ArticleComputational and structural biotechnology journal2024
PENGUIN: A rapid and efficient image preprocessing tool for multiplexed spatial proteomics.
Article in Computational and structural biotechnology journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Frailty of older patients is not reflected in the melanoma tumor microenvironment and treatment response to immune checkpoint blockade therapy.Journal for immunotherapy of cancer · 2026Article
- Dissecting Immune Determinants in Lesional Skin of Cutaneous T-Cell Lymphoma During Mogamulizumab Therapy.Cancers · 2026Article
- Spotlight on challenges and novel methods in highly multiplexed tissue imaging-based spatial proteomics.Journal of translational medicine · 2026Review
- Review
- Spatial immune profiling complements genomic sequencing in biliary tract cancer: hypothesis-generating use cases.ESMO gastrointestinal oncology · 2026Article
- Cellular interaction of mycosis fungoides tumor cells changes from cytotoxic CD8+ T cells in plaques to B cells in tumors.Frontiers in immunology · 2026Article
- Sequential lymphotoxin-β receptor and retinoic acid receptor signals regulate cDC2 fate.Nature immunology · 2025Article
- Antibody-oligonucleotide conjugates for spatial proteomics: principles, applications, and challenges.Acta biochimica et biophysica Sinica · 2025Article
- Sequential Lymphotoxin Beta Receptor and Retinoic Acid Receptor signals regulate cDC2 fates.Research square · 2025Article
- Reprogramming CD8+ T-cell Branched N-Glycosylation Limits Exhaustion, Enhancing Cytotoxicity and Tumor Killing.Cancer immunology research · 2025Article
- Article
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Authors and funding
4 authors.
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Abstract
Multiplex spatial proteomic methodologies can provide a unique perspective on the molecular and cellular composition of complex biological systems. Several challenges are associated to the analysis of imaging data, specifically in regard to the normalization of signal-to-noise ratios across images and subtracting background noise. However, there is a lack of user-friendly solutions for denoising multiplex imaging data that can be applied to large datasets. We have developed PENGUIN -Percentile Normalization GUI Image deNoising: a straightforward image preprocessing tool for multiplexed spatial proteomics data. Compared to existing approaches, PENGUIN distinguishes itself by eliminating the need for manual annotation or machine learning models. It effectively preserves signal intensity differences while reducing noise, improving downstream tasks such as cell segmentation and phenotyping. PENGUIN's simplicity, speed, and intuitive interface, available as both a script and a Jupyter notebook, make it easy to adjust image processing parameters, providing a user-friendly experience. We further demonstrate the effectiveness of PENGUIN by comparing it to conventional image processing techniques and solutions tailored for multiplex imaging data.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.