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., Breimann, L., Zouinkhi, M., Epstein, L., Kolyvanov, K., Mamrak, N., King, B., Long, Xi, Harrington, K.I.S., 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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