Fast analysis of Spatial Transcriptomics (FaST): an ultra lightweight and fast pipeline for the analysis of high...

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• Spatial transcriptomics protocols often generate large datasets requiring high-performance computing.
• Existing analysis methods can be computationally intensive and time-consuming.

Purpose of the Study:

• To introduce Fast analysis of Spatial Transcriptomic (FaST), a novel bioinformatics pipeline.
• To enable rapid analysis of high-throughput spatial transcriptomics data on standard hardware.

Main Methods:

• FaST pipeline utilizes barcoding for subcellular resolution spatial transcriptomics data analysis.
• The pipeline is compatible with multiple spatial transcriptomics protocols (e.g., OpenST, seq-scope, Stereo-seq).
• RNA segmentation is performed using the spateo-release package without requiring imaging data.

Main Results:

• FaST enables full reconstruction of spatially resolved transcriptomes, including cell segmentation.
• Analysis of datasets with over 500 million reads is achievable in approximately 1 hour on a standard workstation.
• The pipeline generates segmented spatial transcriptomics datasets compatible with common analysis packages like Scanpy and Seurat.

Conclusions:

• FaST significantly accelerates the analysis of spatial transcriptomics datasets.
• The pipeline offers an efficient and accessible solution for researchers studying spatial gene expression.
• FaST facilitates downstream analysis and integration with other spatial biology tools.