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STEP, an acronym for Spatial Transcriptomics Embedding Procedure, is a deep learning-based tool for the analysis of single-cell RNA (scRNA-seq) and spatially resolved transcriptomics (SRT) data. step introduces a unified approach to process and analyze multiple samples of scRNA-seq data as well as align several sections of SRT data, disregarding location relationships. Furthermore, step conducts integrative analysis across different modalities like scRNA-seq and SRT.
Spatial domain identification on 10x Visium DLFPC data
Performing integrative analysis on scRNA-seq data and 10x Visium data of Human Lymph Node with STEP
Reveal multiple level of biological heterogeneities in Mouse Hypothalamus by MERFISH-seq
Integrate Human Immune Cell datasets with STEP and generate batch-corrected embeddings and gene expressions.