Back

KaroSpace: a rapid-access framework for interactive exploration of multi-sample spatial omics data

Langseth, C. M.; Herve, B.; Piechaczyk, H. P.; Lor, Y. K.; Sun, T.; Castelo-Branco, G.

2026-03-12 neuroscience
10.64898/2026.03.10.710790 bioRxiv
Show abstract

Spatial omics technologies enable high-resolution mapping of molecular and cellular organization within tissues, yet interactive exploration of these data remains challenging due to computational bottlenecks, and reliance on proprietary software infrastructures. We present KaroSpace, a framework for cell-centric exploration of multi-sample and multi-modality spatial omics data, agnostic to upstream analysis pipelines and operating on preprocessed spatial features. By combining a lightweight design with flexible deployment options, KaroSpace allows immediate interactive spatial data exploration, straightforward implementation to the broader scientific community, supports transparent data sharing, and complements existing computational workflows for hypothesis generation and collaborative analysis.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Nature Methods
○ 385 papers in training set
Top 0.5%
18.0%
Similar papers in this journal
2
Nature Communications
○ 5641 papers in training set
Top 15%
12.1%
Similar papers in this journal
3
Journal of Open Source Software
● 25 papers in training set
Top 0.1%
6.5%
Similar papers in this journal
4
Nucleic Acids Research
◐ 1281 papers in training set
Top 3%
6.5%
Similar papers in this journal
5
PLOS Computational Biology
● 1863 papers in training set
Top 6%
6.1%
6
GigaScience
◐ 212 papers in training set
Top 0.4%
6.1%
Similar papers in this journal
50% of probability mass above
7
Bioinformatics
◐ 1204 papers in training set
Top 4%
5.3%
8
Genome Biology
○ 637 papers in training set
Top 3%
3.9%
9
Nature Protocols
○ 33 papers in training set
Top 0.2%
3.1%
10
Cell Reports Methods
○ 165 papers in training set
Top 1%
2.1%
11
Nature Biotechnology
○ 172 papers in training set
Top 2%
2.1%
12
Scientific Data
○ 209 papers in training set
Top 1%
1.7%
13
eLife
● 5828 papers in training set
Top 52%
1.7%
14
PLOS ONE
● 5266 papers in training set
Top 48%
1.6%
15
Nature Computational Science
○ 55 papers in training set
Top 0.8%
1.5%
16
iScience
○ 1154 papers in training set
Top 22%
1.4%
17
Wellcome Open Research
○ 67 papers in training set
Top 0.8%
1.1%
18
Patterns
○ 78 papers in training set
Top 2%
1.1%
19
Communications Biology
○ 993 papers in training set
Top 26%
1.0%
20
eneuro
● 439 papers in training set
Top 7%
1.0%
21
Scientific Reports
○ 3612 papers in training set
Top 68%
1.0%
22
Cell Reports
○ 1498 papers in training set
Top 25%
1.0%
23
BMC Bioinformatics
○ 457 papers in training set
Top 5%
1.0%
24
SoftwareX
○ 15 papers in training set
Top 0.3%
0.8%
25
Nature
○ 645 papers in training set
Top 11%
0.8%
26
Advanced Science
○ 286 papers in training set
Top 10%
0.8%
27
F1000Research
○ 88 papers in training set
Top 5%
0.6%
28
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 46%
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.