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

Ella Bahry; Laura Breimann; Marwan Zouinkhi; Leo Epstein; Klim Kolyvanov; Nicholas Mamrak; Benjamin R. King; Xi Long; Kyle Harrington; Timothée Lionnet; Stephan Preibisch

doi:10.1038/s41592-022-01669-y

BioinformaticsNature MethodsNov 17, 2022

Peer-reviewed journal article

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

Ella Bahry iD, Laura Breimann iD, Marwan Zouinkhi iD, Leo Epstein, Klim Kolyvanov, Nicholas Mamrak, Benjamin R. King iD, Xi Long iD, Kyle Harrington iD, Timothée Lionnet iD, Stephan Preibisch iD

Abstract

Fluorescent in-situ hybridization (FISH)-based methods are powerful tools to study molecular processes with subcellular resolution, relying on accurate identification and localization of diffraction-limited spots in microscopy images. We developed the Radial Symmetry-FISH (RS-FISH) software that accurately, robustly, and quickly detects single-molecule spots in two and three dimensions, making it applicable to several key assays, including single-molecule FISH (smFISH), spatial transcriptomics, and spatial genomics. RS-FISH allows interactive parameter tuning and scales to large sets of images as well as tera-byte sized image volumes such as entire brain scans using straight-forward distributed processing on workstations, clusters, and in the cloud.

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