Published July 9, 2024 | Version 1.0.0
Dataset Open

Multi-modal image analysis for large scale cancer tissue studies within IMMUcan: multiplex immunofluorescence images

Contributors

  • 1. ROR icon SIB Swiss Institute of Bioinformatics
  • 2. ROR icon University of Lausanne

Description

In cancer research, multiplexed imaging has enabled the in-depth characterization of the tumor microenvironment (TME) and how it relates to patient prognosis. However, standardized, multi-modal data from large numbers of patients to identify robust biomarkers is missing. To provide such data across five cancer indications, the IMMUcan consortium performs broad molecular and cellular spatial profiling of thousands of cancer samples. Two reproducible and scalable workflows have been developed for whole slide multiplexed immunofluorescence (mIF) and imaging mass cytometry (IMC) to overcome challenges of reproducibility and scalability. For mIF we developed IFQuant, a web-based tool optimized for user-friendliness and reproducibility. This Zenodo record contains the mIF images and IFQuant settings to reproduce the results presented in the referenced publication. The companion IMC dataset is available as a joint Zenodo record.

Files

IMMU-BC2-0755-FIXT-01-IF1-01.zip

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Additional details

Related works

Is referenced by
Dataset: 10.5281/zenodo.12912567 (DOI)

Funding

Innovative Medicines Initiative
IMMUcan: Integrated immunoprofiling of large adaptive cancer patients cohorts 821558

Dates

Submitted
2024-07-29

Software

Repository URL
https://github.com/BICC-UNIL-EPFL/IFQuant
Programming language
R, JavaScript, PHP
Development Status
Wip