ArticleNature methods2025
FISHnet: detecting chromatin domains in single-cell sequential Oligopaints imaging data.
Article in Nature methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Chromosome painting in plants: history and future perspectives.Chromosome research : an international journal on the molecular, supramolecular and evolutionary aspects of chromosome biology · 2026Review
- Accurate and robust 3D genome feature discovery from multiplexed DNA FISH.bioRxiv : the preprint server for biology · 2025Article
- Persistent chromatin loops shape gene expression plasticity upon stimulation and restimulation of human neurons.bioRxiv : the preprint server for biology · 2025Article
- Learning induces persistent chromatin loops underlying robust gene expression during memory recall.bioRxiv : the preprint server for biology · 2025Article
- FAIR sharing of Chromatin Tracing datasets using the newly developed 4DN FISH Omics Format.ArXiv · 2025Article
- 3D Genome Engineering: Current Advances and Therapeutic Opportunities in Human Diseases.Research (Washington, D.C.) · 2025Review
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4 authors.
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Abstract
Sequential Oligopaints DNA FISH is an imaging technique that measures higher-order genome folding at single-allele resolution via multiplexed, probe-based tracing. Currently there is a paucity of algorithms to identify 3D genome features in sequential Oligopaints data. Here, we present FISHnet, a graph theory method based on optimization of network modularity to detect chromatin domains in pairwise distance matrices. FISHnet sensitively and specifically identifies domains and boundaries in both simulated and real single-allele imaging data and provides statistical tests for the identification of cell-type-specific domains-like folding patterns. Application of FISHnet across multiple published Oligopaints datasets confirms that nested domains consistent with TADs and subTADs are not an emergent property of ensemble Hi-C data but also observable on single alleles. We make FISHnet code freely available to the scientific community, thus enabling future studies aiming to elucidate the role of single-allele folding variation on genome function.
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