Modeling gene regulation from matched expression and chromatin accessibility data. Mus musculus

We propose a statistical method to model gene regulation by paired expression and chromatin accessibility (PECA) data, which dissects the regulatory elements (RE) of the genome by modeling their interaction with general chromatin regulators (CR) and sequence-specific transcriptional regulators (TF) and consequent effects on transcriptional changes. Overall design: To generate RNA-seq and ATAC-seq data on the retinoic acid-induced mESC differenation at Day 6.

本研究提出一种基于配对表达与染色质可及性（PECA）数据的基因调控建模统计方法，该方法通过建模基因组调控元件（RE）与一般性染色质调控因子（CR）、序列特异性转录调控因子（TF）的相互作用，及其对转录变化的后续影响，来解析基因组中的调控元件。整体实验设计：在视黄酸诱导的小鼠胚胎干细胞（mESC）分化第6天，获取RNA测序（RNA-seq）与转座酶可及性测序（ATAC-seq）数据。