RS-FISH
RS-FISH detects and localizes diffraction-limited single-molecule fluorescent in-situ hybridization (FISH) spots in two-dimensional and three-dimensional microscopy images to enable precise spatial analysis of molecular processes.
Key Features:
- Accuracy and Robustness: Detects single-molecule FISH (smFISH) spots with high precision across two-dimensional and three-dimensional datasets, providing reliable identification in complex imaging conditions.
- Parameter Tuning: Supports adjustment of detection parameters to optimize spot identification for specific experimental conditions and sample types.
- Scalability: Processes large-scale image datasets and supports distributed processing for analysis of extensive image volumes.
Scientific Applications:
- Single-Molecule FISH (smFISH): Enables study of gene expression at single-molecule resolution within cells.
- Spatial Transcriptomics: Facilitates mapping of RNA transcripts across tissue sections to reveal spatial gene expression patterns.
- Spatial Genomics: Aids localization and analysis of genomic elements within their native cellular context.
Methodology:
Uses the Radial Symmetry algorithm, analyzing symmetry around potential spot centers to distinguish true molecular signals from background noise.
Topics
Details
- Tool Type:
- desktop application
- Programming Languages:
- Java, Python
- Added:
- 11/29/2021
- Last Updated:
- 11/29/2021
Operations
Publications
Bahry E, Breimann L, Zouinkhi M, Epstein L, Kolyvanov K, Long X, Harrington KIS, Lionnet T, Preibisch S. RS-FISH: Precise, interactive, fast, and scalable FISH spot detection. Unknown Journal. 2021. doi:10.1101/2021.03.09.434205.
Links
Issue tracker
https://github.com/PreibischLab/RS-FISH/issues