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RS-FISH: precise, interactive, fast, and scalable FISH spot detection.

Ella BahryLaura BreimannMarwan ZouinkhiLeo EpsteinKlim KolyvanovNicholas MamrakBenjamin KingXi LongKyle I S HarringtonTimothée LionnetStephan Preibisch
Published in: Nature methods (2022)
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.
Keyphrases
  • single molecule
  • label free
  • deep learning
  • gene expression
  • high resolution
  • machine learning
  • loop mediated isothermal amplification
  • high throughput
  • real time pcr
  • genome wide
  • ultrasound guided