CROCHET: a versatile pipeline for automated analysis and visual atlas creation from single-cell spatialomic data
Spatial biology technologies offer a unique opportunity to link tissue composition with function. However, analytical methods for quantifying and interpreting highly complex spatial data remain limited. We present CROCHET (ChaRacterization Of Cellular HEterogeneity in Tissues), an end-to-end analysis pipeline for construction of spatially resolved cell atlases from raw data covering millions of cells across large sample cohorts. Its modular architecture supports the integration of diverse data modalities and novel analytical methods for image processing and segmentation, spatialomics quantification and downstream analyses. With comprehensive, open-source, user-friendly, interactive, and visual analysis modules, CROCHET aims to democratize spatial omics for a broad community of users.
Authors
- Guillaume Thibault (ORCID: https://orcid.org/0000-0002-0734-2041)
- Anil Korkut (ORCID: https://orcid.org/0000-0001-8072-9026)
- Zeynep Dereli (ORCID: https://orcid.org/0000-0002-3486-5630)
- John N. Weinstein (ORCID: https://orcid.org/0000-0001-9401-6908)
- Behnaz Bozorgui (ORCID: https://orcid.org/0000-0003-0557-1681)
- Huamin Wang (ORCID: https://orcid.org/0000-0002-4844-8766)
- Michael J Overman
- Chunyu Yuan
Institutions
- The University of Texas MD Anderson Cancer Center (US)
- Oregon Health & Science University (US)
Publication Details
- Journal
- bioRxiv (Cold Spring Harbor Laboratory)
- Published
- 2026-03-17
- DOI
- https://doi.org/10.64898/2026.03.13.711472
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.00