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Updated: Apr 6, 2026

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SpotSweeper: spatially aware quality control for spatial transcriptomics.

Michael Totty1, Stephanie C Hicks1,2,3,4, Boyi Guo5

  • 1Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.

Nature Methods
|June 6, 2025
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Summary
This summary is machine-generated.

SpotSweeper is a new quality control (QC) method for spatially resolved transcriptomics (SRT). It identifies low-quality data and tissue artifacts, improving RNA sequencing data reliability.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Quality control (QC) is essential for reliable RNA sequencing (RNA-Seq) data.
  • Existing QC methods for single-cell RNA sequencing are unsuitable for spatially resolved transcriptomics (SRT) due to spatial biology.
  • There is a lack of methods to detect histological tissue artifacts specific to SRT.

Purpose of the Study:

  • To introduce SpotSweeper, a novel spatially aware QC method for SRT.
  • To address the limitations of current QC approaches in SRT.
  • To identify and correct for spatial confounding and detect unique SRT artifacts.

Main Methods:

  • Developed SpotSweeper, a QC method leveraging local neighborhoods for spatial awareness.
  • Applied SpotSweeper to publicly available SRT datasets.
  • Utilized SpotSweeper to identify local outliers and regional artifacts.

Main Results:

  • SpotSweeper identified a consistent set of low-quality Visium barcoded spots.
  • The method accurately detected two distinct types of regional artifacts in SRT data.
  • Demonstrated the effectiveness of a spatially aware approach for SRT QC.

Conclusions:

  • SpotSweeper offers a robust and generalizable framework for SRT QC.
  • The method enhances data reliability across various experimental conditions and technologies.
  • SpotSweeper represents a significant advancement in ensuring the quality of spatially resolved transcriptomics data.