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Seqtometry 分析单细胞测序数据的方案。

Protocol for analysis of single-cell sequencing data by Seqtometry.

机构信息

Department of Molecular Microbiology and Immunology, Saint Louis University School of Medicine, St. Louis, MO, USA.

Department of Molecular Microbiology and Immunology, Saint Louis University School of Medicine, St. Louis, MO, USA.

出版信息

STAR Protoc. 2024 Sep 20;5(3):103209. doi: 10.1016/j.xpro.2024.103209. Epub 2024 Aug 2.

Abstract

Seqtometry (sequencing-to-measurement) is an analytical platform for single-cell analysis based on direct profiling of gene expression and accessibility achieved by advanced scoring with gene signatures. Here, we present a protocol for single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) analysis using Seqtometry. We describe steps for preprocessing, imputation, scoring, and plotting, with extensions to large datasets and integration of multiple datasets. This protocol yields results in the form of biologically interpretable dimensions for direct identification and comprehensive characterization of specific cells. For complete details on the use and execution of this protocol, please refer to Kousnetsov et al..

摘要

测序计量(sequencing-to-measurement)是一种基于基因表达直接分析和基因特征高级评分的单细胞分析的分析平台。在这里,我们介绍了一种使用 Seqtometry 进行单细胞 RNA 测序(scRNA-seq)和单细胞转座酶可及染色质测序(scATAC-seq)分析的协议。我们描述了预处理、插补、评分和绘图的步骤,并扩展到了大型数据集和多个数据集的集成。该方案以可直接识别和全面描述特定细胞的生物学可解释维度的形式生成结果。有关此方案的使用和执行的完整详细信息,请参阅 Kousnetsov 等人的研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/221a/11342777/0716566fcc59/fx1.jpg

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