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<p>Characterizing the movement of biomolecules in single cells quantitatively is essential to understanding fundamental biological mechanisms. RNA fluorescent in situ hybridization (RNA-FISH) is a technique for visualizing RNA in fixed cells using fluorescent probes. Automated processing of the resulting images is essential for large datasets. Here we demonstrate that our RNA-FISH image processing tool, TrueSpot, is useful for automatically detecting the locations of RNA at single molecule resolution. TrueSpot also performs well on images with immunofluorescent and GFP-tagged clustered protein targets. Additionally, we show that our 3D spot detection approach substantially outperforms current 2D spot detection algorithms.</p>

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TrueSpot: a robust automated tool for quantifying signal puncta in fluorescent imaging

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年9月29日

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  • Blythe G. Hospelhorn,
  • Benjamin K. Kesler,
  • Hossein Jashnsaz,
  • Gregor Neuert

摘要

Characterizing the movement of biomolecules in single cells quantitatively is essential to understanding fundamental biological mechanisms. RNA fluorescent in situ hybridization (RNA-FISH) is a technique for visualizing RNA in fixed cells using fluorescent probes. Automated processing of the resulting images is essential for large datasets. Here we demonstrate that our RNA-FISH image processing tool, TrueSpot, is useful for automatically detecting the locations of RNA at single molecule resolution. TrueSpot also performs well on images with immunofluorescent and GFP-tagged clustered protein targets. Additionally, we show that our 3D spot detection approach substantially outperforms current 2D spot detection algorithms.