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.
Highlights
Transcriptional regulators (TRs), which include transcription factors (TFs) and chromatin regulators (CRs), play essential roles in controlling normal biological processes and are frequently implicated in disease [1,2,3,4]
Regulatory TR prediction based on Cistrome Data Browser (DB) ChIP-seq peaks High-quality TR ChIP-seq data, when available, accurately characterizes genome-wide TR binding sites, which can be used to infer the regulated genes in particular cell types
On the basis of a series of benchmarks, we demonstrate the effectiveness of our method and report recurrent patterns in the TRs predicted by these methods
Summary
Transcriptional regulators (TRs), which include transcription factors (TFs) and chromatin regulators (CRs), play essential roles in controlling normal biological processes and are frequently implicated in disease [1,2,3,4]. There are approximately 1500 transcription factors in humans and mice [10, 11], regulating a wide variety of biological processes in constitutive or cell-type-specific manners, and tens of thousands of ChIP-seq and DNase-seq experiments have been performed in humans and mice. We previously developed the Cistrome Data Browser (DB) [12], a collection of uniformly processed TF ChIPseq (~ 11,000) and chromatin profiles (~ 12,000 histone mark ChIP-seq and DNase-seq) in humans and mice. Chromatin accessibility data, including DNase-seq [16, 17] and ATAC-seq [18], is available for hundreds of cell types and provides maps of the regions in which TRs are likely to be bound in the represented cell types.
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