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Lisa: inferring transcriptional regulators through integrative modeling of public chromatin accessibility and ChIP-seq data

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...

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Detalles Bibliográficos
Autores principales: Qin, Qian, Fan, Jingyu, Zheng, Rongbin, Wan, Changxin, Mei, Shenglin, Wu, Qiu, Sun, Hanfei, Brown, Myles, Zhang, Jing, Meyer, Clifford A., Liu, X. Shirley
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7007693/
https://www.ncbi.nlm.nih.gov/pubmed/32033573
http://dx.doi.org/10.1186/s13059-020-1934-6
Descripción
Sumario: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.