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Updated: Jan 13, 2026

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ASTRO: Automated Spatial-Transcriptome whole RNA Output.

Dingyao Zhang1,2, Zhiyuan Chu2, Yiran Huo3

  • 1Department of Genetics, Yale School of Medicine, New Haven, CT 06520, United States.

Bioinformatics (Oxford, England)
|January 6, 2026
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Summary
This summary is machine-generated.

We developed ASTRO, a computational pipeline for spatial transcriptomics analysis. ASTRO enables whole-transcriptome analysis of formalin-fixed paraffin-embedded (FFPE) samples, including non-coding RNAs, improving RNA mapping rates.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Spatial transcriptomics analysis of formalin-fixed paraffin-embedded (FFPE) tissues is challenging.
  • Existing methods struggle to capture both coding and non-coding RNAs spatially.
  • Patho-DBiT technology requires specialized computational tools for FFPE samples.

Purpose of the Study:

  • To develop an automated computational pipeline for spatial transcriptomics data analysis.
  • To enable comprehensive whole-transcriptome analysis of FFPE samples.
  • To detect various RNA species, including non-coding RNAs, in a spatial context.

Main Methods:

  • Developed ASTRO, an automated pipeline for spatial transcriptomics data processing.
  • Optimized ASTRO for whole-transcriptome analysis of FFPE samples.
  • Incorporated specialized filtering and optimized spatial barcode calling to enhance mapping rates for degraded RNA.

Main Results:

  • ASTRO supports standard spatial transcriptomics datasets and is optimized for FFPE samples.
  • The pipeline enables detection of diverse RNA species, including non-coding RNAs like miRNAs.
  • Optimizations in ASTRO improve mapping rates and allow robust spatial quantification of coding and non-coding RNAs in FFPE tissues.

Conclusions:

  • ASTRO provides a specialized computational solution for spatial transcriptomics of FFPE samples.
  • The pipeline facilitates comprehensive analysis of both coding and non-coding RNAs.
  • ASTRO enhances the utility of FFPE tissues for spatial transcriptomics research.