scGAD: single-cell gene associating domain scores for exploratory analysis of scHi-C data.
scGAD: single-cell gene associating domain scores for exploratory analysis of scHi-C data.
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scGAD：用于 scHi-C 数据探索性分析的单细胞基因关联域评分。
DOI：
10.1093/bioinformatics/btac372
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Keleş,Sündüz
中科院分区：
文献类型：
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作者：
Shen,Siqi;Zheng,Ye;Keleş,Sündüz
需要定量工具来利用单细胞高通量染色质构象（scHi-C）数据的前所未有的分辨率，并将其与其他单细胞数据模式整合。我们提出了单细胞基因相关结构域（scGAD）分数作为scHi-C数据的降维和探索性分析工具。scGAD能够在基因单元处进行汇总，同时考虑到固有的基因水平基因组偏差。使用scGAD的低维投影基于细胞的3D结构捕获细胞的聚类。可以用scGAD鉴定细胞类型内和细胞类型之间的显著染色质相互作用。我们进一步表明，scGAD通过将其投影到参考低维嵌入上，促进了scHi-C数据与其他单细胞数据模式的整合。这种多模式数据集成为scHi-C数据提供了自动化和精细化的细胞类型注释。可用性和实施scGAD是BandNormR软件包的一部分，网址为https://sshen82.github.io/BandNorm/articles/scGAD-tutorial.html.Supplementary信息补充数据可在Bioinformatics online获得。
SummaryQuantitative tools are needed to leverage the unprecedented resolution of single-cell high-throughput chromatin conformation (scHi-C) data and integrate it with other single-cell data modalities. We present single-cell gene associating domain (scGAD) scores as a dimension reduction and exploratory analysis tool for scHi-C data. scGAD enables summarization at the gene unit while accounting for inherent gene-level genomic biases. Low-dimensional projections with scGAD capture clustering of cells based on their 3D structures. Significant chromatin interactions within and between cell types can be identified with scGAD. We further show that scGAD facilitates the integration of scHi-C data with other single-cell data modalities by enabling its projection onto reference low-dimensional embeddings. This multi-modal data integration provides an automated and refined cell-type annotation for scHi-C data.Availability and implementationscGAD is part of theBandNormR package at https://sshen82.github.io/BandNorm/articles/scGAD-tutorial.html.Supplementary informationSupplementary data are available atBioinformaticsonline.