转载自 http://cole-trapnell-lab.github.io/projects/sc-atac/
基于cell barcode ,无需FACS/mannual select 物理方法分选细胞 construct library,即可对单个细胞加上index, 处理细胞量与花费时间 、费用sublinearly 非线性关系，so,可以较低的实验成本来实现对单个细胞水平之间比较细胞状态、染色质的开放程度、关键元件的调控机制等。
传统PCA难以应对大量细胞的高维度、稀疏的数据。
Papers
Joint profiling of chromatin accessibility and gene expression in thousands of single cells
Cicero predicts cis-regulatory DNA interactions from single-cell chromatin accessibility data
A single-cell atlas of in vivo mammalian chromatin accessibility
The cis-regulatory dynamics of embryonic development at single-cell resolution
Defining cell types and states with single-cell genomics
Multiplex single-cell profiling of chromatin accessibility by combinatorial cellular indexing
[https://research.jetbrains.org/files/material/5c3f48ef1b2b5.pdf]
ATAC-Seq 方法总结
https://www.biorxiv.org/content/10.1101/739011v1
https://www.cell.com/cell/fulltext/S0092-8674(18)30446-X
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