Journal article Open Access
Lisa: inferring transcriptional regulators through integrative modeling of public chromatin accessibility and ChIP-seq data
Qian Qin;
Jingyu Fan;
Rongbin Zheng;
Changxin Wan;
Shenglin Mei;
Qiu Wu;
Hanfei Sun;
Jing Zhang;
Myles Brown;
Clifford A. Meyer;
X. Shirley Liu
We develop Lisa (epigenetic Landscape In silico Sequence Analysis) to predict transcriptional regulators (TRs) of differentially expressed or co-expressed gene sets. Based on input gene sets, Lisa first uses histone mark ChIP-seq and chromatin accessibility profiles to construct a chromatin model related to the regulation of these genes. Using TR ChIP-seq peaks or imputed TR binding sites, Lisa probes the chromatin models using in silico deletion to find the most relevant TRs. Applied to gene sets derived from targeted TF perturbation experiments, Lisa boosts the performance of imputed TR cistromes, and outperforms alternative methods in identifying the perturbed TRs.
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- Publication date:
- December 19, 2019
- DOI:
-
- Keyword(s):
- Transcription factors gene regulation chromatin accessibility DNase-seq H3K27ac ChIP-seq differential gene expression gene set analysis
- Related identifiers:
- Source of
- 10.1101/846139 (Preprint)
- License (for files):
- MIT License