Interactive single-cell data analysis using Cellar.

Interactive single-cell data analysis using Cellar.
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DOI:
10.1038/s41467-022-29744-0
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发表时间:
2022-04-14
影响因子:
16.6
通讯作者:
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中科院分区:
综合性期刊1区
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细胞类型分配是所有类型的高通量单细胞数据的主要挑战。在许多情况下,这种分配需要反复手工使用外部和补充数据源。为了提高在大型联盟、平台和模式中统一分配细胞类型的能力,我们开发了Cellar,这是一种软件工具,为分配和数据集比较过程中涉及的所有不同步骤提供交互式支持。我们讨论了Cellar实现的不同方法,这些方法如何与不同的数据类型一起使用,如何联合收割机互补数据类型以及如何分析和可视化空间数据。我们通过使用Cellar来注释来自多组学单细胞测序和空间蛋白质组学研究的几个HuBMAP数据集,展示了Cellar的优势。Cellar是开源的,包括几个带注释的HuBMAP数据集。在这里,作者介绍了Cellar,一个用于分析单细胞组学数据的交互式网络服务器。它们表明Cellar支持分析和建模过程的各个方面,并可用于整合不同类型的单细胞组学和空间数据。
Cell type assignment is a major challenge for all types of high throughput single cell data. In many cases such assignment requires the repeated manual use of external and complementary data sources. To improve the ability to uniformly assign cell types across large consortia, platforms and modalities, we developed Cellar, a software tool that provides interactive support to all the different steps involved in the assignment and dataset comparison process. We discuss the different methods implemented by Cellar, how these can be used with different data types, how to combine complementary data types and how to analyze and visualize spatial data. We demonstrate the advantages of Cellar by using it to annotate several HuBMAP datasets from multi-omics single-cell sequencing and spatial proteomics studies. Cellar is open-source and includes several annotated HuBMAP datasets. Here the authors introduce Cellar, an interactive webserver for analyzing single-cell omics data. They show that Cellar supports all aspects of the analysis and modeling process and can be used to integrate different types of single cell omics and spatial data.
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