step-kit 0.2.0

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.

STEP: Spatial Transcriptomics Embedding Procedure

Introduction

STEP, an acronym for Spatial Transcriptomics Embedding Procedure, is a foundation deep learning/AI architecture for the analysis of single-cell RNA (scRNA-seq) and spatially resolved transcriptomics (SRT) data. step introduces a unified approach to stepcess 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.

Key Features

• Integration of multiple scRNA-seq and single-cell resolution SRT samples to reveal cell-type level heterogeneities
• Alignment of various SRT data sections contiguous or non-contiguous to identify spatial domains across sections
• Performance of integrative analysis across modalities (scRNA-seq and SRT) and cell-type deconvolution for the non-single-cell resolution SRT data.

Installation

pip install step-kit

require python version 3.10+

Contribution

We welcome contributions! Please see CONTRIBUTING.md for more details!

License

step is licensed under LICENSE