ArticleCommunications biology2024
Chrysalis: decoding tissue compartments in spatial transcriptomics with archetypal analysis.
Article in Communications biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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Who cites it
5 citing papers in PubMed.
- ParTIpy: a scalable framework for archetypal analysis and Pareto task inference.Molecular systems biology · 2026Article
- Spatiotemporal organisation of residual disease in mouse and human BRCA1-deficient mammary tumours and breast cancer.Nature communications · 2026Article
- SECTOR: structural entropy-based learning of spatiotemporal organisation in spatial transcriptomics.Bioinformatics (Oxford, England) · 2026Article
- Chrysalis: decoding tissue compartments in spatial transcriptomics with archetypal analysis.Communications biology · 2024Article
- LIANA+ provides an all-in-one framework for cell-cell communication inference.Nature cell biology · 2024Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Dissecting tissue compartments in spatial transcriptomics (ST) remains challenging due to limited spatial resolution and dependence on single-cell reference data. We present Chrysalis, a computational method that rapidly uncovers tissue compartments through spatially variable gene (SVG) detection and archetypal analysis without requiring external reference data. Additionally, it offers a unique visualisation approach for swift tissue characterisation and provides access to the underlying gene expression signatures, enabling the identification of spatially and functionally distinct cellular niches. Chrysalis was evaluated through various benchmarks and validated against deconvolution, independently obtained cell type abundance data, and histopathological annotations, demonstrating superior performance compared to other algorithms on both in silico and real-world test examples. Furthermore, we showcased its versatility across different technologies, such as Visium, Visium HD, Slide-seq, and Stereo-seq.
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Registered trials
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