SpatialQC：空间转录组数据的自动化质量控制。

SpatialQC: automated quality control for spatial transcriptome data.

机构信息

Key Laboratory of Developmental Genes and Human Disease, School of Life Science and Technology, Southeast University, Nanjing 210000, China.

Co-innovation Center of Neuroregeneration, Nantong University, Nantong 226000, China.

出版信息

Bioinformatics. 2024 Aug 2;40(8). doi: 10.1093/bioinformatics/btae458.

DOI:10.1093/bioinformatics/btae458

PMID:39051702

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11333854/

Abstract

SUMMARY

The advent of spatial transcriptomics has revolutionized our understanding of the spatial heterogeneity in tissues, providing unprecedented insights into the cellular and molecular mechanisms underlying biological processes. Although quality control (QC) critical for downstream data analyses, there is currently a lack of specialized tools for one-stop spatial transcriptome QC. Here, we introduce SpatialQC, a one-stop QC pipeline, which generates comprehensive QC reports and produces clean data in an interactive fashion. SpatialQC is widely applicable to spatial transcriptomic techniques.

AVAILABILITY AND IMPLEMENTATION

source code and user manuals are available via https://github.com/mgy520/spatialQC, and deposited on Zenodo (https://doi.org/10.5281/zenodo.12634669).

摘要

空间转录组学的出现彻底改变了我们对组织中空间异质性的理解，为生物过程背后的细胞和分子机制提供了前所未有的见解。尽管质量控制（QC）对于下游数据分析至关重要，但目前缺乏用于一站式空间转录组 QC 的专用工具。在这里，我们介绍了 SpatialQC，这是一个一站式 QC 管道，它以交互方式生成全面的 QC 报告并生成清洁数据。SpatialQC 广泛适用于空间转录组学技术。