Back

CROCHET: a versatile pipeline for automated analysis and visual atlas creation from single-cell spatialomic data

Bozorgui, B.; Thibault, G.; Yuan, C.; Dereli, Z.; Wang, H.; Overman, M. J.; Weinstein, J. N.; Korkut, A.

2026-03-17 bioinformatics
10.64898/2026.03.13.711472 bioRxiv
Show abstract

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.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
Nature Methods
○ 385 papers in training set
Top 0.5%
18.2%
Similar papers in this journal
2
Nature Communications
○ 5641 papers in training set
Top 14%
12.9%
Similar papers in this journal
3
Bioinformatics
◐ 1204 papers in training set
Top 3%
9.6%
Similar papers in this journal
4
Cell Reports Methods
○ 165 papers in training set
Top 0.1%
7.2%
Similar papers in this journal
5
Nature Protocols
○ 33 papers in training set
Top 0.1%
5.4%
Similar papers in this journal
50% of probability mass above
6
Nature Biotechnology
○ 172 papers in training set
Top 0.8%
4.8%
7
Briefings in Bioinformatics
◐ 354 papers in training set
Top 2%
4.0%
8
Genome Biology
○ 637 papers in training set
Top 3%
4.0%
9
Patterns
○ 78 papers in training set
Top 0.5%
3.4%
10
Nucleic Acids Research
◐ 1281 papers in training set
Top 6%
3.2%
11
Molecular Systems Biology
○ 162 papers in training set
Top 0.8%
2.7%
12
Cell Systems
○ 201 papers in training set
Top 2%
2.1%
13
Biological Imaging
◐ 15 papers in training set
Top 0.1%
2.1%
14
Bioinformatics Advances
◐ 203 papers in training set
Top 3%
1.9%
15
Communications Biology
○ 993 papers in training set
Top 12%
1.9%
16
PLOS Computational Biology
● 1863 papers in training set
Top 15%
1.7%
17
NAR Genomics and Bioinformatics
◐ 242 papers in training set
Top 4%
1.0%
18
Scientific Reports
○ 3612 papers in training set
Top 67%
1.0%
19
eLife
● 5828 papers in training set
Top 63%
1.0%
20
GigaScience
◐ 212 papers in training set
Top 4%
1.0%
21
Small Methods
○ 29 papers in training set
Top 0.8%
0.8%
22
BMC Bioinformatics
○ 457 papers in training set
Top 6%
0.8%
23
BMC Methods
○ 15 papers in training set
Top 0.3%
0.6%
24
iScience
○ 1154 papers in training set
Top 42%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.