ArticleRNA (New York, N.Y.)2022
FISH-quant v2: a scalable and modular tool for smFISH image analysis.
Article in RNA (New York, N.Y.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 103 papers.
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Who cites it
103 citing papers in PubMed.
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- RNA-binding proteins in the mouse lens: Functional classifications, expression profiling, and interaction studies of Carhsp1 with crystallin mRNAs.Developmental biology · 2026Article
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- Locally synthesized glycyl aminoacyl-tRNA synthetase is important for local translation in neurons.Life science alliance · 2026Article
- The SPN-4 Rbfox RNA-binding protein selects maternal mRNAs for CCR4-NOT-dependent clearance in early Caenorhabditis elegans embryos.Development (Cambridge, England) · 2026Article
- zFISHer: Automated 3D Registration, Detection, and Colocalization with Interactive Curation for Sequential Multiplexed FISH.bioRxiv : the preprint server for biology · 2026Article
- Tuning tRNA synthetase inhibition reveals parabolic induction of stress granules limited in size and RNA content.RNA (New York, N.Y.) · 2026Article
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- Temporal gating dictates stress-induced transcript export from the nucleus.bioRxiv : the preprint server for biology · 2026Article
- Whole-organism spatial transcriptomics at single-cell resolution inbioRxiv : the preprint server for biology · 2026Article
- Poxvirus infection triggers remodeling of host m⁶A epitranscriptome and benefits from the m⁶A regulatory responses.Virology journal · 2026Article
- Incorporation of genome-bound cellular proteins into HIV-1 particles regulates viral infection.Cell reports · 2026Article
- autoFISH: a modular toolbox for sequential single-molecule RNA FISH experiments.Communications biology · 2026Article
43 more citing papers are in PubMed but not listed here.
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Regulation of RNA abundance and localization is a key step in gene expression control. Single-molecule RNA fluorescence in situ hybridization (smFISH) is a widely used single-cell-single-molecule imaging technique enabling quantitative studies of gene expression and its regulatory mechanisms. Today, these methods are applicable at a large scale, which in turn come with a need for adequate tools for data analysis and exploration. Here, we present FISH-quant v2, a highly modular tool accessible for both experts and non-experts. Our user-friendly package allows the user to segment nuclei and cells, detect isolated RNAs, decompose dense RNA clusters, quantify RNA localization patterns and visualize these results both at the single-cell level and variations within the cell population. This tool was validated and applied on large-scale smFISH image data sets, revealing diverse subcellular RNA localization patterns and a surprisingly high degree of cell-to-cell heterogeneity.
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