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Matching queried single-cell open-chromatin profiles to large pools of single-cell transcriptomes and epigenomes for reference supported analysis
Genome Research ( IF 7 ) Pub Date : 2023-02-01 , DOI: 10.1101/gr.277015.122
Shreya Mishra 1 , Neetesh Pandey 1 , Smriti Chawla 1 , Madhu Sharma 1 , Omkar Chandra 1 , Indra Prakash Jha 1 , Debarka SenGupta 1, 2 , Kedar Nath Natarajan 3 , Vibhor Kumar 4
Affiliation  

The true benefits of large single-cell transcriptome and epigenome data sets can be realized only with the development of new approaches and search tools for annotating individual cells. Matching a single-cell epigenome profile to a large pool of reference cells remains a major challenge. Here, we present scEpiSearch, which enables searching, comparison, and independent classification of single-cell open-chromatin profiles against a large reference of single-cell expression and open-chromatin data sets. Across performance benchmarks, scEpiSearch outperformed multiple methods in accuracy of search and low-dimensional coembedding of single-cell profiles, irrespective of platforms and species. Here we also demonstrate the unconventional utilities of scEpiSearch by applying it on single-cell epigenome profiles of K562 cells and samples from patients with acute leukaemia to reveal different aspects of their heterogeneity, multipotent behavior, and dedifferentiated states. Applying scEpiSearch on our single-cell open-chromatin profiles from embryonic stem cells (ESCs), we identified ESC subpopulations with more activity and poising for endoplasmic reticulum stress and unfolded protein response. Thus, scEpiSearch solves the nontrivial problem of amalgamating information from a large pool of single cells to identify and study the regulatory states of cells using their single-cell epigenomes.

中文翻译:

将查询的单细胞开放染色质图谱与大量单细胞转录组和表观基因组进行匹配,以进行参考支持的分析

只有开发用于注释单个细胞的新方法和搜索工具,才能实现大型单细胞转录组和表观基因组数据集的真正好处。将单细胞表观基因组图谱与大量参考细胞进行匹配仍然是一个重大挑战。在这里,我们提出了 scEpiSearch,它能够根据单细胞表达和开放染色质数据集的大量参考对单细胞开放染色质图谱进行搜索、比较和独立分类。在性能基准测试中,无论平台和物种如何,scEpiSearch 在搜索准确性和单细胞图谱低维共嵌入方面均优于多种方法。在这里,我们还展示了 scEpiSearch 的非常规实用性,将其应用于 K562 细胞的单细胞表观基因组图谱和急性白血病患者的样本,以揭示其异质性、多能行为和去分化状态的不同方面。通过对胚胎干细胞 (ESC) 的单细胞开放染色质图谱应用 scEpiSearch,我们发现了具有更高活性并能应对内质网应激和未折叠蛋白反应的 ESC 亚群。因此,scEpiSearch 解决了合并大量单细胞信息以利用单细胞表观基因组识别和研究细胞调节状态的重要问题。
更新日期:2023-02-01
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