FISH-quant v2: a scalable and modular tool for smFISH image analysis
- Arthur Imbert1,
- Wei Ouyang2,
- Adham Safieddine3,
- Emeline Coleno4,
- Christophe Zimmer5,
- Edouard Bertrand4,
- Thomas Walter1 and
- Florian Mueller6,7
- 1 Centre for Computational Biology (CBIO), MINES ParisTech;
- 2 Royal Institute of Technology, Stockholm, Sweden;
- 3 Sorbonne Université;
- 4 IGH, University of Montpellier;
- 5 Imaging and Modeling Unit, Institut Pasteur;
- 6 Institut Pasteur
- ↵* Corresponding author; email: fmueller{at}pasteur.fr
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 datasets, revealing diverse subcellular RNA localization patterns and a surprisingly high degree of cell-to-cell heterogeneity.
Keywords
- Received December 2, 2021.
- Accepted February 19, 2022.
- Published by Cold Spring Harbor Laboratory Press for the RNA Society
This article, published in RNA, is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.










