TY - JOUR T1 - RS-FISH: Precise, interactive, fast, and scalable FISH spot detection JF - bioRxiv DO - 10.1101/2021.03.09.434205 SP - 2021.03.09.434205 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 Y1 - 2021/01/01 UR - http://biorxiv.org/content/early/2021/10/18/2021.03.09.434205.abstract N2 - 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. ER -