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RS-FISH: precise, interactive, fast, and scalable FISH spot detection

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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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