{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Bahry E"],"funding":["Howard Hughes Medical Institute","NCI NIH HHS","NIGMS NIH HHS"],"pagination":["1563-1567"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9718671"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["19(12)"],"pubmed_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."],"journal":["Nature methods"],"pubmed_title":["RS-FISH: precise, interactive, fast, and scalable FISH spot detection."],"pmcid":["PMC9718671"],"funding_grant_id":["R01 GM127538","F32 CA239394"],"pubmed_authors":["Long X","Preibisch S","Bahry E","Lionnet T","Kolyvanov K","Mamrak N","Zouinkhi M","Harrington KIS","Breimann L","Epstein L","King B"],"additional_accession":[]},"is_claimable":false,"name":"RS-FISH: precise, interactive, fast, and scalable FISH spot detection.","description":"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.","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Dec","modification":"2026-06-04T05:57:49.098Z","creation":"2025-04-05T11:27:22.078Z"},"accession":"S-EPMC9718671","cross_references":{"pubmed":["36396787"],"doi":["10.1038/s41592-022-01669-y"]}}