Characterizing epigenetic heterogeneity at the cellular level is a critical problem in the modern genomics era. Assays such as single cell ATAC-seq (scATAC-seq) offer an opportunity to interrogate cellular level epigenetic heterogeneity through patterns of variability in open chromatin. However, these assays exhibit technical variability that complicates clear classification and cell type identification in heterogeneous populations. We present scABC, an R package for the unsupervised clustering of single-cell epigenetic data, to classify scATAC-seq data and discover regions of open chromatin specific to cell identity.

中文翻译：

---

单细胞的无监督聚类和表观遗传分类。

在细胞水平上表征表观遗传异质性是现代基因组学时代的一个关键问题。诸如单细胞ATAC-seq（scATAC-seq）之类的测定法提供了通过开放染色质变异性模式询问细胞水平表观遗传异质性的机会。但是，这些测定法显示出技术变异性，这使异质群体中的清晰分类和细胞类型鉴定变得复杂。我们提出了scABC，R包用于单细胞表观遗传数据的无监督聚类，以对scATAC-seq数据进行分类并发现特定于细胞身份的开放染色质区域。