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| Item Type: | Article |
|---|---|
| Title: | RS-FISH: precise, interactive, fast, and scalable FISH spot detection |
| Creators Name: | Bahry, E. and Breimann, L. and Zouinkhi, M. and Epstein, L. and Kolyvanov, K. and Mamrak, N. and King, B. and Long, Xi and Harrington, K.I.S. and Lionnet, T. and Preibisch, S. |
| Abstract: | Fluorescent in-situ hybridization (FISH)-based methods extract spatially resolved genetic and epigenetic information from biological samples by detecting fluorescent spots in microscopy images, an often challenging task. We present Radial Symmetry-FISH (RS-FISH), an accurate, fast, and user-friendly software for spot detection in two- and three-dimensional images. RS-FISH offers interactive parameter tuning and readily scales to large datasets and image volumes of cleared or expanded samples using distributed processing on workstations, clusters, or the cloud. RS-FISH maintains high detection accuracy and low localization error across a wide range of signal-to-noise ratios, a key feature for single-molecule FISH, spatial transcriptomics, or spatial genomics applications. |
| Keywords: | Image Processing, Software, Transcription |
| Source: | Nature Methods |
| ISSN: | 1548-7091 |
| Publisher: | Nature Publishing Group |
| Volume: | 19 |
| Number: | 12 |
| Page Range: | 1563-1567 |
| Date: | December 2022 |
| Official Publication: | https://doi.org/10.1038/s41592-022-01669-y |
| PubMed: | View item in PubMed |
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