PT - JOURNAL ARTICLE AU - Ella Bahry AU - Laura Breimann AU - Marwan Zouinkhi AU - Leo Epstein AU - Klim Kolyvanov AU - Xi Long AU - Kyle I S Harrington AU - Timothée Lionnet AU - Stephan Preibisch TI - RS-FISH: Precise, interactive, fast, and scalable FISH spot detection AID - 10.1101/2021.03.09.434205 DP - 2021 Jan 01 TA - bioRxiv PG - 2021.03.09.434205 4099 - http://biorxiv.org/content/early/2021/10/18/2021.03.09.434205.short 4100 - http://biorxiv.org/content/early/2021/10/18/2021.03.09.434205.full AB - 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.Competing Interest StatementThe authors have declared no competing interest.