SAW: An efficient and accurate data analysis workflow for Stereo-seq spatial transcriptomics(Dataset ID: STDS0000234)

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Dataset information
Summary:
The basic analysis steps of spatial transcriptomics involves obtaining gene expression information from both space and cells. This process requires a set of tools to be completed, and existing tools face performance issues when dealing with large data sets. These issues include computationally intensive spatial localization, RNA genome alignment, and excessive memory usage in large chip scenarios. These problems affect the applicability and efficiency of the process. To address these issues, a high-performance and accurate spatial transcriptomics data analysis workflow called Stereo-Seq Analysis Workflow (SAW) has been developed for the Stereo-Seq technology developed by BGI. This workflow includes mRNA spatial position reconstruction, genome alignment, gene expression matrix generation and clustering, and generate results files in a universal format for subsequent personalized analysis. The excutation time for the entire analysis process is ~148 minutes on 1G reads 1*1 cm chip test data, 1.8 times faster than unoptimized workflow.
Overall design:
overall_design is gone!
Technology:
Stereo-Seq
Platform:
DNBSEQ-T10
Species:
Mus musculus
Tissues:
Brain
Development stage:
Puberscent
Sex:
Male
Submission date: 2023-06-10Update date: 2023-09-07
Sample number: 1Section number: 1
Contributors
Chun Gong; Shengkang Li; Leying Wang; Fuxiang Zhao; Shuangsang Fang; Dong Yuan; Zijian Zhao; Qiqi He; Mei Li; Weiqing Liu; Zhaoxun Li; Hongqing Xie; Sha Liao; Ao Chen; Yong Zhang; Yuxiang Li; Xun Xu
Contact: gongchun@mgi-tech.com
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Reference way
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