Genome Biology (Feb 2020)

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,
  • Myles Brown,
  • Jing Zhang,
  • Clifford A. Meyer,
  • X. Shirley Liu

DOI
https://doi.org/10.1186/s13059-020-1934-6
Journal volume & issue
Vol. 21, no. 1
pp. 1 – 14

Abstract

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Abstract We developed Lisa ( http://lisa.cistrome.org/ ) to predict the transcriptional regulators (TRs) of differentially expressed or co-expressed gene sets. Based on the 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 boosted the performance of imputed TR cistromes and outperformed alternative methods in identifying the perturbed TRs.

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