表观遗传学
染色质
计算生物学
R包
注释
转录因子
计算机科学
生物
聚类分析
遗传学
数据挖掘
人工智能
DNA
基因
DNA甲基化
基因表达
计算科学
作者
Alicia N. Schep,Beijing Wu,Jason D. Buenrostro,William J. Greenleaf
出处
期刊:Nature Methods
[Springer Nature]
日期:2017-08-21
卷期号:14 (10): 975-978
被引量:1235
摘要
ChromVar infers transcription-factor-associated accessibility from low-coverage or single-cell chromatin-accessibility data, thus enabling the clustering of cells and analysis of regulatory sequence motifs from sparse data sets. Single-cell ATAC-seq (scATAC) yields sparse data that make conventional analysis challenging. We developed chromVAR ( http://www.github.com/GreenleafLab/chromVAR ), an R package for analyzing sparse chromatin-accessibility data by estimating gain or loss of accessibility within peaks sharing the same motif or annotation while controlling for technical biases. chromVAR enables accurate clustering of scATAC-seq profiles and characterization of known and de novo sequence motifs associated with variation in chromatin accessibility.
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