended to distribute reproducibility assets for the CLEAR-IT study. Dataset-specific source data provenance remains documented in the referenced original dataset records/publications.