RS-FISH: precise, interactive, fast, and scalable FISH spot detection
Ella Bahry, Laura Breimann, Marwan Zouinkhi, Leo F. Epstein, Klim Kolyvanov, Nicholas Mamrak, Benjamin R. King, Xi Long, Kyle Harrington, Timothée Lionnet, Stephan Preibisch
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.