Abstract
Recently, several protocols repurposing the Illumina flow cells or DNA nanoballs as an RNA capture device for spatial transcriptomics have been reported. These protocols yield high volumes of sequencing data which are usually analyzed through the use of high-performance computing clusters. I report Fast analysis of Spatial Transcriptomic (FaST), a novel pipeline for the analysis of subcellular resolution spatial transcriptomics datasets based on barcoding. FaST is compatible with OpenST, seq-scope, Stereo-seq, and potentially other protocols. It allows full reconstruction of the spatially resolved transcriptome, including cell segmentation, of datasets consisting of >500 M million reads in as little as 1 h on a standard multi core workstation with 32 Gb of RAM. The FaST pipeline returns RNA segmented Spatial Transcriptomics datasets suitable for subsequent analysis through commonly used packages (e.g scanpy or seurat). Notably, the pipeline I present relies on the spateo-release package for RNA segmentation and does not require hematoxylin/eosin or any other imaging procedure to guide cell segmentation. Nevertheless, integration with other software for imaging-guided cell segmentation is still possible. FaST is publicly available on github (https://github.com/flcvlr/FaST).