Back

Sphere-sequencing unveils local tissue microenvironments at single cell resolution

Handler, K.; Bach, K.; Borrelli, C.; Ficht, X.; Acar, I. E.; Moor, A. E.

2022-11-01 genomics
10.1101/2022.10.31.514509 bioRxiv
Show abstract

The spatial organization of cells within tissues is tightly linked to their biological function. Yet, methods to probe the entire transcriptome of multiple native tissue microenvironments at single cell resolution are lacking. Here, we introduce spheresequencing, a method that enables the transcriptomic characterization of single cells within spatially distinct tissue niches. Sphere-sequencing of the mouse metastatic liver revealed previously uncharacterized zonated genes and ligand-receptor interactions enriched in different hepatic microenvironments and the metastatic niche.

Matching journals

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

1
Nature Communications
○ 5641 papers in training set
Top 5%
26.0%
Similar papers in this journal
2
Nature Biotechnology
○ 172 papers in training set
Top 0.2%
8.7%
Similar papers in this journal
3
Nature
○ 645 papers in training set
Top 2%
7.7%
Similar papers in this journal
4
Cell
○ 431 papers in training set
Top 0.7%
7.1%
Similar papers in this journal
5
Nature Genetics
○ 286 papers in training set
Top 1%
5.4%
Similar papers in this journal
50% of probability mass above
6
Cell Genomics
○ 172 papers in training set
Top 0.8%
5.4%
7
Nature Methods
○ 385 papers in training set
Top 3%
3.1%
8
eLife
● 5828 papers in training set
Top 43%
2.4%
9
Nature Cell Biology
○ 118 papers in training set
Top 1%
2.3%
10
Genome Biology
○ 637 papers in training set
Top 5%
2.3%
11
Cell Reports
○ 1498 papers in training set
Top 16%
2.3%
12
Communications Biology
○ 993 papers in training set
Top 15%
1.7%
13
Cancer Cell
○ 42 papers in training set
Top 0.8%
1.6%
14
Molecular Systems Biology
○ 162 papers in training set
Top 2%
1.5%
15
Nature Medicine
○ 125 papers in training set
Top 2%
1.3%
16
Nature Cancer
○ 39 papers in training set
Top 1%
1.1%
17
Cell Research
○ 51 papers in training set
Top 0.9%
1.1%
18
Science
● 477 papers in training set
Top 7%
1.1%
19
Molecular Cell
○ 350 papers in training set
Top 4%
1.0%
20
Science Advances
● 1243 papers in training set
Top 29%
1.0%
21
Proceedings of the National Academy of Sciences
● 2444 papers in training set
Top 42%
0.8%
22
Cell Reports Methods
○ 165 papers in training set
Top 4%
0.8%
23
Genome Medicine
○ 183 papers in training set
Top 5%
0.8%
24
Nature Structural & Molecular Biology
236 papers in training set
Top 3%
0.8%
25
Gastroenterology
○ 42 papers in training set
Top 1%
0.8%
26
iScience
○ 1154 papers in training set
Top 38%
0.8%
27
Nature Neuroscience
○ 252 papers in training set
Top 6%
0.6%
28
Nature Cardiovascular Research
○ 33 papers in training set
Top 1%
0.6%
29
Developmental Cell
○ 196 papers in training set
Top 5%
0.6%
30
Nature Ecology & Evolution
131 papers in training set
Top 3%
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.