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Updated: Mar 28, 2026

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Published on: September 5, 2025

Smoothie: efficient inference and integration of spatial co-expression networks from denoised spatial transcriptomics

Chase Holdener^1,2, Iwijn De Vlaminck³

¹Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA.

Communications Biology

|March 27, 2026

Summary

This summary is machine-generated.

Smoothie is a new pipeline that analyzes spatial gene expression data. It effectively denoises data and builds gene co-expression networks, enabling deeper biological insights from spatial transcriptomics.

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Area of Science:

Genomics
Bioinformatics
Systems Biology

Background:

Spatial transcriptomics reveals gene co-expression patterns crucial for understanding tissue biology.
Data sparsity and noise present significant challenges in analyzing spatial transcriptomics datasets.
Existing methods struggle to scale for comprehensive genome-wide co-expression network construction.

Purpose of the Study:

To introduce Smoothie, a scalable computational pipeline for denoising spatial transcriptomics data.
To construct and integrate genome-wide co-expression networks from spatial gene expression data.
To enable robust gene module detection and functional annotation using spatial data.

Main Methods:

Gaussian smoothing for denoising spatial transcriptomics data.
Construction and integration of genome-wide co-expression networks.
Implicit and explicit parallelization for handling large-scale datasets.

Main Results:

Smoothie successfully denoises spatial transcriptomics data and builds co-expression networks.
The pipeline scales to datasets with over 100 million spatially resolved spots.
Co-expression networks facilitate gene module detection, functional annotation, and analysis of gene expression dynamics.

Conclusions:

Smoothie offers a scalable and versatile framework for spatial transcriptomics analysis.
The pipeline enhances the extraction of biological insights from high-resolution spatial gene expression data.
Smoothie supports multi-sample comparisons for stable and dynamic gene expression pattern assessment.