HemaScope: A Tool for Analyzing Single-cell and Spatial Transcriptomics Data of Hematopoietic Cells.

IF 7.9
Zhenyi Wang, Yuxin Miao, Hongjun Li, Wenyan Cheng, Minglei Shi, Lv Gang, Yating Zhu, Junyi Zhang, Tingting Tan, Jin Gu, Michael Q Zhang, Jianfeng Li, Hai Fang, Zhu Chen, Saijuan Chen
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Abstract

Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) techniques hold great value in evaluating the heterogeneity and spatial characteristics of hematopoietic cells within tissues. These two techniques are highly complementary, with scRNA-seq offering single-cell resolution and ST retaining spatial information. However, there is an urgent demand for well-organized and user-friendly toolkits capable of handling single-cell and spatial information. Here, we present HemaScope, a specialized bioinformatics toolkit featuring modular designs to analyze scRNA-seq and ST data generated from hematopoietic cells. It enables users to perform quality control, basic analysis, cell atlas construction, cellular heterogeneity exploration, and dynamical examination on scRNA-seq data. Also, it can perform spatial analysis and microenvironment analysis on ST data. Meanwhile, HemaScope takes into consideration hematopoietic cell-specific features, including lineage affiliation evaluation, cell cycle prediction, and marker gene collection. To enhance the user experience, we have deployed the toolkit in user-friendly forms: HemaScopeR (an R package), HemaScopeCloud (a web server), HemaScopeDocker (a Docker image), and HemaScopeShiny (a graphical interface). In case studies, we employed it to construct a cell atlas of human bone marrow, analyze age-related changes, and identify acute myeloid leukemia cells in mice. Moreover, we characterized the microenvironments in angioimmunoblastic T cell lymphoma and primary central nervous system lymphoma, elucidating tumor boundaries. HemaScope is freely available at https://zhenyiwangthu.github.io/HemaScope_Tutorial/.

血镜:分析造血细胞单细胞和空间转录组学数据的工具。
单细胞RNA测序(scRNA-seq)和空间转录组学(ST)技术在评估组织内造血细胞的异质性和空间特征方面具有重要价值。这两种技术是高度互补的,scRNA-seq提供单细胞分辨率,而ST保留空间信息。然而,迫切需要能够处理单细胞和空间信息的组织良好和用户友好的工具包。在这里,我们介绍了HemaScope,一个专门的生物信息学工具包,具有模块化设计,可以分析造血细胞产生的scRNA-seq和ST数据。它使用户能够对scRNA-seq数据进行质量控制、基础分析、细胞图谱构建、细胞异质性探索和动态检查。还可以对ST数据进行空间分析和微环境分析。同时,HemaScope还考虑了造血细胞的特异性,包括谱系归属评估、细胞周期预测和标记基因收集。为了增强用户体验,我们以用户友好的形式部署了这个工具包:HemaScopeR(一个R包)、HemaScopeCloud(一个web服务器)、HemaScopeDocker(一个Docker镜像)和HemaScopeShiny(一个图形界面)。在案例研究中,我们利用它构建了人类骨髓细胞图谱,分析了与年龄相关的变化,并鉴定了小鼠的急性髓性白血病细胞。此外,我们描述了血管免疫母细胞T细胞淋巴瘤和原发性中枢神经系统淋巴瘤的微环境,阐明了肿瘤的边界。HemaScope可在https://zhenyiwangthu.github.io/HemaScope_Tutorial/免费获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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